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| author | Nikhil Raj <nikhil.raj@arm.com> | 2022-03-08 20:01:38 +0000 |
|---|---|---|
| committer | Nikhil Raj <nikhil.raj@arm.com> | 2022-03-09 12:26:14 +0000 |
| commit | f4019872c1134c6fcc1d6993e5746f55c1e79208 (patch) | |
| tree | b07ea8bdd70d696adfa3814344e210ea67be1e8c /22.02/_unidirectional_sequence_lstm_test_impl_8cpp.xhtml | |
| parent | 0d75c02b21b919b81035205f3914ee273b93b30c (diff) | |
| download | armnn-f4019872c1134c6fcc1d6993e5746f55c1e79208.tar.gz | |
IVGCVSW-6819 Fix the directory structure and broken link to latest docu
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: I05b559d15faf92c76ff536719693b361316be4f3
Diffstat (limited to '22.02/_unidirectional_sequence_lstm_test_impl_8cpp.xhtml')
| -rw-r--r-- | 22.02/_unidirectional_sequence_lstm_test_impl_8cpp.xhtml | 855 |
1 files changed, 855 insertions, 0 deletions
diff --git a/22.02/_unidirectional_sequence_lstm_test_impl_8cpp.xhtml b/22.02/_unidirectional_sequence_lstm_test_impl_8cpp.xhtml new file mode 100644 index 0000000000..6ea6b5f5bc --- /dev/null +++ b/22.02/_unidirectional_sequence_lstm_test_impl_8cpp.xhtml @@ -0,0 +1,855 @@ +<!-- Copyright (c) 2020 ARM Limited. --> +<!-- --> +<!-- SPDX-License-Identifier: MIT --> +<!-- --> +<!-- HTML header for doxygen 1.8.13--> +<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> +<html xmlns="http://www.w3.org/1999/xhtml"> +<head> +<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/> +<meta http-equiv="X-UA-Compatible" content="IE=9"/> +<meta name="generator" content="Doxygen 1.8.13"/> +<meta name="robots" content="NOINDEX, NOFOLLOW" /> +<meta name="viewport" content="width=device-width, initial-scale=1"/> +<title>ArmNN: src/backends/backendsCommon/test/layerTests/UnidirectionalSequenceLstmTestImpl.cpp File 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class="header"> + <div class="summary"> +<a href="#func-members">Functions</a> </div> + <div class="headertitle"> +<div class="title">UnidirectionalSequenceLstmTestImpl.cpp File Reference</div> </div> +</div><!--header--> +<div class="contents"> +<div class="textblock"><code>#include "<a class="el" href="_unidirectional_sequence_lstm_test_impl_8hpp_source.xhtml">UnidirectionalSequenceLstmTestImpl.hpp</a>"</code><br /> +<code>#include <<a class="el" href="_numeric_cast_8hpp_source.xhtml">armnn/utility/NumericCast.hpp</a>></code><br /> +<code>#include <<a class="el" href="include_2armnn_2backends_2_tensor_handle_8hpp_source.xhtml">armnn/backends/TensorHandle.hpp</a>></code><br /> +<code>#include <<a class="el" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_source.xhtml">armnnTestUtils/TensorCopyUtils.hpp</a>></code><br /> +<code>#include <<a class="el" href="include_2armnn_test_utils_2_workload_test_utils_8hpp_source.xhtml">armnnTestUtils/WorkloadTestUtils.hpp</a>></code><br /> +<code>#include <<a class="el" href="_resolve_type_8hpp_source.xhtml">ResolveType.hpp</a>></code><br /> +</div> +<p><a href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml">Go to the source code of this file.</a></p> +<table class="memberdecls"> +<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> +Functions</h2></td></tr> +<tr class="memitem:ab5aedf0fbe3810773302b480ff1ef0fe"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 3 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp.xhtml#ab5aedf0fbe3810773302b480ff1ef0fe">UnidirectionalSequenceLstmLayerFloat32Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:ab5aedf0fbe3810773302b480ff1ef0fe"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a3e62d48c04adef20dc1e813544e5792f"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 3 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp.xhtml#a3e62d48c04adef20dc1e813544e5792f">UnidirectionalSequenceLstmLayerFloat32TimeMajorTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:a3e62d48c04adef20dc1e813544e5792f"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:ab8fb90e22b99c4d41ad3566fd5968829"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 3 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp.xhtml#ab8fb90e22b99c4d41ad3566fd5968829">UnidirectionalSequenceLstmLayerNoCifgWithPeepholeWithProjectionTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:ab8fb90e22b99c4d41ad3566fd5968829"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:adf8faacc3aacfa0b1342d78cfe1b61fe"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 3 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp.xhtml#adf8faacc3aacfa0b1342d78cfe1b61fe">UnidirectionalSequenceLstmLayerNoCifgWithPeepholeWithProjectionWithLayerNormTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:adf8faacc3aacfa0b1342d78cfe1b61fe"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a5c36dcbd8e95871d57e8a50222a02494"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 3 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp.xhtml#a5c36dcbd8e95871d57e8a50222a02494">UnidirectionalSequenceLstmWithCifgWithPeepholeNoProjectionTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:a5c36dcbd8e95871d57e8a50222a02494"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a96b8e256c3e15254d98f27f291d6befb"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 3 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp.xhtml#a96b8e256c3e15254d98f27f291d6befb">UnidirectionalSequenceLstmLayerInt8Test</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:a96b8e256c3e15254d98f27f291d6befb"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:af09125829e58e0e9e05e0ecd3f1bcacb"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 3 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp.xhtml#af09125829e58e0e9e05e0ecd3f1bcacb">UnidirectionalSequenceLstmLayerInt8TimeMajorTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:af09125829e58e0e9e05e0ecd3f1bcacb"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a8a1a97bb52fc24a8d66e2c2dd98c6d9b"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 3 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp.xhtml#a8a1a97bb52fc24a8d66e2c2dd98c6d9b">UnidirectionalSequenceLstmLayerInt8NoCifgWithPeepholeWithProjectionTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:a8a1a97bb52fc24a8d66e2c2dd98c6d9b"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:af7d1e03806f56e8e8e1444f16d735af5"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 3 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp.xhtml#af7d1e03806f56e8e8e1444f16d735af5">UnidirectionalSequenceLstmLayerInt8NoCifgWithPeepholeWithProjectionWithLayerNormTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:af7d1e03806f56e8e8e1444f16d735af5"><td class="memSeparator" colspan="2"> </td></tr> +<tr class="memitem:a45a379eda493e31f0f34de4aa69c7b65"><td class="memItemLeft" align="right" valign="top"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a>< float, 3 > </td><td class="memItemRight" valign="bottom"><a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp.xhtml#a45a379eda493e31f0f34de4aa69c7b65">UnidirectionalSequenceLstmInt8WithCifgWithPeepholeNoProjectionTest</a> (<a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> &workloadFactory, const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> &memoryManager, const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> &tensorHandleFactory)</td></tr> +<tr class="separator:a45a379eda493e31f0f34de4aa69c7b65"><td class="memSeparator" colspan="2"> </td></tr> +</table> +<h2 class="groupheader">Function Documentation</h2> +<a id="a45a379eda493e31f0f34de4aa69c7b65"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a45a379eda493e31f0f34de4aa69c7b65">◆ </a></span>UnidirectionalSequenceLstmInt8WithCifgWithPeepholeNoProjectionTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 3> UnidirectionalSequenceLstmInt8WithCifgWithPeepholeNoProjectionTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml#l01672">1672</a> of file <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml">UnidirectionalSequenceLstmTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01541">IWorkloadFactory::CreateWorkload()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01104">LstmDescriptor::m_ActivationFunc</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00750">UnidirectionalSequenceLstmQueueDescriptor::m_CellToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00751">UnidirectionalSequenceLstmQueueDescriptor::m_CellToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01110">LstmDescriptor::m_CifgEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01106">LstmDescriptor::m_ClippingThresCell</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01108">LstmDescriptor::m_ClippingThresProj</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01112">LstmDescriptor::m_PeepholeEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01114">LstmDescriptor::m_ProjectionEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01118">LstmDescriptor::m_TimeMajor</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::QAsymmS8</a>, and <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::UnidirectionalSequenceLstm</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l01676"></a><span class="lineno"> 1676</span> {</div><div class="line"><a name="l01677"></a><span class="lineno"> 1677</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l01678"></a><span class="lineno"> 1678</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 3;</div><div class="line"><a name="l01679"></a><span class="lineno"> 1679</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> timeSize = 2;</div><div class="line"><a name="l01680"></a><span class="lineno"> 1680</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputSize = 3;</div><div class="line"><a name="l01681"></a><span class="lineno"> 1681</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = 4;</div><div class="line"><a name="l01682"></a><span class="lineno"> 1682</span>  <span class="keywordtype">unsigned</span> numUnits = outputSize;</div><div class="line"><a name="l01683"></a><span class="lineno"> 1683</span> </div><div class="line"><a name="l01684"></a><span class="lineno"> 1684</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({batchSize, timeSize, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01685"></a><span class="lineno"> 1685</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> cellStateInTensorInfo({batchSize, numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01686"></a><span class="lineno"> 1686</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputStateInTensorInfo({batchSize, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01687"></a><span class="lineno"> 1687</span> </div><div class="line"><a name="l01688"></a><span class="lineno"> 1688</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({batchSize, timeSize, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01689"></a><span class="lineno"> 1689</span> </div><div class="line"><a name="l01690"></a><span class="lineno"> 1690</span>  <span class="keyword">const</span> std::vector<float> inputVector = { 0.1f, 0.2f, 0.3f, 0.4f, 0.5f, 0.4f,</div><div class="line"><a name="l01691"></a><span class="lineno"> 1691</span>  0.3f, 0.2f, 0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l01692"></a><span class="lineno"> 1692</span>  0.5f, 0.4f, 0.3f, 0.2f, 0.1f, 0.2f };</div><div class="line"><a name="l01693"></a><span class="lineno"> 1693</span> </div><div class="line"><a name="l01694"></a><span class="lineno"> 1694</span>  std::vector<float> cellStateInVector(batchSize * numUnits, 0.f);</div><div class="line"><a name="l01695"></a><span class="lineno"> 1695</span>  std::vector<float> outputStateInVector(batchSize * outputSize, 0.f);</div><div class="line"><a name="l01696"></a><span class="lineno"> 1696</span> </div><div class="line"><a name="l01697"></a><span class="lineno"> 1697</span>  std::vector<float> actualOutput(outputTensorInfo.GetNumElements());</div><div class="line"><a name="l01698"></a><span class="lineno"> 1698</span> </div><div class="line"><a name="l01699"></a><span class="lineno"> 1699</span>  <span class="keyword">const</span> std::vector<float> outputVector = { -0.0072104f, -0.00991171f, -0.00650478f, -0.00713055f,</div><div class="line"><a name="l01700"></a><span class="lineno"> 1700</span>  -0.0191782f, -0.0161269f, -0.0233683f, -0.054299f,</div><div class="line"><a name="l01701"></a><span class="lineno"> 1701</span>  -0.00783725f, 0.00635271f, -0.0126718f, -0.022613f,</div><div class="line"><a name="l01702"></a><span class="lineno"> 1702</span>  -0.0161351f, -0.00775868f, -0.021054f, -0.0339778f,</div><div class="line"><a name="l01703"></a><span class="lineno"> 1703</span>  -0.0146392f, 0.00330261f, -0.0258733f, -0.0407797f,</div><div class="line"><a name="l01704"></a><span class="lineno"> 1704</span>  -0.0174297f, 0.0050105f, -0.0266275f, -0.0362564f };</div><div class="line"><a name="l01705"></a><span class="lineno"> 1705</span> </div><div class="line"><a name="l01706"></a><span class="lineno"> 1706</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l01707"></a><span class="lineno"> 1707</span>  std::unique_ptr<armnn::ITensorHandle> cellStateInHandle =</div><div class="line"><a name="l01708"></a><span class="lineno"> 1708</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(cellStateInTensorInfo);</div><div class="line"><a name="l01709"></a><span class="lineno"> 1709</span>  std::unique_ptr<armnn::ITensorHandle> outputStateInHandle =</div><div class="line"><a name="l01710"></a><span class="lineno"> 1710</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputStateInTensorInfo);</div><div class="line"><a name="l01711"></a><span class="lineno"> 1711</span> </div><div class="line"><a name="l01712"></a><span class="lineno"> 1712</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l01713"></a><span class="lineno"> 1713</span> </div><div class="line"><a name="l01714"></a><span class="lineno"> 1714</span>  <a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a> data;</div><div class="line"><a name="l01715"></a><span class="lineno"> 1715</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l01716"></a><span class="lineno"> 1716</span> </div><div class="line"><a name="l01717"></a><span class="lineno"> 1717</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l01718"></a><span class="lineno"> 1718</span>  AddInputToWorkload(data, info, outputStateInTensorInfo, outputStateInHandle.get());</div><div class="line"><a name="l01719"></a><span class="lineno"> 1719</span>  AddInputToWorkload(data, info, cellStateInTensorInfo, cellStateInHandle.get());</div><div class="line"><a name="l01720"></a><span class="lineno"> 1720</span> </div><div class="line"><a name="l01721"></a><span class="lineno"> 1721</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l01722"></a><span class="lineno"> 1722</span> </div><div class="line"><a name="l01723"></a><span class="lineno"> 1723</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumFp({numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01724"></a><span class="lineno"> 1724</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNum({numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01725"></a><span class="lineno"> 1725</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumInput({numUnits, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01726"></a><span class="lineno"> 1726</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumOutput({numUnits, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01727"></a><span class="lineno"> 1727</span> </div><div class="line"><a name="l01728"></a><span class="lineno"> 1728</span>  std::vector<int8_t> inputToForgetWeights = { 2, 1, 4, -4, 3, -1, -3, -2, -3, 1, -4, -1 };</div><div class="line"><a name="l01729"></a><span class="lineno"> 1729</span>  std::vector<int8_t> inputToCellWeights = { -2, 1, -2, 4, -3, -2, -4, 3, -2, -2, -6, 3 };</div><div class="line"><a name="l01730"></a><span class="lineno"> 1730</span>  std::vector<int8_t> inputToOutputWeights = { 2, 5, -4, 5, 2, -3, 5, 7, 3, -5, 1, -4 };</div><div class="line"><a name="l01731"></a><span class="lineno"> 1731</span> </div><div class="line"><a name="l01732"></a><span class="lineno"> 1732</span>  std::vector<int8_t> recurrentToForgetWeights = { -1, 1, -1, 1, -3, -4, -1, 4, 2, 3, 5, -1, 1, 3, -2, -1 };</div><div class="line"><a name="l01733"></a><span class="lineno"> 1733</span>  std::vector<int8_t> recurrentToCellWeights = { -2, -3, -1, -3, -4, 2, 1, -1, 2, 2, 1, 2, 3, -2, 3, -3 };</div><div class="line"><a name="l01734"></a><span class="lineno"> 1734</span>  std::vector<int8_t> recurrentToOutputWeights = { -3, 3, -1, -2, -2, -2, -1, -5, 1, 3, -4, -1, -1, -1, 2, -1 };</div><div class="line"><a name="l01735"></a><span class="lineno"> 1735</span> </div><div class="line"><a name="l01736"></a><span class="lineno"> 1736</span>  std::vector<int8_t> cellToForgetWeights = { 47, -52, -24, 31 };</div><div class="line"><a name="l01737"></a><span class="lineno"> 1737</span>  std::vector<int8_t> cellToOutputWeights = { -17, 82, 85, -77 };</div><div class="line"><a name="l01738"></a><span class="lineno"> 1738</span> </div><div class="line"><a name="l01739"></a><span class="lineno"> 1739</span>  std::vector<float> forgetGateBias = { 1., 1., 1., 1. };</div><div class="line"><a name="l01740"></a><span class="lineno"> 1740</span>  std::vector<float> cellBias = { 0., 0., 0., 0. };</div><div class="line"><a name="l01741"></a><span class="lineno"> 1741</span>  std::vector<float> outputGateBias = { 0., 0., 0., 0. };</div><div class="line"><a name="l01742"></a><span class="lineno"> 1742</span> </div><div class="line"><a name="l01743"></a><span class="lineno"> 1743</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToForgetWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01744"></a><span class="lineno"> 1744</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToCellWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01745"></a><span class="lineno"> 1745</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToOutputWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01746"></a><span class="lineno"> 1746</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToForgetWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01747"></a><span class="lineno"> 1747</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToCellWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01748"></a><span class="lineno"> 1748</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToOutputWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01749"></a><span class="lineno"> 1749</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToForgetWeightsTensor(tensorInfoNum);</div><div class="line"><a name="l01750"></a><span class="lineno"> 1750</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToOutputWeightsTensor(tensorInfoNum);</div><div class="line"><a name="l01751"></a><span class="lineno"> 1751</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> forgetGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01752"></a><span class="lineno"> 1752</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01753"></a><span class="lineno"> 1753</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> outputGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01754"></a><span class="lineno"> 1754</span> </div><div class="line"><a name="l01755"></a><span class="lineno"> 1755</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToForgetWeightsTensor, inputToForgetWeights.data());</div><div class="line"><a name="l01756"></a><span class="lineno"> 1756</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToCellWeightsTensor, inputToCellWeights.data());</div><div class="line"><a name="l01757"></a><span class="lineno"> 1757</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToOutputWeightsTensor, inputToOutputWeights.data());</div><div class="line"><a name="l01758"></a><span class="lineno"> 1758</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToForgetWeightsTensor, recurrentToForgetWeights.data());</div><div class="line"><a name="l01759"></a><span class="lineno"> 1759</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToCellWeightsTensor, recurrentToCellWeights.data());</div><div class="line"><a name="l01760"></a><span class="lineno"> 1760</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToOutputWeightsTensor, recurrentToOutputWeights.data());</div><div class="line"><a name="l01761"></a><span class="lineno"> 1761</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToForgetWeightsTensor, cellToForgetWeights.data());</div><div class="line"><a name="l01762"></a><span class="lineno"> 1762</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToOutputWeightsTensor, cellToOutputWeights.data());</div><div class="line"><a name="l01763"></a><span class="lineno"> 1763</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&forgetGateBiasTensor, forgetGateBias.data());</div><div class="line"><a name="l01764"></a><span class="lineno"> 1764</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellBiasTensor, cellBias.data());</div><div class="line"><a name="l01765"></a><span class="lineno"> 1765</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&outputGateBiasTensor, outputGateBias.data());</div><div class="line"><a name="l01766"></a><span class="lineno"> 1766</span> </div><div class="line"><a name="l01767"></a><span class="lineno"> 1767</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">m_InputToForgetWeights</a> = &inputToForgetWeightsTensor;</div><div class="line"><a name="l01768"></a><span class="lineno"> 1768</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">m_InputToCellWeights</a> = &inputToCellWeightsTensor;</div><div class="line"><a name="l01769"></a><span class="lineno"> 1769</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">m_InputToOutputWeights</a> = &inputToOutputWeightsTensor;</div><div class="line"><a name="l01770"></a><span class="lineno"> 1770</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeightsTensor;</div><div class="line"><a name="l01771"></a><span class="lineno"> 1771</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">m_RecurrentToCellWeights</a> = &recurrentToCellWeightsTensor;</div><div class="line"><a name="l01772"></a><span class="lineno"> 1772</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeightsTensor;</div><div class="line"><a name="l01773"></a><span class="lineno"> 1773</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">m_CellToForgetWeights</a> = &cellToForgetWeightsTensor;</div><div class="line"><a name="l01774"></a><span class="lineno"> 1774</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">m_CellToOutputWeights</a> = &cellToOutputWeightsTensor;</div><div class="line"><a name="l01775"></a><span class="lineno"> 1775</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">m_ForgetGateBias</a> = &forgetGateBiasTensor;</div><div class="line"><a name="l01776"></a><span class="lineno"> 1776</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">m_CellBias</a> = &cellBiasTensor;</div><div class="line"><a name="l01777"></a><span class="lineno"> 1777</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">m_OutputGateBias</a> = &outputGateBiasTensor;</div><div class="line"><a name="l01778"></a><span class="lineno"> 1778</span> </div><div class="line"><a name="l01779"></a><span class="lineno"> 1779</span>  <span class="comment">// Flags to set test configuration</span></div><div class="line"><a name="l01780"></a><span class="lineno"> 1780</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a> = 10;</div><div class="line"><a name="l01781"></a><span class="lineno"> 1781</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a86e88bef0df4df96df752b4b8955a3af">m_ClippingThresProj</a> = 0;</div><div class="line"><a name="l01782"></a><span class="lineno"> 1782</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = 4;</div><div class="line"><a name="l01783"></a><span class="lineno"> 1783</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l01784"></a><span class="lineno"> 1784</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l01785"></a><span class="lineno"> 1785</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01786"></a><span class="lineno"> 1786</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">m_TimeMajor</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01787"></a><span class="lineno"> 1787</span> </div><div class="line"><a name="l01788"></a><span class="lineno"> 1788</span>  std::unique_ptr<armnn::IWorkload> workload</div><div class="line"><a name="l01789"></a><span class="lineno"> 1789</span>  = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">CreateWorkload</a>(<a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a>, data, info);</div><div class="line"><a name="l01790"></a><span class="lineno"> 1790</span>  inputHandle->Allocate();</div><div class="line"><a name="l01791"></a><span class="lineno"> 1791</span>  outputStateInHandle->Allocate();</div><div class="line"><a name="l01792"></a><span class="lineno"> 1792</span>  cellStateInHandle->Allocate();</div><div class="line"><a name="l01793"></a><span class="lineno"> 1793</span> </div><div class="line"><a name="l01794"></a><span class="lineno"> 1794</span>  outputHandle->Allocate();</div><div class="line"><a name="l01795"></a><span class="lineno"> 1795</span> </div><div class="line"><a name="l01796"></a><span class="lineno"> 1796</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), inputVector.data());</div><div class="line"><a name="l01797"></a><span class="lineno"> 1797</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(outputStateInHandle.get(), outputStateInVector.data());</div><div class="line"><a name="l01798"></a><span class="lineno"> 1798</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(cellStateInHandle.get(), cellStateInVector.data());</div><div class="line"><a name="l01799"></a><span class="lineno"> 1799</span> </div><div class="line"><a name="l01800"></a><span class="lineno"> 1800</span>  workload->Execute();</div><div class="line"><a name="l01801"></a><span class="lineno"> 1801</span> </div><div class="line"><a name="l01802"></a><span class="lineno"> 1802</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a>(actualOutput.data(), outputHandle.get());</div><div class="line"><a name="l01803"></a><span class="lineno"> 1803</span> </div><div class="line"><a name="l01804"></a><span class="lineno"> 1804</span>  <span class="keywordflow">return</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 3></a>(actualOutput,</div><div class="line"><a name="l01805"></a><span class="lineno"> 1805</span>  outputVector,</div><div class="line"><a name="l01806"></a><span class="lineno"> 1806</span>  outputHandle->GetShape(),</div><div class="line"><a name="l01807"></a><span class="lineno"> 1807</span>  outputTensorInfo.GetShape());</div><div class="line"><a name="l01808"></a><span class="lineno"> 1808</span> }</div><div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::LstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01114">Descriptors.hpp:1114</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a86e88bef0df4df96df752b4b8955a3af"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a86e88bef0df4df96df752b4b8955a3af">armnn::LstmDescriptor::m_ClippingThresProj</a></div><div class="ttdeci">float m_ClippingThresProj</div><div class="ttdoc">Clipping threshold value for the projection. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01108">Descriptors.hpp:1108</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ac18c8b8b2039267d8282e91b4162d8aa"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">WorkloadData.hpp:747</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a3dcd10ca3ea2e132558b1e2814668c15"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">armnn::LstmDescriptor::m_TimeMajor</a></div><div class="ttdeci">bool m_TimeMajor</div><div class="ttdoc">Enable/disable time major. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01118">Descriptors.hpp:1118</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">WorkloadData.hpp:54</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_afaaca8c3f3a467d124bba44067d2afa8"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a></div><div class="ttdeci">void AllocateAndCopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00019">TensorCopyUtils.cpp:19</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a5ff4158b1b363b898d0da04c42d37ce0"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">WorkloadData.hpp:755</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a17ba1c8bcc71a55a95b2a3913f8cb203"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">WorkloadData.hpp:744</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a841439e3b8dc157a7368b19c9ecb7d03"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">WorkloadData.hpp:743</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aab77f54a037658ca9b2bf9cc8a1fadf1"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">WorkloadData.hpp:742</a></div></div> +<div class="ttc" id="classarmnn_1_1_scoped_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_tensor_handle_8hpp_source.xhtml#l00115">TensorHandle.hpp:115</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::LstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01112">Descriptors.hpp:1112</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ab5dfed8358e500ed523d78090ec78e88"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *mem, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ae1b07ed928036004bd257169e5aeeef4"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">armnn::LstmDescriptor::m_ActivationFunc</a></div><div class="ttdeci">uint32_t m_ActivationFunc</div><div class="ttdoc">The activation function to use. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01104">Descriptors.hpp:1104</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a531a3907ec13d3772370da88030191a5"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">armnn::LstmDescriptor::m_ClippingThresCell</a></div><div class="ttdeci">float m_ClippingThresCell</div><div class="ttdoc">Clipping threshold value for the cell state. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01106">Descriptors.hpp:1106</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::LstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable cifg (coupled input & forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01110">Descriptors.hpp:1110</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a29fa293fffbf9c6f00cd75db1dc0a52a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">WorkloadData.hpp:753</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a6e9593869b82984de198fed27f72cdcf"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a></div><div class="ttdeci">const ConstTensorHandle * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">WorkloadData.hpp:754</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00015">LayerTestResult.hpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a20c10fcb26657477377d07b7b1e13120"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00750">WorkloadData.hpp:750</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00714">WorkloadData.hpp:714</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a4c27716f61bb68e8ea0bd4e8389ba01a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">WorkloadData.hpp:748</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a13060ebb89d2c21a7a5d897e99cccf72"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">armnn::IWorkloadFactory::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01541">WorkloadFactory.cpp:1541</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_adf8571dd1867ee91082bd005f94f2610"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">WorkloadData.hpp:746</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aa09f7bdb9fd0d06b6386e412a4e72dd6"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00751">WorkloadData.hpp:751</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="ab5aedf0fbe3810773302b480ff1ef0fe"></a> +<h2 class="memtitle"><span class="permalink"><a href="#ab5aedf0fbe3810773302b480ff1ef0fe">◆ </a></span>UnidirectionalSequenceLstmLayerFloat32Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 3> UnidirectionalSequenceLstmLayerFloat32Test </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml#l00372">372</a> of file <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml">UnidirectionalSequenceLstmTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  {</div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo({3, 2, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  std::vector<float> input = { 1., 2., 3., 4., 5., 4.,</div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  3., 2., 1., 2., 3., 4.,</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  5., 4., 3., 2., 1., 2. };</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span> </div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({3, 2, 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  std::vector<float> expectedOutput = { -0.07149004f, -0.1621171f, -0.17516759f, -0.0232934225f,</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  -0.16810727f, -0.41412935f, -0.5498753f, -0.00803578f,</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  -0.06687349f, 0.204077631f, -0.4276504f, -0.03123213f,</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  -0.12000261f, -0.0941918f, -0.45639035f, -0.02870186f,</div><div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  -0.03429216f, 0.20824050f, -0.6569892f, -0.004152651f,</div><div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  -0.10493034f, 0.14210969f, -0.58347696f, -0.03297536f };</div><div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="keywordflow">return</span> UnidirectionalSequenceLstmLayerFloat32TestImpl<armnn::DataType::Float32>(</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  workloadFactory, memoryManager, tensorHandleFactory,</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  input, expectedOutput, inputInfo.GetShape(), outputInfo.GetShape());</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a3e62d48c04adef20dc1e813544e5792f"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a3e62d48c04adef20dc1e813544e5792f">◆ </a></span>UnidirectionalSequenceLstmLayerFloat32TimeMajorTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 3> UnidirectionalSequenceLstmLayerFloat32TimeMajorTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml#l00393">393</a> of file <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml">UnidirectionalSequenceLstmTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  {</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputInfo({2, 3, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  std::vector<float> input = { 1., 2., 3., 4., 5., 4.,</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  3., 2., 1., 2., 3., 4.,</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  5., 4., 3., 2., 1., 2. };</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span> </div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputInfo({2, 3, 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  std::vector<float> expectedOutput = { 0.135657698f, 0.124672532f, 0.0212090332f, -0.0530203655f,</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  0.106138252f, 0.0404792242f, 0.0151643595f, -0.00675163185f,</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  -0.0128514022f, 0.0644884035f, 0.0709072053f, -0.0454045124f,</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  0.16288602f, 0.16649379f, 0.02770456f, -0.03698075f,</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  0.11171641f, 0.043119f , 0.0762981f , -0.01228541f,</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  0.10439701f, 0.21439962f, 0.11919238f, -0.08390583f };</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  <span class="keywordflow">return</span> UnidirectionalSequenceLstmLayerFloat32TimeMajorTestImpl<armnn::DataType::Float32>(</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  workloadFactory, memoryManager, tensorHandleFactory,</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  input, expectedOutput, inputInfo.GetShape(), outputInfo.GetShape());</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span> }</div><div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a8a1a97bb52fc24a8d66e2c2dd98c6d9b"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a8a1a97bb52fc24a8d66e2c2dd98c6d9b">◆ </a></span>UnidirectionalSequenceLstmLayerInt8NoCifgWithPeepholeWithProjectionTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 3> UnidirectionalSequenceLstmLayerInt8NoCifgWithPeepholeWithProjectionTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml#l01317">1317</a> of file <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml">UnidirectionalSequenceLstmTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01541">IWorkloadFactory::CreateWorkload()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01104">LstmDescriptor::m_ActivationFunc</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00750">UnidirectionalSequenceLstmQueueDescriptor::m_CellToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00749">UnidirectionalSequenceLstmQueueDescriptor::m_CellToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00751">UnidirectionalSequenceLstmQueueDescriptor::m_CellToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01110">LstmDescriptor::m_CifgEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01106">LstmDescriptor::m_ClippingThresCell</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00752">UnidirectionalSequenceLstmQueueDescriptor::m_InputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00741">UnidirectionalSequenceLstmQueueDescriptor::m_InputToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01116">LstmDescriptor::m_LayerNormEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01112">LstmDescriptor::m_PeepholeEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00757">UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionBias</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01114">LstmDescriptor::m_ProjectionEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00756">UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00745">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01118">LstmDescriptor::m_TimeMajor</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::QAsymmS8</a>, and <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::UnidirectionalSequenceLstm</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l01321"></a><span class="lineno"> 1321</span> {</div><div class="line"><a name="l01322"></a><span class="lineno"> 1322</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l01323"></a><span class="lineno"> 1323</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 3;</div><div class="line"><a name="l01324"></a><span class="lineno"> 1324</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> timeSize = 2;</div><div class="line"><a name="l01325"></a><span class="lineno"> 1325</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = 4;</div><div class="line"><a name="l01326"></a><span class="lineno"> 1326</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputSize = 3;</div><div class="line"><a name="l01327"></a><span class="lineno"> 1327</span>  <span class="keywordtype">unsigned</span> numUnits = 4;</div><div class="line"><a name="l01328"></a><span class="lineno"> 1328</span> </div><div class="line"><a name="l01329"></a><span class="lineno"> 1329</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({batchSize, timeSize, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01330"></a><span class="lineno"> 1330</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> cellStateInTensorInfo({batchSize , numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01331"></a><span class="lineno"> 1331</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputStateInTensorInfo({batchSize , outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01332"></a><span class="lineno"> 1332</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({batchSize, timeSize, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01333"></a><span class="lineno"> 1333</span> </div><div class="line"><a name="l01334"></a><span class="lineno"> 1334</span>  <span class="keyword">const</span> std::vector<float> inputVector = { 0.1f, 0.2f, 0.3f, 0.4f, 0.5f, 0.4f,</div><div class="line"><a name="l01335"></a><span class="lineno"> 1335</span>  0.3f, 0.2f, 0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>  0.5f, 0.4f, 0.3f, 0.2f, 0.1f, 0.2f };</div><div class="line"><a name="l01337"></a><span class="lineno"> 1337</span> </div><div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>  std::vector<float> cellStateInVector(batchSize * numUnits, 0.f);</div><div class="line"><a name="l01339"></a><span class="lineno"> 1339</span>  std::vector<float> outputStateInVector(batchSize * outputSize, 0.f);</div><div class="line"><a name="l01340"></a><span class="lineno"> 1340</span> </div><div class="line"><a name="l01341"></a><span class="lineno"> 1341</span>  std::vector<float> actualOutput(outputTensorInfo.GetNumElements());</div><div class="line"><a name="l01342"></a><span class="lineno"> 1342</span> </div><div class="line"><a name="l01343"></a><span class="lineno"> 1343</span>  <span class="keyword">const</span> std::vector<float> expectedOutput = { 0.612103f, 1.56788f, 0.31966f, 1.42956f,</div><div class="line"><a name="l01344"></a><span class="lineno"> 1344</span>  0.909718f, 3.07916f, -0.560586f, 3.8907f,</div><div class="line"><a name="l01345"></a><span class="lineno"> 1345</span>  0.753671f, 1.77485f, 0.365122f, 1.60077f,</div><div class="line"><a name="l01346"></a><span class="lineno"> 1346</span>  0.812644f, 2.79092f, -0.605396f, 3.61742f,</div><div class="line"><a name="l01347"></a><span class="lineno"> 1347</span>  0.791857f, 1.64353f, 0.316588f, 1.55192f,</div><div class="line"><a name="l01348"></a><span class="lineno"> 1348</span>  0.807265f, 2.47012f, -0.539598f, 3.25654f };</div><div class="line"><a name="l01349"></a><span class="lineno"> 1349</span> </div><div class="line"><a name="l01350"></a><span class="lineno"> 1350</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>  std::unique_ptr<armnn::ITensorHandle> cellStateInHandle =</div><div class="line"><a name="l01352"></a><span class="lineno"> 1352</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(cellStateInTensorInfo);</div><div class="line"><a name="l01353"></a><span class="lineno"> 1353</span>  std::unique_ptr<armnn::ITensorHandle> outputStateInHandle =</div><div class="line"><a name="l01354"></a><span class="lineno"> 1354</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputStateInTensorInfo);</div><div class="line"><a name="l01355"></a><span class="lineno"> 1355</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l01356"></a><span class="lineno"> 1356</span> </div><div class="line"><a name="l01357"></a><span class="lineno"> 1357</span>  <a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a> data;</div><div class="line"><a name="l01358"></a><span class="lineno"> 1358</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l01359"></a><span class="lineno"> 1359</span> </div><div class="line"><a name="l01360"></a><span class="lineno"> 1360</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l01361"></a><span class="lineno"> 1361</span>  AddInputToWorkload(data, info, outputStateInTensorInfo, outputStateInHandle.get());</div><div class="line"><a name="l01362"></a><span class="lineno"> 1362</span>  AddInputToWorkload(data, info, cellStateInTensorInfo, cellStateInHandle.get());</div><div class="line"><a name="l01363"></a><span class="lineno"> 1363</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l01364"></a><span class="lineno"> 1364</span> </div><div class="line"><a name="l01365"></a><span class="lineno"> 1365</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoOut({outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01366"></a><span class="lineno"> 1366</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumFp({numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01367"></a><span class="lineno"> 1367</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNum({numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01368"></a><span class="lineno"> 1368</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumInput({numUnits, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01369"></a><span class="lineno"> 1369</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumOutput({numUnits, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01370"></a><span class="lineno"> 1370</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoOutNum({outputSize, numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01371"></a><span class="lineno"> 1371</span> </div><div class="line"><a name="l01372"></a><span class="lineno"> 1372</span>  std::vector<int8_t> inputToInputWeights = { -4, -1, -1, -2, 3, -2, 2, 4, 1, -4, -2, 3 };</div><div class="line"><a name="l01373"></a><span class="lineno"> 1373</span>  std::vector<int8_t> inputToForgetWeights = { 2, 1, 4, -4, 3, -1, -3, -2, -3, 1, -4, -1 };</div><div class="line"><a name="l01374"></a><span class="lineno"> 1374</span>  std::vector<int8_t> inputToCellWeights = { -2, 1, -2, 4, -3, -2, -4, 3, -2, -2, -6, 3 };</div><div class="line"><a name="l01375"></a><span class="lineno"> 1375</span>  std::vector<int8_t> inputToOutputWeights = { 2, 5, -4, 5, 2, -3, 5, 7, 3, -5, 1, -4 };</div><div class="line"><a name="l01376"></a><span class="lineno"> 1376</span> </div><div class="line"><a name="l01377"></a><span class="lineno"> 1377</span>  std::vector<int8_t> recurrentToInputWeights = { -1, 1, -1, 1, -3, -4, -1, 4, 2, 3, 5, -1, 1, 3, -1, -1 };</div><div class="line"><a name="l01378"></a><span class="lineno"> 1378</span>  std::vector<int8_t> recurrentToForgetWeights = { -1, 1, -1, 1, -3, -4, -1, 4, 2, 3, 5, -1, 1, 3, -2, -1 };</div><div class="line"><a name="l01379"></a><span class="lineno"> 1379</span>  std::vector<int8_t> recurrentToCellWeights = { -2, -3, -1, -3, -4, 2, 1, -1, 2, 2, 1, 2, 3, -2, 3, -3 };</div><div class="line"><a name="l01380"></a><span class="lineno"> 1380</span>  std::vector<int8_t> recurrentToOutputWeights = { -3, 3, -1, -2, -2, -2, -1, -5, 1, 3, -4, -1, -1, -1, 2, -1 };</div><div class="line"><a name="l01381"></a><span class="lineno"> 1381</span> </div><div class="line"><a name="l01382"></a><span class="lineno"> 1382</span>  std::vector<float> inputGateBias = { 0.02234832f, 0.14757581f, 0.18176508f, 0.10380666f};</div><div class="line"><a name="l01383"></a><span class="lineno"> 1383</span>  std::vector<float> forgetGateBias = { 0.035185695f, -0.042891346f, -0.3032477f, 0.23027696f};</div><div class="line"><a name="l01384"></a><span class="lineno"> 1384</span>  std::vector<float> cellBias = { -0.124379363f, 0.55531194f, 0.23377132f, 0.033463873f };</div><div class="line"><a name="l01385"></a><span class="lineno"> 1385</span>  std::vector<float> outputGateBias = { 0.046159424f, -0.12809046f, 0.03563469f, 0.12648113f };</div><div class="line"><a name="l01386"></a><span class="lineno"> 1386</span> </div><div class="line"><a name="l01387"></a><span class="lineno"> 1387</span>  std::vector<int8_t> cellToInputWeights = { 5, 10, 25, 15 };</div><div class="line"><a name="l01388"></a><span class="lineno"> 1388</span>  std::vector<int8_t> cellToForgetWeights = { -5, 15, 25, 3 };</div><div class="line"><a name="l01389"></a><span class="lineno"> 1389</span>  std::vector<int8_t> cellToOutputWeights = { 10, -10, -5, 50 };</div><div class="line"><a name="l01390"></a><span class="lineno"> 1390</span> </div><div class="line"><a name="l01391"></a><span class="lineno"> 1391</span>  std::vector<int8_t> projectionWeights = { -25, 51, 3, -5, 25, 127, 77, 20, 18, 51, -10, 51, -25, 88, 77, -13 };</div><div class="line"><a name="l01392"></a><span class="lineno"> 1392</span> </div><div class="line"><a name="l01393"></a><span class="lineno"> 1393</span>  std::vector<float> projectionBiasVector(outputSize, 0.f); <span class="comment">//{outputSize}</span></div><div class="line"><a name="l01394"></a><span class="lineno"> 1394</span> </div><div class="line"><a name="l01395"></a><span class="lineno"> 1395</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToInputWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01396"></a><span class="lineno"> 1396</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToForgetWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01397"></a><span class="lineno"> 1397</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToCellWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01398"></a><span class="lineno"> 1398</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToOutputWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01399"></a><span class="lineno"> 1399</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToForgetWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01400"></a><span class="lineno"> 1400</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToInputWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01401"></a><span class="lineno"> 1401</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToCellWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01402"></a><span class="lineno"> 1402</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToOutputWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01403"></a><span class="lineno"> 1403</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToInputWeightsTensor(tensorInfoNum);</div><div class="line"><a name="l01404"></a><span class="lineno"> 1404</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01405"></a><span class="lineno"> 1405</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> forgetGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01406"></a><span class="lineno"> 1406</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01407"></a><span class="lineno"> 1407</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> outputGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01408"></a><span class="lineno"> 1408</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToForgetWeightsTensor(tensorInfoNum);</div><div class="line"><a name="l01409"></a><span class="lineno"> 1409</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToOutputWeightsTensor(tensorInfoNum);</div><div class="line"><a name="l01410"></a><span class="lineno"> 1410</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> projectionWeightsTensor(tensorInfoOutNum);</div><div class="line"><a name="l01411"></a><span class="lineno"> 1411</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> projectionBiasTensor(tensorInfoOut);</div><div class="line"><a name="l01412"></a><span class="lineno"> 1412</span> </div><div class="line"><a name="l01413"></a><span class="lineno"> 1413</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToInputWeightsTensor, inputToInputWeights.data());</div><div class="line"><a name="l01414"></a><span class="lineno"> 1414</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToForgetWeightsTensor, inputToForgetWeights.data());</div><div class="line"><a name="l01415"></a><span class="lineno"> 1415</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToCellWeightsTensor, inputToCellWeights.data());</div><div class="line"><a name="l01416"></a><span class="lineno"> 1416</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToOutputWeightsTensor, inputToOutputWeights.data());</div><div class="line"><a name="l01417"></a><span class="lineno"> 1417</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToInputWeightsTensor, recurrentToInputWeights.data());</div><div class="line"><a name="l01418"></a><span class="lineno"> 1418</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToForgetWeightsTensor, recurrentToForgetWeights.data());</div><div class="line"><a name="l01419"></a><span class="lineno"> 1419</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToCellWeightsTensor, recurrentToCellWeights.data());</div><div class="line"><a name="l01420"></a><span class="lineno"> 1420</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToOutputWeightsTensor, recurrentToOutputWeights.data());</div><div class="line"><a name="l01421"></a><span class="lineno"> 1421</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToInputWeightsTensor, cellToInputWeights.data());</div><div class="line"><a name="l01422"></a><span class="lineno"> 1422</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputGateBiasTensor, inputGateBias.data());</div><div class="line"><a name="l01423"></a><span class="lineno"> 1423</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&forgetGateBiasTensor, forgetGateBias.data());</div><div class="line"><a name="l01424"></a><span class="lineno"> 1424</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellBiasTensor, cellBias.data());</div><div class="line"><a name="l01425"></a><span class="lineno"> 1425</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&outputGateBiasTensor, outputGateBias.data());</div><div class="line"><a name="l01426"></a><span class="lineno"> 1426</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToForgetWeightsTensor, cellToForgetWeights.data());</div><div class="line"><a name="l01427"></a><span class="lineno"> 1427</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToOutputWeightsTensor, cellToOutputWeights.data());</div><div class="line"><a name="l01428"></a><span class="lineno"> 1428</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&projectionWeightsTensor, projectionWeights.data());</div><div class="line"><a name="l01429"></a><span class="lineno"> 1429</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&projectionBiasTensor, projectionBiasVector.data());</div><div class="line"><a name="l01430"></a><span class="lineno"> 1430</span> </div><div class="line"><a name="l01431"></a><span class="lineno"> 1431</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">m_InputToInputWeights</a> = &inputToInputWeightsTensor;</div><div class="line"><a name="l01432"></a><span class="lineno"> 1432</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">m_InputToForgetWeights</a> = &inputToForgetWeightsTensor;</div><div class="line"><a name="l01433"></a><span class="lineno"> 1433</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">m_InputToCellWeights</a> = &inputToCellWeightsTensor;</div><div class="line"><a name="l01434"></a><span class="lineno"> 1434</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">m_InputToOutputWeights</a> = &inputToOutputWeightsTensor;</div><div class="line"><a name="l01435"></a><span class="lineno"> 1435</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">m_RecurrentToInputWeights</a> = &recurrentToInputWeightsTensor;</div><div class="line"><a name="l01436"></a><span class="lineno"> 1436</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeightsTensor;</div><div class="line"><a name="l01437"></a><span class="lineno"> 1437</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">m_RecurrentToCellWeights</a> = &recurrentToCellWeightsTensor;</div><div class="line"><a name="l01438"></a><span class="lineno"> 1438</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeightsTensor;</div><div class="line"><a name="l01439"></a><span class="lineno"> 1439</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">m_CellToInputWeights</a> = &cellToInputWeightsTensor;</div><div class="line"><a name="l01440"></a><span class="lineno"> 1440</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">m_InputGateBias</a> = &inputGateBiasTensor;</div><div class="line"><a name="l01441"></a><span class="lineno"> 1441</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">m_ForgetGateBias</a> = &forgetGateBiasTensor;</div><div class="line"><a name="l01442"></a><span class="lineno"> 1442</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">m_CellBias</a> = &cellBiasTensor;</div><div class="line"><a name="l01443"></a><span class="lineno"> 1443</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">m_OutputGateBias</a> = &outputGateBiasTensor;</div><div class="line"><a name="l01444"></a><span class="lineno"> 1444</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">m_CellToForgetWeights</a> = &cellToForgetWeightsTensor;</div><div class="line"><a name="l01445"></a><span class="lineno"> 1445</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">m_CellToOutputWeights</a> = &cellToOutputWeightsTensor;</div><div class="line"><a name="l01446"></a><span class="lineno"> 1446</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">m_ProjectionWeights</a> = &projectionWeightsTensor;</div><div class="line"><a name="l01447"></a><span class="lineno"> 1447</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a> = &projectionBiasTensor;</div><div class="line"><a name="l01448"></a><span class="lineno"> 1448</span> </div><div class="line"><a name="l01449"></a><span class="lineno"> 1449</span>  <span class="comment">// Flags to set test configuration</span></div><div class="line"><a name="l01450"></a><span class="lineno"> 1450</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = 4;</div><div class="line"><a name="l01451"></a><span class="lineno"> 1451</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01452"></a><span class="lineno"> 1452</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l01453"></a><span class="lineno"> 1453</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l01454"></a><span class="lineno"> 1454</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01455"></a><span class="lineno"> 1455</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">m_TimeMajor</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01456"></a><span class="lineno"> 1456</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a> = 10.0f;</div><div class="line"><a name="l01457"></a><span class="lineno"> 1457</span> </div><div class="line"><a name="l01458"></a><span class="lineno"> 1458</span> </div><div class="line"><a name="l01459"></a><span class="lineno"> 1459</span>  std::unique_ptr<armnn::IWorkload> workload</div><div class="line"><a name="l01460"></a><span class="lineno"> 1460</span>  = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">CreateWorkload</a>(<a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a>, data, info);</div><div class="line"><a name="l01461"></a><span class="lineno"> 1461</span>  inputHandle->Allocate();</div><div class="line"><a name="l01462"></a><span class="lineno"> 1462</span>  outputStateInHandle->Allocate();</div><div class="line"><a name="l01463"></a><span class="lineno"> 1463</span>  cellStateInHandle->Allocate();</div><div class="line"><a name="l01464"></a><span class="lineno"> 1464</span>  outputHandle->Allocate();</div><div class="line"><a name="l01465"></a><span class="lineno"> 1465</span> </div><div class="line"><a name="l01466"></a><span class="lineno"> 1466</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), inputVector.data());</div><div class="line"><a name="l01467"></a><span class="lineno"> 1467</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(outputStateInHandle.get(), outputStateInVector.data());</div><div class="line"><a name="l01468"></a><span class="lineno"> 1468</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(cellStateInHandle.get(), cellStateInVector.data());</div><div class="line"><a name="l01469"></a><span class="lineno"> 1469</span> </div><div class="line"><a name="l01470"></a><span class="lineno"> 1470</span>  workload->Execute();</div><div class="line"><a name="l01471"></a><span class="lineno"> 1471</span> </div><div class="line"><a name="l01472"></a><span class="lineno"> 1472</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a>(actualOutput.data(), outputHandle.get());</div><div class="line"><a name="l01473"></a><span class="lineno"> 1473</span> </div><div class="line"><a name="l01474"></a><span class="lineno"> 1474</span>  <span class="keywordflow">return</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 3></a>(actualOutput,</div><div class="line"><a name="l01475"></a><span class="lineno"> 1475</span>  expectedOutput,</div><div class="line"><a name="l01476"></a><span class="lineno"> 1476</span>  outputHandle->GetShape(),</div><div class="line"><a name="l01477"></a><span class="lineno"> 1477</span>  outputTensorInfo.GetShape());</div><div class="line"><a name="l01478"></a><span class="lineno"> 1478</span> }</div><div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::LstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01114">Descriptors.hpp:1114</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a44eb7524badcca9b2073359e3814c98b"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00752">WorkloadData.hpp:752</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ac18c8b8b2039267d8282e91b4162d8aa"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">WorkloadData.hpp:747</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ab160eba2493d5fe52185c0986dcb190c"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00741">WorkloadData.hpp:741</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a3dcd10ca3ea2e132558b1e2814668c15"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">armnn::LstmDescriptor::m_TimeMajor</a></div><div class="ttdeci">bool m_TimeMajor</div><div class="ttdoc">Enable/disable time major. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01118">Descriptors.hpp:1118</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">WorkloadData.hpp:54</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_afaaca8c3f3a467d124bba44067d2afa8"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a></div><div class="ttdeci">void AllocateAndCopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00019">TensorCopyUtils.cpp:19</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a5ff4158b1b363b898d0da04c42d37ce0"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">WorkloadData.hpp:755</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ac668b31de6fb0f19d4c793d5ed3c3316"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ProjectionBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00757">WorkloadData.hpp:757</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a17ba1c8bcc71a55a95b2a3913f8cb203"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">WorkloadData.hpp:744</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a841439e3b8dc157a7368b19c9ecb7d03"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">WorkloadData.hpp:743</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aab77f54a037658ca9b2bf9cc8a1fadf1"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">WorkloadData.hpp:742</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a951b7c90b862138071a298065f16be61"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00749">WorkloadData.hpp:749</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a3ead2ef8da00b2709d561d85996fc513"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_ProjectionWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00756">WorkloadData.hpp:756</a></div></div> +<div class="ttc" id="classarmnn_1_1_scoped_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_tensor_handle_8hpp_source.xhtml#l00115">TensorHandle.hpp:115</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::LstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01112">Descriptors.hpp:1112</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ab5dfed8358e500ed523d78090ec78e88"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *mem, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ae1b07ed928036004bd257169e5aeeef4"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">armnn::LstmDescriptor::m_ActivationFunc</a></div><div class="ttdeci">uint32_t m_ActivationFunc</div><div class="ttdoc">The activation function to use. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01104">Descriptors.hpp:1104</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a531a3907ec13d3772370da88030191a5"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">armnn::LstmDescriptor::m_ClippingThresCell</a></div><div class="ttdeci">float m_ClippingThresCell</div><div class="ttdoc">Clipping threshold value for the cell state. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01106">Descriptors.hpp:1106</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::LstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable cifg (coupled input & forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01110">Descriptors.hpp:1110</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a29fa293fffbf9c6f00cd75db1dc0a52a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">WorkloadData.hpp:753</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a6e9593869b82984de198fed27f72cdcf"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a></div><div class="ttdeci">const ConstTensorHandle * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">WorkloadData.hpp:754</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a4a8ec49f130084445d44297549254780"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">armnn::LstmDescriptor::m_LayerNormEnabled</a></div><div class="ttdeci">bool m_LayerNormEnabled</div><div class="ttdoc">Enable/disable layer normalization. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01116">Descriptors.hpp:1116</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a299587d4f3fca029492700f3e2585bd8"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00745">WorkloadData.hpp:745</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00015">LayerTestResult.hpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a20c10fcb26657477377d07b7b1e13120"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00750">WorkloadData.hpp:750</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00714">WorkloadData.hpp:714</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a4c27716f61bb68e8ea0bd4e8389ba01a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">WorkloadData.hpp:748</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a13060ebb89d2c21a7a5d897e99cccf72"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">armnn::IWorkloadFactory::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01541">WorkloadFactory.cpp:1541</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_adf8571dd1867ee91082bd005f94f2610"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">WorkloadData.hpp:746</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aa09f7bdb9fd0d06b6386e412a4e72dd6"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00751">WorkloadData.hpp:751</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="af7d1e03806f56e8e8e1444f16d735af5"></a> +<h2 class="memtitle"><span class="permalink"><a href="#af7d1e03806f56e8e8e1444f16d735af5">◆ </a></span>UnidirectionalSequenceLstmLayerInt8NoCifgWithPeepholeWithProjectionWithLayerNormTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 3> UnidirectionalSequenceLstmLayerInt8NoCifgWithPeepholeWithProjectionWithLayerNormTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml#l01480">1480</a> of file <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml">UnidirectionalSequenceLstmTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01541">IWorkloadFactory::CreateWorkload()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01104">LstmDescriptor::m_ActivationFunc</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00760">UnidirectionalSequenceLstmQueueDescriptor::m_CellLayerNormWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00750">UnidirectionalSequenceLstmQueueDescriptor::m_CellToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00749">UnidirectionalSequenceLstmQueueDescriptor::m_CellToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00751">UnidirectionalSequenceLstmQueueDescriptor::m_CellToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01110">LstmDescriptor::m_CifgEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01106">LstmDescriptor::m_ClippingThresCell</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00759">UnidirectionalSequenceLstmQueueDescriptor::m_ForgetLayerNormWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00752">UnidirectionalSequenceLstmQueueDescriptor::m_InputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00758">UnidirectionalSequenceLstmQueueDescriptor::m_InputLayerNormWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00741">UnidirectionalSequenceLstmQueueDescriptor::m_InputToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01116">LstmDescriptor::m_LayerNormEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00761">UnidirectionalSequenceLstmQueueDescriptor::m_OutputLayerNormWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01112">LstmDescriptor::m_PeepholeEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00757">UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionBias</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01114">LstmDescriptor::m_ProjectionEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00756">UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00745">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01118">LstmDescriptor::m_TimeMajor</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::QAsymmS8</a>, and <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::UnidirectionalSequenceLstm</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l01484"></a><span class="lineno"> 1484</span> {</div><div class="line"><a name="l01485"></a><span class="lineno"> 1485</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l01486"></a><span class="lineno"> 1486</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 3;</div><div class="line"><a name="l01487"></a><span class="lineno"> 1487</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> timeSize = 2;</div><div class="line"><a name="l01488"></a><span class="lineno"> 1488</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = 4;</div><div class="line"><a name="l01489"></a><span class="lineno"> 1489</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputSize = 3;</div><div class="line"><a name="l01490"></a><span class="lineno"> 1490</span>  <span class="keywordtype">unsigned</span> numUnits = 5;</div><div class="line"><a name="l01491"></a><span class="lineno"> 1491</span> </div><div class="line"><a name="l01492"></a><span class="lineno"> 1492</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({batchSize, timeSize, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01493"></a><span class="lineno"> 1493</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> cellStateInTensorInfo({batchSize , numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01494"></a><span class="lineno"> 1494</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputStateInTensorInfo({batchSize , outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01495"></a><span class="lineno"> 1495</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({batchSize, timeSize, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01496"></a><span class="lineno"> 1496</span> </div><div class="line"><a name="l01497"></a><span class="lineno"> 1497</span>  <span class="keyword">const</span> std::vector<float> inputVector = { 1., 8., 3., 4., 5., 4.,</div><div class="line"><a name="l01498"></a><span class="lineno"> 1498</span>  3., 2., 1., 2., 3., 4.,</div><div class="line"><a name="l01499"></a><span class="lineno"> 1499</span>  5., 4., 3., 2., 1., 2. };</div><div class="line"><a name="l01500"></a><span class="lineno"> 1500</span> </div><div class="line"><a name="l01501"></a><span class="lineno"> 1501</span>  std::vector<float> cellStateInVector(batchSize * numUnits, 0.f);</div><div class="line"><a name="l01502"></a><span class="lineno"> 1502</span>  std::vector<float> outputStateInVector(batchSize * outputSize, 0.f);</div><div class="line"><a name="l01503"></a><span class="lineno"> 1503</span> </div><div class="line"><a name="l01504"></a><span class="lineno"> 1504</span>  std::vector<float> actualOutput(outputTensorInfo.GetNumElements());</div><div class="line"><a name="l01505"></a><span class="lineno"> 1505</span> </div><div class="line"><a name="l01506"></a><span class="lineno"> 1506</span>  <span class="keyword">const</span> std::vector<float> expectedOutput = { 0.0471276f, 0.0168155f, 0.0789885f, 0.16550f,</div><div class="line"><a name="l01507"></a><span class="lineno"> 1507</span>  0.0643133f, -0.0400722f, 0.100593f, 0.197722f,</div><div class="line"><a name="l01508"></a><span class="lineno"> 1508</span>  0.0465562f, -0.0600682f, 0.0622087f, 0.115053f,</div><div class="line"><a name="l01509"></a><span class="lineno"> 1509</span>  0.056287f, -0.0566218f, 0.0856832f, 0.148484f,</div><div class="line"><a name="l01510"></a><span class="lineno"> 1510</span>  0.0457859f, -0.0588112f, 0.0623636f, 0.114333f,</div><div class="line"><a name="l01511"></a><span class="lineno"> 1511</span>  0.0509271f, -0.0754262f, 0.058600f, 0.0801288f };</div><div class="line"><a name="l01512"></a><span class="lineno"> 1512</span> </div><div class="line"><a name="l01513"></a><span class="lineno"> 1513</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l01514"></a><span class="lineno"> 1514</span>  std::unique_ptr<armnn::ITensorHandle> cellStateInHandle =</div><div class="line"><a name="l01515"></a><span class="lineno"> 1515</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(cellStateInTensorInfo);</div><div class="line"><a name="l01516"></a><span class="lineno"> 1516</span>  std::unique_ptr<armnn::ITensorHandle> outputStateInHandle =</div><div class="line"><a name="l01517"></a><span class="lineno"> 1517</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputStateInTensorInfo);</div><div class="line"><a name="l01518"></a><span class="lineno"> 1518</span> </div><div class="line"><a name="l01519"></a><span class="lineno"> 1519</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l01520"></a><span class="lineno"> 1520</span> </div><div class="line"><a name="l01521"></a><span class="lineno"> 1521</span>  <a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a> data;</div><div class="line"><a name="l01522"></a><span class="lineno"> 1522</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l01523"></a><span class="lineno"> 1523</span> </div><div class="line"><a name="l01524"></a><span class="lineno"> 1524</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l01525"></a><span class="lineno"> 1525</span>  AddInputToWorkload(data, info, outputStateInTensorInfo, outputStateInHandle.get());</div><div class="line"><a name="l01526"></a><span class="lineno"> 1526</span>  AddInputToWorkload(data, info, cellStateInTensorInfo, cellStateInHandle.get());</div><div class="line"><a name="l01527"></a><span class="lineno"> 1527</span> </div><div class="line"><a name="l01528"></a><span class="lineno"> 1528</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l01529"></a><span class="lineno"> 1529</span> </div><div class="line"><a name="l01530"></a><span class="lineno"> 1530</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoOut({outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01531"></a><span class="lineno"> 1531</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumFp({numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01532"></a><span class="lineno"> 1532</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNum({numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01533"></a><span class="lineno"> 1533</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumInput({numUnits, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01534"></a><span class="lineno"> 1534</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumOutput({numUnits, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01535"></a><span class="lineno"> 1535</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoOutNum({outputSize, numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01536"></a><span class="lineno"> 1536</span> </div><div class="line"><a name="l01537"></a><span class="lineno"> 1537</span>  std::vector<int8_t> inputToInputWeights = { -4, -1, -1, -2, 3, -2, 2, 4, 1, -4, -2, 3, 2, 2, -4 };</div><div class="line"><a name="l01538"></a><span class="lineno"> 1538</span>  std::vector<int8_t> inputToForgetWeights = { 2, 1, 4, -4, 3, -1, -3, -2, -3, 1, -4, -1, -3, -2, -4 };</div><div class="line"><a name="l01539"></a><span class="lineno"> 1539</span>  std::vector<int8_t> inputToCellWeights = { -2, 1, -2, 4, -3, -2, -4, 3, -2, -2, -6, 3, 2, 5, -4 };</div><div class="line"><a name="l01540"></a><span class="lineno"> 1540</span>  std::vector<int8_t> inputToOutputWeights = { 2, 5, -4, 5, 2, -3, 5, 7, 3, -5, 1, -4, -4, -1, -1 };</div><div class="line"><a name="l01541"></a><span class="lineno"> 1541</span> </div><div class="line"><a name="l01542"></a><span class="lineno"> 1542</span>  std::vector<float> inputGateBias = { 0.03f, 0.15f, 0.22f, 0.38f, 0.05f };</div><div class="line"><a name="l01543"></a><span class="lineno"> 1543</span>  std::vector<float> forgetGateBias = { 0.1f, -0.3f, -0.2f, 0.1f, 0.4f };</div><div class="line"><a name="l01544"></a><span class="lineno"> 1544</span>  std::vector<float> cellBias = { -0.05f, 0.72f, 0.25f, 0.08f, 0.1f };</div><div class="line"><a name="l01545"></a><span class="lineno"> 1545</span>  std::vector<float> outputGateBias = { 0.05f, -0.01f, 0.2f, 0.1f, -0.2f };</div><div class="line"><a name="l01546"></a><span class="lineno"> 1546</span> </div><div class="line"><a name="l01547"></a><span class="lineno"> 1547</span>  std::vector<int8_t> recurrentToInputWeights = { -1, 1, -1, 1, -3, -4, -1, 4, 2, 3,</div><div class="line"><a name="l01548"></a><span class="lineno"> 1548</span>  5, -1, 1, 3, -1, -1, -1, 4, 2, 3 };</div><div class="line"><a name="l01549"></a><span class="lineno"> 1549</span> </div><div class="line"><a name="l01550"></a><span class="lineno"> 1550</span>  std::vector<int8_t> recurrentToForgetWeights = { -1, 1, -1, 1, -3, -4, -1, 4, 2, 3,</div><div class="line"><a name="l01551"></a><span class="lineno"> 1551</span>  5, -1, 1, 3, -2, -1, -1, 2, 2, 1 };</div><div class="line"><a name="l01552"></a><span class="lineno"> 1552</span> </div><div class="line"><a name="l01553"></a><span class="lineno"> 1553</span>  std::vector<int8_t> recurrentToCellWeights = { -2, -3, -1, -3, -4, 2, 1, -1, 2, 2,</div><div class="line"><a name="l01554"></a><span class="lineno"> 1554</span>  1, 2, 3, -2, 3, -3, -1, -5, 1, 3 };</div><div class="line"><a name="l01555"></a><span class="lineno"> 1555</span> </div><div class="line"><a name="l01556"></a><span class="lineno"> 1556</span>  std::vector<int8_t> recurrentToOutputWeights = { -3, 3, -1, -2, -2, -2, -1, -5, 1, 3,</div><div class="line"><a name="l01557"></a><span class="lineno"> 1557</span>  -4, -1, -1, -1, 2, -1, 5, 1, -3, -4 };</div><div class="line"><a name="l01558"></a><span class="lineno"> 1558</span> </div><div class="line"><a name="l01559"></a><span class="lineno"> 1559</span>  std::vector<int8_t> cellToInputWeights = { 5, 3, 8, -5, 2 };</div><div class="line"><a name="l01560"></a><span class="lineno"> 1560</span>  std::vector<int8_t> cellToForgetWeights = { -2, -7, 5, -3, 4 };</div><div class="line"><a name="l01561"></a><span class="lineno"> 1561</span>  std::vector<int8_t> cellToOutputWeights = { 9, -10 , -5, 5, 1 };</div><div class="line"><a name="l01562"></a><span class="lineno"> 1562</span> </div><div class="line"><a name="l01563"></a><span class="lineno"> 1563</span>  std::vector<int8_t> projectionWeights = { -1, 2, 1, -2, 1, 5, 3, 8, 7, 2,</div><div class="line"><a name="l01564"></a><span class="lineno"> 1564</span>  -4, 2, 5, -4, 3, -2, 3, 8, -7, 2 };</div><div class="line"><a name="l01565"></a><span class="lineno"> 1565</span> </div><div class="line"><a name="l01566"></a><span class="lineno"> 1566</span>  std::vector<float> projectionBiasVector(outputSize, 0.f); <span class="comment">//{outputSize}</span></div><div class="line"><a name="l01567"></a><span class="lineno"> 1567</span> </div><div class="line"><a name="l01568"></a><span class="lineno"> 1568</span>  std::vector<float> inputLayerNormWeights = { 0.1f, 0.2f, -0.3f, -0.1f, 0.5f };</div><div class="line"><a name="l01569"></a><span class="lineno"> 1569</span>  std::vector<float> forgetLayerNormWeights = { -0.1f, 0.2f, 0.3f, 0.5f, 0.2f };</div><div class="line"><a name="l01570"></a><span class="lineno"> 1570</span>  std::vector<float> cellLayerNormWeights = { 0.5f, 0.2f, 0.3f, 0.4f, -0.5f };</div><div class="line"><a name="l01571"></a><span class="lineno"> 1571</span>  std::vector<float> outputLayerNormWeights = { 0.6f, -0.2f, -0.2f, 0.5f, 0.1f };</div><div class="line"><a name="l01572"></a><span class="lineno"> 1572</span> </div><div class="line"><a name="l01573"></a><span class="lineno"> 1573</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToInputWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01574"></a><span class="lineno"> 1574</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToForgetWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01575"></a><span class="lineno"> 1575</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToCellWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01576"></a><span class="lineno"> 1576</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToOutputWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01577"></a><span class="lineno"> 1577</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToForgetWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01578"></a><span class="lineno"> 1578</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToInputWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01579"></a><span class="lineno"> 1579</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToCellWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01580"></a><span class="lineno"> 1580</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToOutputWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01581"></a><span class="lineno"> 1581</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToInputWeightsTensor(tensorInfoNum);</div><div class="line"><a name="l01582"></a><span class="lineno"> 1582</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01583"></a><span class="lineno"> 1583</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> forgetGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01584"></a><span class="lineno"> 1584</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01585"></a><span class="lineno"> 1585</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> outputGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01586"></a><span class="lineno"> 1586</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToForgetWeightsTensor(tensorInfoNum);</div><div class="line"><a name="l01587"></a><span class="lineno"> 1587</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToOutputWeightsTensor(tensorInfoNum);</div><div class="line"><a name="l01588"></a><span class="lineno"> 1588</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> projectionWeightsTensor(tensorInfoOutNum);</div><div class="line"><a name="l01589"></a><span class="lineno"> 1589</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> projectionBiasTensor(tensorInfoOut);</div><div class="line"><a name="l01590"></a><span class="lineno"> 1590</span> </div><div class="line"><a name="l01591"></a><span class="lineno"> 1591</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputLayerNormWeightsTensor(tensorInfoNumFp);</div><div class="line"><a name="l01592"></a><span class="lineno"> 1592</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> forgetLayerNormWeightsTensor(tensorInfoNumFp);</div><div class="line"><a name="l01593"></a><span class="lineno"> 1593</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellLayerNormWeightsTensor(tensorInfoNumFp);</div><div class="line"><a name="l01594"></a><span class="lineno"> 1594</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> outputLayerNormWeightsTensor(tensorInfoNumFp);</div><div class="line"><a name="l01595"></a><span class="lineno"> 1595</span> </div><div class="line"><a name="l01596"></a><span class="lineno"> 1596</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToInputWeightsTensor, inputToInputWeights.data());</div><div class="line"><a name="l01597"></a><span class="lineno"> 1597</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToForgetWeightsTensor, inputToForgetWeights.data());</div><div class="line"><a name="l01598"></a><span class="lineno"> 1598</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToCellWeightsTensor, inputToCellWeights.data());</div><div class="line"><a name="l01599"></a><span class="lineno"> 1599</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToOutputWeightsTensor, inputToOutputWeights.data());</div><div class="line"><a name="l01600"></a><span class="lineno"> 1600</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToInputWeightsTensor, recurrentToInputWeights.data());</div><div class="line"><a name="l01601"></a><span class="lineno"> 1601</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToForgetWeightsTensor, recurrentToForgetWeights.data());</div><div class="line"><a name="l01602"></a><span class="lineno"> 1602</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToCellWeightsTensor, recurrentToCellWeights.data());</div><div class="line"><a name="l01603"></a><span class="lineno"> 1603</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToOutputWeightsTensor, recurrentToOutputWeights.data());</div><div class="line"><a name="l01604"></a><span class="lineno"> 1604</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToInputWeightsTensor, cellToInputWeights.data());</div><div class="line"><a name="l01605"></a><span class="lineno"> 1605</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputGateBiasTensor, inputGateBias.data());</div><div class="line"><a name="l01606"></a><span class="lineno"> 1606</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&forgetGateBiasTensor, forgetGateBias.data());</div><div class="line"><a name="l01607"></a><span class="lineno"> 1607</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellBiasTensor, cellBias.data());</div><div class="line"><a name="l01608"></a><span class="lineno"> 1608</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&outputGateBiasTensor, outputGateBias.data());</div><div class="line"><a name="l01609"></a><span class="lineno"> 1609</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToForgetWeightsTensor, cellToForgetWeights.data());</div><div class="line"><a name="l01610"></a><span class="lineno"> 1610</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToOutputWeightsTensor, cellToOutputWeights.data());</div><div class="line"><a name="l01611"></a><span class="lineno"> 1611</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&projectionWeightsTensor, projectionWeights.data());</div><div class="line"><a name="l01612"></a><span class="lineno"> 1612</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&projectionBiasTensor, projectionBiasVector.data());</div><div class="line"><a name="l01613"></a><span class="lineno"> 1613</span> </div><div class="line"><a name="l01614"></a><span class="lineno"> 1614</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputLayerNormWeightsTensor, inputLayerNormWeights.data());</div><div class="line"><a name="l01615"></a><span class="lineno"> 1615</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&forgetLayerNormWeightsTensor, forgetLayerNormWeights.data());</div><div class="line"><a name="l01616"></a><span class="lineno"> 1616</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellLayerNormWeightsTensor, cellLayerNormWeights.data());</div><div class="line"><a name="l01617"></a><span class="lineno"> 1617</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&outputLayerNormWeightsTensor, outputLayerNormWeights.data());</div><div class="line"><a name="l01618"></a><span class="lineno"> 1618</span> </div><div class="line"><a name="l01619"></a><span class="lineno"> 1619</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">m_InputToInputWeights</a> = &inputToInputWeightsTensor;</div><div class="line"><a name="l01620"></a><span class="lineno"> 1620</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">m_InputToForgetWeights</a> = &inputToForgetWeightsTensor;</div><div class="line"><a name="l01621"></a><span class="lineno"> 1621</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">m_InputToCellWeights</a> = &inputToCellWeightsTensor;</div><div class="line"><a name="l01622"></a><span class="lineno"> 1622</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">m_InputToOutputWeights</a> = &inputToOutputWeightsTensor;</div><div class="line"><a name="l01623"></a><span class="lineno"> 1623</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">m_RecurrentToInputWeights</a> = &recurrentToInputWeightsTensor;</div><div class="line"><a name="l01624"></a><span class="lineno"> 1624</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeightsTensor;</div><div class="line"><a name="l01625"></a><span class="lineno"> 1625</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">m_RecurrentToCellWeights</a> = &recurrentToCellWeightsTensor;</div><div class="line"><a name="l01626"></a><span class="lineno"> 1626</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeightsTensor;</div><div class="line"><a name="l01627"></a><span class="lineno"> 1627</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">m_CellToInputWeights</a> = &cellToInputWeightsTensor;</div><div class="line"><a name="l01628"></a><span class="lineno"> 1628</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">m_InputGateBias</a> = &inputGateBiasTensor;</div><div class="line"><a name="l01629"></a><span class="lineno"> 1629</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">m_ForgetGateBias</a> = &forgetGateBiasTensor;</div><div class="line"><a name="l01630"></a><span class="lineno"> 1630</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">m_CellBias</a> = &cellBiasTensor;</div><div class="line"><a name="l01631"></a><span class="lineno"> 1631</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">m_OutputGateBias</a> = &outputGateBiasTensor;</div><div class="line"><a name="l01632"></a><span class="lineno"> 1632</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">m_CellToForgetWeights</a> = &cellToForgetWeightsTensor;</div><div class="line"><a name="l01633"></a><span class="lineno"> 1633</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">m_CellToOutputWeights</a> = &cellToOutputWeightsTensor;</div><div class="line"><a name="l01634"></a><span class="lineno"> 1634</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">m_ProjectionWeights</a> = &projectionWeightsTensor;</div><div class="line"><a name="l01635"></a><span class="lineno"> 1635</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a> = &projectionBiasTensor;</div><div class="line"><a name="l01636"></a><span class="lineno"> 1636</span> </div><div class="line"><a name="l01637"></a><span class="lineno"> 1637</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a1dbad32cad5c0437e1272f59fedf52ea">m_InputLayerNormWeights</a> = &inputLayerNormWeightsTensor;</div><div class="line"><a name="l01638"></a><span class="lineno"> 1638</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ad9442e26aa79f896da5f404ab825a9c8">m_ForgetLayerNormWeights</a> = &forgetLayerNormWeightsTensor;</div><div class="line"><a name="l01639"></a><span class="lineno"> 1639</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aeef6f1ac3efad8ec8b0a7118652b64c9">m_CellLayerNormWeights</a> = &cellLayerNormWeightsTensor;</div><div class="line"><a name="l01640"></a><span class="lineno"> 1640</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a0e0f66bd03c88f3d2dc666f581d3cf12">m_OutputLayerNormWeights</a> = &outputLayerNormWeightsTensor;</div><div class="line"><a name="l01641"></a><span class="lineno"> 1641</span> </div><div class="line"><a name="l01642"></a><span class="lineno"> 1642</span>  <span class="comment">// Flags to set test configuration</span></div><div class="line"><a name="l01643"></a><span class="lineno"> 1643</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = 4;</div><div class="line"><a name="l01644"></a><span class="lineno"> 1644</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01645"></a><span class="lineno"> 1645</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l01646"></a><span class="lineno"> 1646</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l01647"></a><span class="lineno"> 1647</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l01648"></a><span class="lineno"> 1648</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">m_TimeMajor</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01649"></a><span class="lineno"> 1649</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a> = 10.0f;</div><div class="line"><a name="l01650"></a><span class="lineno"> 1650</span> </div><div class="line"><a name="l01651"></a><span class="lineno"> 1651</span>  std::unique_ptr<armnn::IWorkload> workload</div><div class="line"><a name="l01652"></a><span class="lineno"> 1652</span>  = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">CreateWorkload</a>(<a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a>, data, info);</div><div class="line"><a name="l01653"></a><span class="lineno"> 1653</span>  inputHandle->Allocate();</div><div class="line"><a name="l01654"></a><span class="lineno"> 1654</span>  outputStateInHandle->Allocate();</div><div class="line"><a name="l01655"></a><span class="lineno"> 1655</span>  cellStateInHandle->Allocate();</div><div class="line"><a name="l01656"></a><span class="lineno"> 1656</span>  outputHandle->Allocate();</div><div class="line"><a name="l01657"></a><span class="lineno"> 1657</span> </div><div class="line"><a name="l01658"></a><span class="lineno"> 1658</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), inputVector.data());</div><div class="line"><a name="l01659"></a><span class="lineno"> 1659</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(outputStateInHandle.get(), outputStateInVector.data());</div><div class="line"><a name="l01660"></a><span class="lineno"> 1660</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(cellStateInHandle.get(), cellStateInVector.data());</div><div class="line"><a name="l01661"></a><span class="lineno"> 1661</span> </div><div class="line"><a name="l01662"></a><span class="lineno"> 1662</span>  workload->Execute();</div><div class="line"><a name="l01663"></a><span class="lineno"> 1663</span> </div><div class="line"><a name="l01664"></a><span class="lineno"> 1664</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a>(actualOutput.data(), outputHandle.get());</div><div class="line"><a name="l01665"></a><span class="lineno"> 1665</span> </div><div class="line"><a name="l01666"></a><span class="lineno"> 1666</span>  <span class="keywordflow">return</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 3></a>(actualOutput,</div><div class="line"><a name="l01667"></a><span class="lineno"> 1667</span>  expectedOutput,</div><div class="line"><a name="l01668"></a><span class="lineno"> 1668</span>  outputHandle->GetShape(),</div><div class="line"><a name="l01669"></a><span class="lineno"> 1669</span>  outputTensorInfo.GetShape());</div><div class="line"><a name="l01670"></a><span class="lineno"> 1670</span> }</div><div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::LstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01114">Descriptors.hpp:1114</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a44eb7524badcca9b2073359e3814c98b"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00752">WorkloadData.hpp:752</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ac18c8b8b2039267d8282e91b4162d8aa"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">WorkloadData.hpp:747</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ab160eba2493d5fe52185c0986dcb190c"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00741">WorkloadData.hpp:741</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a3dcd10ca3ea2e132558b1e2814668c15"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">armnn::LstmDescriptor::m_TimeMajor</a></div><div class="ttdeci">bool m_TimeMajor</div><div class="ttdoc">Enable/disable time major. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01118">Descriptors.hpp:1118</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">WorkloadData.hpp:54</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_afaaca8c3f3a467d124bba44067d2afa8"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a></div><div class="ttdeci">void AllocateAndCopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00019">TensorCopyUtils.cpp:19</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a5ff4158b1b363b898d0da04c42d37ce0"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">WorkloadData.hpp:755</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ac668b31de6fb0f19d4c793d5ed3c3316"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ProjectionBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00757">WorkloadData.hpp:757</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a17ba1c8bcc71a55a95b2a3913f8cb203"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">WorkloadData.hpp:744</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a841439e3b8dc157a7368b19c9ecb7d03"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">WorkloadData.hpp:743</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aab77f54a037658ca9b2bf9cc8a1fadf1"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">WorkloadData.hpp:742</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aeef6f1ac3efad8ec8b0a7118652b64c9"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aeef6f1ac3efad8ec8b0a7118652b64c9">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00760">WorkloadData.hpp:760</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a951b7c90b862138071a298065f16be61"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00749">WorkloadData.hpp:749</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a3ead2ef8da00b2709d561d85996fc513"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_ProjectionWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00756">WorkloadData.hpp:756</a></div></div> +<div class="ttc" id="classarmnn_1_1_scoped_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_tensor_handle_8hpp_source.xhtml#l00115">TensorHandle.hpp:115</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::LstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01112">Descriptors.hpp:1112</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ab5dfed8358e500ed523d78090ec78e88"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *mem, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ae1b07ed928036004bd257169e5aeeef4"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">armnn::LstmDescriptor::m_ActivationFunc</a></div><div class="ttdeci">uint32_t m_ActivationFunc</div><div class="ttdoc">The activation function to use. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01104">Descriptors.hpp:1104</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a531a3907ec13d3772370da88030191a5"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">armnn::LstmDescriptor::m_ClippingThresCell</a></div><div class="ttdeci">float m_ClippingThresCell</div><div class="ttdoc">Clipping threshold value for the cell state. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01106">Descriptors.hpp:1106</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ad9442e26aa79f896da5f404ab825a9c8"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ad9442e26aa79f896da5f404ab825a9c8">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ForgetLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00759">WorkloadData.hpp:759</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a0e0f66bd03c88f3d2dc666f581d3cf12"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a0e0f66bd03c88f3d2dc666f581d3cf12">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_OutputLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00761">WorkloadData.hpp:761</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::LstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable cifg (coupled input & forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01110">Descriptors.hpp:1110</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a29fa293fffbf9c6f00cd75db1dc0a52a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">WorkloadData.hpp:753</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a6e9593869b82984de198fed27f72cdcf"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a></div><div class="ttdeci">const ConstTensorHandle * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">WorkloadData.hpp:754</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a4a8ec49f130084445d44297549254780"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">armnn::LstmDescriptor::m_LayerNormEnabled</a></div><div class="ttdeci">bool m_LayerNormEnabled</div><div class="ttdoc">Enable/disable layer normalization. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01116">Descriptors.hpp:1116</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a299587d4f3fca029492700f3e2585bd8"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00745">WorkloadData.hpp:745</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00015">LayerTestResult.hpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a20c10fcb26657477377d07b7b1e13120"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00750">WorkloadData.hpp:750</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00714">WorkloadData.hpp:714</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a4c27716f61bb68e8ea0bd4e8389ba01a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">WorkloadData.hpp:748</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a13060ebb89d2c21a7a5d897e99cccf72"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">armnn::IWorkloadFactory::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01541">WorkloadFactory.cpp:1541</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_adf8571dd1867ee91082bd005f94f2610"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">WorkloadData.hpp:746</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aa09f7bdb9fd0d06b6386e412a4e72dd6"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00751">WorkloadData.hpp:751</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a1dbad32cad5c0437e1272f59fedf52ea"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a1dbad32cad5c0437e1272f59fedf52ea">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00758">WorkloadData.hpp:758</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a96b8e256c3e15254d98f27f291d6befb"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a96b8e256c3e15254d98f27f291d6befb">◆ </a></span>UnidirectionalSequenceLstmLayerInt8Test()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 3> UnidirectionalSequenceLstmLayerInt8Test </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml#l01037">1037</a> of file <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml">UnidirectionalSequenceLstmTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01541">IWorkloadFactory::CreateWorkload()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01104">LstmDescriptor::m_ActivationFunc</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01110">LstmDescriptor::m_CifgEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01106">LstmDescriptor::m_ClippingThresCell</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01108">LstmDescriptor::m_ClippingThresProj</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00752">UnidirectionalSequenceLstmQueueDescriptor::m_InputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00741">UnidirectionalSequenceLstmQueueDescriptor::m_InputToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01112">LstmDescriptor::m_PeepholeEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01114">LstmDescriptor::m_ProjectionEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00745">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01118">LstmDescriptor::m_TimeMajor</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::QAsymmS8</a>, and <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::UnidirectionalSequenceLstm</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l01041"></a><span class="lineno"> 1041</span> {</div><div class="line"><a name="l01042"></a><span class="lineno"> 1042</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l01043"></a><span class="lineno"> 1043</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 3;</div><div class="line"><a name="l01044"></a><span class="lineno"> 1044</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> timeSize = 2;</div><div class="line"><a name="l01045"></a><span class="lineno"> 1045</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputSize = 3;</div><div class="line"><a name="l01046"></a><span class="lineno"> 1046</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = 4;</div><div class="line"><a name="l01047"></a><span class="lineno"> 1047</span>  <span class="keywordtype">unsigned</span> numUnits = outputSize;</div><div class="line"><a name="l01048"></a><span class="lineno"> 1048</span> </div><div class="line"><a name="l01049"></a><span class="lineno"> 1049</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({batchSize, timeSize, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01050"></a><span class="lineno"> 1050</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> cellStateInTensorInfo({batchSize, numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01051"></a><span class="lineno"> 1051</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputStateInTensorInfo({batchSize, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01052"></a><span class="lineno"> 1052</span> </div><div class="line"><a name="l01053"></a><span class="lineno"> 1053</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({batchSize, timeSize, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01054"></a><span class="lineno"> 1054</span> </div><div class="line"><a name="l01055"></a><span class="lineno"> 1055</span>  <span class="keyword">const</span> std::vector<float> inputVector = { 0.1f, 0.2f, 0.3f, 0.4f, 0.5f, 0.4f,</div><div class="line"><a name="l01056"></a><span class="lineno"> 1056</span>  0.3f, 0.2f, 0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l01057"></a><span class="lineno"> 1057</span>  0.5f, 0.4f, 0.3f, 0.2f, 0.1f, 0.2f };</div><div class="line"><a name="l01058"></a><span class="lineno"> 1058</span> </div><div class="line"><a name="l01059"></a><span class="lineno"> 1059</span>  std::vector<float> cellStateInVector(batchSize * numUnits, 0.f);</div><div class="line"><a name="l01060"></a><span class="lineno"> 1060</span>  std::vector<float> outputStateInVector(batchSize * outputSize, 0.f);</div><div class="line"><a name="l01061"></a><span class="lineno"> 1061</span> </div><div class="line"><a name="l01062"></a><span class="lineno"> 1062</span>  std::vector<float> actualOutput(outputTensorInfo.GetNumElements());</div><div class="line"><a name="l01063"></a><span class="lineno"> 1063</span> </div><div class="line"><a name="l01064"></a><span class="lineno"> 1064</span>  <span class="keyword">const</span> std::vector<float> outputVector = { -0.0142517f, -0.0198845f, -0.0120569f, -0.0116868f,</div><div class="line"><a name="l01065"></a><span class="lineno"> 1065</span>  -0.0350714f, -0.0343202f, -0.047504f, -0.0569789f,</div><div class="line"><a name="l01066"></a><span class="lineno"> 1066</span>  -0.0146346f, 0.0106663f, -0.0247238f, -0.0319502f,</div><div class="line"><a name="l01067"></a><span class="lineno"> 1067</span>  -0.0294759f, -0.0129935f, -0.0444175f, -0.0444354f,</div><div class="line"><a name="l01068"></a><span class="lineno"> 1068</span>  -0.0280855f, 0.00545101f, -0.051422f, -0.0463838f,</div><div class="line"><a name="l01069"></a><span class="lineno"> 1069</span>  -0.0310702f, 0.00915739f, -0.0625207f, -0.0482648f };</div><div class="line"><a name="l01070"></a><span class="lineno"> 1070</span> </div><div class="line"><a name="l01071"></a><span class="lineno"> 1071</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l01072"></a><span class="lineno"> 1072</span>  std::unique_ptr<armnn::ITensorHandle> cellStateInHandle =</div><div class="line"><a name="l01073"></a><span class="lineno"> 1073</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(cellStateInTensorInfo);</div><div class="line"><a name="l01074"></a><span class="lineno"> 1074</span>  std::unique_ptr<armnn::ITensorHandle> outputStateInHandle =</div><div class="line"><a name="l01075"></a><span class="lineno"> 1075</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputStateInTensorInfo);</div><div class="line"><a name="l01076"></a><span class="lineno"> 1076</span> </div><div class="line"><a name="l01077"></a><span class="lineno"> 1077</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l01078"></a><span class="lineno"> 1078</span> </div><div class="line"><a name="l01079"></a><span class="lineno"> 1079</span>  <a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a> data;</div><div class="line"><a name="l01080"></a><span class="lineno"> 1080</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l01081"></a><span class="lineno"> 1081</span> </div><div class="line"><a name="l01082"></a><span class="lineno"> 1082</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l01083"></a><span class="lineno"> 1083</span>  AddInputToWorkload(data, info, outputStateInTensorInfo, outputStateInHandle.get());</div><div class="line"><a name="l01084"></a><span class="lineno"> 1084</span>  AddInputToWorkload(data, info, cellStateInTensorInfo, cellStateInHandle.get());</div><div class="line"><a name="l01085"></a><span class="lineno"> 1085</span> </div><div class="line"><a name="l01086"></a><span class="lineno"> 1086</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l01087"></a><span class="lineno"> 1087</span> </div><div class="line"><a name="l01088"></a><span class="lineno"> 1088</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumFp({numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01089"></a><span class="lineno"> 1089</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumInput({numUnits, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01090"></a><span class="lineno"> 1090</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumOutput({numUnits, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01091"></a><span class="lineno"> 1091</span> </div><div class="line"><a name="l01092"></a><span class="lineno"> 1092</span>  std::vector<int8_t> inputToInputWeights = { -4, -1, -1, -2, 3, -2, 2, 4, 1, -4, -2, 3 };</div><div class="line"><a name="l01093"></a><span class="lineno"> 1093</span>  std::vector<int8_t> inputToForgetWeights = { 2, 1, 4, -4, 3, -1, -3, -2, -3, 1, -4, -1 };</div><div class="line"><a name="l01094"></a><span class="lineno"> 1094</span>  std::vector<int8_t> inputToCellWeights = { -2, 1, -2, 4, -3, -2, -4, 3, -2, -2, -6, 3 };</div><div class="line"><a name="l01095"></a><span class="lineno"> 1095</span>  std::vector<int8_t> inputToOutputWeights = { 2, 5, -4, 5, 2, -3, 5, 7, 3, -5, 1, -4 };</div><div class="line"><a name="l01096"></a><span class="lineno"> 1096</span> </div><div class="line"><a name="l01097"></a><span class="lineno"> 1097</span>  std::vector<int8_t> recurrentToInputWeights = { -1, 1, -1, 1, -3, -4, -1, 4, 2, 3, 5, -1, 1, 3, -1, -1 };</div><div class="line"><a name="l01098"></a><span class="lineno"> 1098</span>  std::vector<int8_t> recurrentToForgetWeights = { -1, 1, -1, 1, -3, -4, -1, 4, 2, 3, 5, -1, 1, 3, -2, -1 };</div><div class="line"><a name="l01099"></a><span class="lineno"> 1099</span>  std::vector<int8_t> recurrentToCellWeights = { -2, -3, -1, -3, -4, 2, 1, -1, 2, 2, 1, 2, 3, -2, 3, -3 };</div><div class="line"><a name="l01100"></a><span class="lineno"> 1100</span>  std::vector<int8_t> recurrentToOutputWeights = { -3, 3, -1, -2, -2, -2, -1, -5, 1, 3, -4, -1, -1, -1, 2, -1 };</div><div class="line"><a name="l01101"></a><span class="lineno"> 1101</span> </div><div class="line"><a name="l01102"></a><span class="lineno"> 1102</span>  std::vector<float> inputGateBias = { 0., 0., 0., 0. };</div><div class="line"><a name="l01103"></a><span class="lineno"> 1103</span>  std::vector<float> forgetGateBias = { 1., 1., 1., 1. };</div><div class="line"><a name="l01104"></a><span class="lineno"> 1104</span>  std::vector<float> cellBias = { 0., 0., 0., 0. };</div><div class="line"><a name="l01105"></a><span class="lineno"> 1105</span>  std::vector<float> outputGateBias = { 0., 0., 0., 0. };</div><div class="line"><a name="l01106"></a><span class="lineno"> 1106</span> </div><div class="line"><a name="l01107"></a><span class="lineno"> 1107</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToInputWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01108"></a><span class="lineno"> 1108</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToForgetWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01109"></a><span class="lineno"> 1109</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToCellWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01110"></a><span class="lineno"> 1110</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToOutputWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01111"></a><span class="lineno"> 1111</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToInputWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01112"></a><span class="lineno"> 1112</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToForgetWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01113"></a><span class="lineno"> 1113</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToCellWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01114"></a><span class="lineno"> 1114</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToOutputWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01115"></a><span class="lineno"> 1115</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01116"></a><span class="lineno"> 1116</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> forgetGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01117"></a><span class="lineno"> 1117</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01118"></a><span class="lineno"> 1118</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> outputGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01119"></a><span class="lineno"> 1119</span> </div><div class="line"><a name="l01120"></a><span class="lineno"> 1120</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToInputWeightsTensor, inputToInputWeights.data());</div><div class="line"><a name="l01121"></a><span class="lineno"> 1121</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToForgetWeightsTensor, inputToForgetWeights.data());</div><div class="line"><a name="l01122"></a><span class="lineno"> 1122</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToCellWeightsTensor, inputToCellWeights.data());</div><div class="line"><a name="l01123"></a><span class="lineno"> 1123</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToOutputWeightsTensor, inputToOutputWeights.data());</div><div class="line"><a name="l01124"></a><span class="lineno"> 1124</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToInputWeightsTensor, recurrentToInputWeights.data());</div><div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToForgetWeightsTensor, recurrentToForgetWeights.data());</div><div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToCellWeightsTensor, recurrentToCellWeights.data());</div><div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToOutputWeightsTensor, recurrentToOutputWeights.data());</div><div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputGateBiasTensor, inputGateBias.data());</div><div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&forgetGateBiasTensor, forgetGateBias.data());</div><div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellBiasTensor, cellBias.data());</div><div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&outputGateBiasTensor, outputGateBias.data());</div><div class="line"><a name="l01132"></a><span class="lineno"> 1132</span> </div><div class="line"><a name="l01133"></a><span class="lineno"> 1133</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">m_InputToInputWeights</a> = &inputToInputWeightsTensor;</div><div class="line"><a name="l01134"></a><span class="lineno"> 1134</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">m_InputToForgetWeights</a> = &inputToForgetWeightsTensor;</div><div class="line"><a name="l01135"></a><span class="lineno"> 1135</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">m_InputToCellWeights</a> = &inputToCellWeightsTensor;</div><div class="line"><a name="l01136"></a><span class="lineno"> 1136</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">m_InputToOutputWeights</a> = &inputToOutputWeightsTensor;</div><div class="line"><a name="l01137"></a><span class="lineno"> 1137</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">m_RecurrentToInputWeights</a> = &recurrentToInputWeightsTensor;</div><div class="line"><a name="l01138"></a><span class="lineno"> 1138</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeightsTensor;</div><div class="line"><a name="l01139"></a><span class="lineno"> 1139</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">m_RecurrentToCellWeights</a> = &recurrentToCellWeightsTensor;</div><div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeightsTensor;</div><div class="line"><a name="l01141"></a><span class="lineno"> 1141</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">m_InputGateBias</a> = &inputGateBiasTensor;</div><div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">m_ForgetGateBias</a> = &forgetGateBiasTensor;</div><div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">m_CellBias</a> = &cellBiasTensor;</div><div class="line"><a name="l01144"></a><span class="lineno"> 1144</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">m_OutputGateBias</a> = &outputGateBiasTensor;</div><div class="line"><a name="l01145"></a><span class="lineno"> 1145</span> </div><div class="line"><a name="l01146"></a><span class="lineno"> 1146</span>  <span class="comment">// Flags to set test configuration</span></div><div class="line"><a name="l01147"></a><span class="lineno"> 1147</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a> = 10;</div><div class="line"><a name="l01148"></a><span class="lineno"> 1148</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a86e88bef0df4df96df752b4b8955a3af">m_ClippingThresProj</a> = 0;</div><div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = 4;</div><div class="line"><a name="l01150"></a><span class="lineno"> 1150</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01151"></a><span class="lineno"> 1151</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01153"></a><span class="lineno"> 1153</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">m_TimeMajor</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01154"></a><span class="lineno"> 1154</span> </div><div class="line"><a name="l01155"></a><span class="lineno"> 1155</span>  std::unique_ptr<armnn::IWorkload> workload</div><div class="line"><a name="l01156"></a><span class="lineno"> 1156</span>  = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">CreateWorkload</a>(<a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a>, data, info);</div><div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>  inputHandle->Allocate();</div><div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>  outputStateInHandle->Allocate();</div><div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>  cellStateInHandle->Allocate();</div><div class="line"><a name="l01160"></a><span class="lineno"> 1160</span> </div><div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>  outputHandle->Allocate();</div><div class="line"><a name="l01162"></a><span class="lineno"> 1162</span> </div><div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), inputVector.data());</div><div class="line"><a name="l01164"></a><span class="lineno"> 1164</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(outputStateInHandle.get(), outputStateInVector.data());</div><div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(cellStateInHandle.get(), cellStateInVector.data());</div><div class="line"><a name="l01166"></a><span class="lineno"> 1166</span> </div><div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>  workload->Execute();</div><div class="line"><a name="l01168"></a><span class="lineno"> 1168</span> </div><div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a>(actualOutput.data(), outputHandle.get());</div><div class="line"><a name="l01170"></a><span class="lineno"> 1170</span> </div><div class="line"><a name="l01171"></a><span class="lineno"> 1171</span>  <span class="keywordflow">return</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 3></a>(actualOutput,</div><div class="line"><a name="l01172"></a><span class="lineno"> 1172</span>  outputVector,</div><div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>  outputHandle->GetShape(),</div><div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>  outputTensorInfo.GetShape());</div><div class="line"><a name="l01175"></a><span class="lineno"> 1175</span> }</div><div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::LstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01114">Descriptors.hpp:1114</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a44eb7524badcca9b2073359e3814c98b"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00752">WorkloadData.hpp:752</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a86e88bef0df4df96df752b4b8955a3af"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a86e88bef0df4df96df752b4b8955a3af">armnn::LstmDescriptor::m_ClippingThresProj</a></div><div class="ttdeci">float m_ClippingThresProj</div><div class="ttdoc">Clipping threshold value for the projection. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01108">Descriptors.hpp:1108</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ac18c8b8b2039267d8282e91b4162d8aa"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">WorkloadData.hpp:747</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ab160eba2493d5fe52185c0986dcb190c"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00741">WorkloadData.hpp:741</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a3dcd10ca3ea2e132558b1e2814668c15"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">armnn::LstmDescriptor::m_TimeMajor</a></div><div class="ttdeci">bool m_TimeMajor</div><div class="ttdoc">Enable/disable time major. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01118">Descriptors.hpp:1118</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">WorkloadData.hpp:54</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_afaaca8c3f3a467d124bba44067d2afa8"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a></div><div class="ttdeci">void AllocateAndCopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00019">TensorCopyUtils.cpp:19</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a5ff4158b1b363b898d0da04c42d37ce0"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">WorkloadData.hpp:755</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a17ba1c8bcc71a55a95b2a3913f8cb203"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">WorkloadData.hpp:744</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a841439e3b8dc157a7368b19c9ecb7d03"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">WorkloadData.hpp:743</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aab77f54a037658ca9b2bf9cc8a1fadf1"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">WorkloadData.hpp:742</a></div></div> +<div class="ttc" id="classarmnn_1_1_scoped_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_tensor_handle_8hpp_source.xhtml#l00115">TensorHandle.hpp:115</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::LstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01112">Descriptors.hpp:1112</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ab5dfed8358e500ed523d78090ec78e88"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *mem, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ae1b07ed928036004bd257169e5aeeef4"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">armnn::LstmDescriptor::m_ActivationFunc</a></div><div class="ttdeci">uint32_t m_ActivationFunc</div><div class="ttdoc">The activation function to use. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01104">Descriptors.hpp:1104</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a531a3907ec13d3772370da88030191a5"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">armnn::LstmDescriptor::m_ClippingThresCell</a></div><div class="ttdeci">float m_ClippingThresCell</div><div class="ttdoc">Clipping threshold value for the cell state. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01106">Descriptors.hpp:1106</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::LstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable cifg (coupled input & forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01110">Descriptors.hpp:1110</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a29fa293fffbf9c6f00cd75db1dc0a52a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">WorkloadData.hpp:753</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a6e9593869b82984de198fed27f72cdcf"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a></div><div class="ttdeci">const ConstTensorHandle * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">WorkloadData.hpp:754</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a299587d4f3fca029492700f3e2585bd8"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00745">WorkloadData.hpp:745</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00015">LayerTestResult.hpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00714">WorkloadData.hpp:714</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a4c27716f61bb68e8ea0bd4e8389ba01a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">WorkloadData.hpp:748</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a13060ebb89d2c21a7a5d897e99cccf72"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">armnn::IWorkloadFactory::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01541">WorkloadFactory.cpp:1541</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_adf8571dd1867ee91082bd005f94f2610"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">WorkloadData.hpp:746</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="af09125829e58e0e9e05e0ecd3f1bcacb"></a> +<h2 class="memtitle"><span class="permalink"><a href="#af09125829e58e0e9e05e0ecd3f1bcacb">◆ </a></span>UnidirectionalSequenceLstmLayerInt8TimeMajorTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 3> UnidirectionalSequenceLstmLayerInt8TimeMajorTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml#l01177">1177</a> of file <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml">UnidirectionalSequenceLstmTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01541">IWorkloadFactory::CreateWorkload()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01104">LstmDescriptor::m_ActivationFunc</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01110">LstmDescriptor::m_CifgEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01106">LstmDescriptor::m_ClippingThresCell</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01108">LstmDescriptor::m_ClippingThresProj</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00752">UnidirectionalSequenceLstmQueueDescriptor::m_InputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00741">UnidirectionalSequenceLstmQueueDescriptor::m_InputToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01112">LstmDescriptor::m_PeepholeEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01114">LstmDescriptor::m_ProjectionEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00745">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01118">LstmDescriptor::m_TimeMajor</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::QAsymmS8</a>, and <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::UnidirectionalSequenceLstm</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l01181"></a><span class="lineno"> 1181</span> {</div><div class="line"><a name="l01182"></a><span class="lineno"> 1182</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l01183"></a><span class="lineno"> 1183</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 3;</div><div class="line"><a name="l01184"></a><span class="lineno"> 1184</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> timeSize = 2;</div><div class="line"><a name="l01185"></a><span class="lineno"> 1185</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputSize = 3;</div><div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = 4;</div><div class="line"><a name="l01187"></a><span class="lineno"> 1187</span>  <span class="keywordtype">unsigned</span> numUnits = outputSize;</div><div class="line"><a name="l01188"></a><span class="lineno"> 1188</span> </div><div class="line"><a name="l01189"></a><span class="lineno"> 1189</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({timeSize, batchSize, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01190"></a><span class="lineno"> 1190</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> cellStateInTensorInfo({batchSize, numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01191"></a><span class="lineno"> 1191</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputStateInTensorInfo({batchSize, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01192"></a><span class="lineno"> 1192</span> </div><div class="line"><a name="l01193"></a><span class="lineno"> 1193</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({timeSize, batchSize, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01194"></a><span class="lineno"> 1194</span> </div><div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>  <span class="keyword">const</span> std::vector<float> inputVector = { 0.1f, 0.2f, 0.3f, 0.4f, 0.5f, 0.4f,</div><div class="line"><a name="l01196"></a><span class="lineno"> 1196</span>  0.3f, 0.2f, 0.1f, 0.2f, 0.3f, 0.4f,</div><div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>  0.5f, 0.4f, 0.3f, 0.2f, 0.1f, 0.2f };</div><div class="line"><a name="l01198"></a><span class="lineno"> 1198</span> </div><div class="line"><a name="l01199"></a><span class="lineno"> 1199</span>  std::vector<float> cellStateInVector(batchSize * numUnits, 0.f);</div><div class="line"><a name="l01200"></a><span class="lineno"> 1200</span>  std::vector<float> outputStateInVector(batchSize * outputSize, 0.f);</div><div class="line"><a name="l01201"></a><span class="lineno"> 1201</span> </div><div class="line"><a name="l01202"></a><span class="lineno"> 1202</span>  std::vector<float> actualOutput(outputTensorInfo.GetNumElements());</div><div class="line"><a name="l01203"></a><span class="lineno"> 1203</span> </div><div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>  <span class="keyword">const</span> std::vector<float> outputVector = { -0.0142517f, -0.0198845f, -0.0120122f, -0.0116868f,</div><div class="line"><a name="l01205"></a><span class="lineno"> 1205</span>  -0.0261295f, -0.0188487f, -0.0345463f, -0.049733f,</div><div class="line"><a name="l01206"></a><span class="lineno"> 1206</span>  -0.0146346f, 0.0106663f, -0.0247238f, -0.0319502f,</div><div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>  -0.0291863f, -0.0369402f, -0.0354071f, -0.0296529f,</div><div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>  -0.0419539f, -0.00617731f, -0.0814796f, -0.0804005f,</div><div class="line"><a name="l01209"></a><span class="lineno"> 1209</span>  -0.0244737f, 0.0119905f, -0.0457527f, -0.0331862f };</div><div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l01211"></a><span class="lineno"> 1211</span>  std::unique_ptr<armnn::ITensorHandle> cellStateInHandle =</div><div class="line"><a name="l01212"></a><span class="lineno"> 1212</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(cellStateInTensorInfo);</div><div class="line"><a name="l01213"></a><span class="lineno"> 1213</span>  std::unique_ptr<armnn::ITensorHandle> outputStateInHandle =</div><div class="line"><a name="l01214"></a><span class="lineno"> 1214</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputStateInTensorInfo);</div><div class="line"><a name="l01215"></a><span class="lineno"> 1215</span> </div><div class="line"><a name="l01216"></a><span class="lineno"> 1216</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l01217"></a><span class="lineno"> 1217</span> </div><div class="line"><a name="l01218"></a><span class="lineno"> 1218</span>  <a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a> data;</div><div class="line"><a name="l01219"></a><span class="lineno"> 1219</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l01220"></a><span class="lineno"> 1220</span> </div><div class="line"><a name="l01221"></a><span class="lineno"> 1221</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l01222"></a><span class="lineno"> 1222</span>  AddInputToWorkload(data, info, outputStateInTensorInfo, outputStateInHandle.get());</div><div class="line"><a name="l01223"></a><span class="lineno"> 1223</span>  AddInputToWorkload(data, info, cellStateInTensorInfo, cellStateInHandle.get());</div><div class="line"><a name="l01224"></a><span class="lineno"> 1224</span> </div><div class="line"><a name="l01225"></a><span class="lineno"> 1225</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l01226"></a><span class="lineno"> 1226</span> </div><div class="line"><a name="l01227"></a><span class="lineno"> 1227</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumFp({numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l01228"></a><span class="lineno"> 1228</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumInput({numUnits, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01229"></a><span class="lineno"> 1229</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfoNumOutput({numUnits, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a>, 0.1f, 0);</div><div class="line"><a name="l01230"></a><span class="lineno"> 1230</span> </div><div class="line"><a name="l01231"></a><span class="lineno"> 1231</span>  std::vector<int8_t> inputToInputWeights = { -4, -1, -1, -2, 3, -2, 2, 4, 1, -4, -2, 3 };</div><div class="line"><a name="l01232"></a><span class="lineno"> 1232</span>  std::vector<int8_t> inputToForgetWeights = { 2, 1, 4, -4, 3, -1, -3, -2, -3, 1, -4, -1 };</div><div class="line"><a name="l01233"></a><span class="lineno"> 1233</span>  std::vector<int8_t> inputToCellWeights = { -2, 1, -2, 4, -3, -2, -4, 3, -2, -2, -6, 3 };</div><div class="line"><a name="l01234"></a><span class="lineno"> 1234</span>  std::vector<int8_t> inputToOutputWeights = { 2, 5, -4, 5, 2, -3, 5, 7, 3, -5, 1, -4 };</div><div class="line"><a name="l01235"></a><span class="lineno"> 1235</span> </div><div class="line"><a name="l01236"></a><span class="lineno"> 1236</span>  std::vector<int8_t> recurrentToInputWeights = { -1, 1, -1, 1, -3, -4, -1, 4, 2, 3, 5, -1, 1, 3, -1, -1 };</div><div class="line"><a name="l01237"></a><span class="lineno"> 1237</span>  std::vector<int8_t> recurrentToForgetWeights = { -1, 1, -1, 1, -3, -4, -1, 4, 2, 3, 5, -1, 1, 3, -2, -1 };</div><div class="line"><a name="l01238"></a><span class="lineno"> 1238</span>  std::vector<int8_t> recurrentToCellWeights = { -2, -3, -1, -3, -4, 2, 1, -1, 2, 2, 1, 2, 3, -2, 3, -3 };</div><div class="line"><a name="l01239"></a><span class="lineno"> 1239</span>  std::vector<int8_t> recurrentToOutputWeights = { -3, 3, -1, -2, -2, -2, -1, -5, 1, 3, -4, -1, -1, -1, 2, -1 };</div><div class="line"><a name="l01240"></a><span class="lineno"> 1240</span> </div><div class="line"><a name="l01241"></a><span class="lineno"> 1241</span> </div><div class="line"><a name="l01242"></a><span class="lineno"> 1242</span>  std::vector<float> inputGateBias = { 0., 0., 0., 0. };</div><div class="line"><a name="l01243"></a><span class="lineno"> 1243</span>  std::vector<float> forgetGateBias = { 1., 1., 1., 1. };</div><div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>  std::vector<float> cellBias = { 0., 0., 0., 0. };</div><div class="line"><a name="l01245"></a><span class="lineno"> 1245</span>  std::vector<float> outputGateBias = { 0., 0., 0., 0. };</div><div class="line"><a name="l01246"></a><span class="lineno"> 1246</span> </div><div class="line"><a name="l01247"></a><span class="lineno"> 1247</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToInputWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01248"></a><span class="lineno"> 1248</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToForgetWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01249"></a><span class="lineno"> 1249</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToCellWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01250"></a><span class="lineno"> 1250</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToOutputWeightsTensor(tensorInfoNumInput);</div><div class="line"><a name="l01251"></a><span class="lineno"> 1251</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToInputWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01252"></a><span class="lineno"> 1252</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToForgetWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01253"></a><span class="lineno"> 1253</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToCellWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01254"></a><span class="lineno"> 1254</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToOutputWeightsTensor(tensorInfoNumOutput);</div><div class="line"><a name="l01255"></a><span class="lineno"> 1255</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01256"></a><span class="lineno"> 1256</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> forgetGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01257"></a><span class="lineno"> 1257</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01258"></a><span class="lineno"> 1258</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> outputGateBiasTensor(tensorInfoNumFp);</div><div class="line"><a name="l01259"></a><span class="lineno"> 1259</span> </div><div class="line"><a name="l01260"></a><span class="lineno"> 1260</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToInputWeightsTensor, inputToInputWeights.data());</div><div class="line"><a name="l01261"></a><span class="lineno"> 1261</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToForgetWeightsTensor, inputToForgetWeights.data());</div><div class="line"><a name="l01262"></a><span class="lineno"> 1262</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToCellWeightsTensor, inputToCellWeights.data());</div><div class="line"><a name="l01263"></a><span class="lineno"> 1263</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToOutputWeightsTensor, inputToOutputWeights.data());</div><div class="line"><a name="l01264"></a><span class="lineno"> 1264</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToInputWeightsTensor, recurrentToInputWeights.data());</div><div class="line"><a name="l01265"></a><span class="lineno"> 1265</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToForgetWeightsTensor, recurrentToForgetWeights.data());</div><div class="line"><a name="l01266"></a><span class="lineno"> 1266</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToCellWeightsTensor, recurrentToCellWeights.data());</div><div class="line"><a name="l01267"></a><span class="lineno"> 1267</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToOutputWeightsTensor, recurrentToOutputWeights.data());</div><div class="line"><a name="l01268"></a><span class="lineno"> 1268</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputGateBiasTensor, inputGateBias.data());</div><div class="line"><a name="l01269"></a><span class="lineno"> 1269</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&forgetGateBiasTensor, forgetGateBias.data());</div><div class="line"><a name="l01270"></a><span class="lineno"> 1270</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellBiasTensor, cellBias.data());</div><div class="line"><a name="l01271"></a><span class="lineno"> 1271</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&outputGateBiasTensor, outputGateBias.data());</div><div class="line"><a name="l01272"></a><span class="lineno"> 1272</span> </div><div class="line"><a name="l01273"></a><span class="lineno"> 1273</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">m_InputToInputWeights</a> = &inputToInputWeightsTensor;</div><div class="line"><a name="l01274"></a><span class="lineno"> 1274</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">m_InputToForgetWeights</a> = &inputToForgetWeightsTensor;</div><div class="line"><a name="l01275"></a><span class="lineno"> 1275</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">m_InputToCellWeights</a> = &inputToCellWeightsTensor;</div><div class="line"><a name="l01276"></a><span class="lineno"> 1276</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">m_InputToOutputWeights</a> = &inputToOutputWeightsTensor;</div><div class="line"><a name="l01277"></a><span class="lineno"> 1277</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">m_RecurrentToInputWeights</a> = &recurrentToInputWeightsTensor;</div><div class="line"><a name="l01278"></a><span class="lineno"> 1278</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeightsTensor;</div><div class="line"><a name="l01279"></a><span class="lineno"> 1279</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">m_RecurrentToCellWeights</a> = &recurrentToCellWeightsTensor;</div><div class="line"><a name="l01280"></a><span class="lineno"> 1280</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeightsTensor;</div><div class="line"><a name="l01281"></a><span class="lineno"> 1281</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">m_InputGateBias</a> = &inputGateBiasTensor;</div><div class="line"><a name="l01282"></a><span class="lineno"> 1282</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">m_ForgetGateBias</a> = &forgetGateBiasTensor;</div><div class="line"><a name="l01283"></a><span class="lineno"> 1283</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">m_CellBias</a> = &cellBiasTensor;</div><div class="line"><a name="l01284"></a><span class="lineno"> 1284</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">m_OutputGateBias</a> = &outputGateBiasTensor;</div><div class="line"><a name="l01285"></a><span class="lineno"> 1285</span> </div><div class="line"><a name="l01286"></a><span class="lineno"> 1286</span>  <span class="comment">// Flags to set test configuration</span></div><div class="line"><a name="l01287"></a><span class="lineno"> 1287</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a> = 10;</div><div class="line"><a name="l01288"></a><span class="lineno"> 1288</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a86e88bef0df4df96df752b4b8955a3af">m_ClippingThresProj</a> = 0;</div><div class="line"><a name="l01289"></a><span class="lineno"> 1289</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = 4;</div><div class="line"><a name="l01290"></a><span class="lineno"> 1290</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01291"></a><span class="lineno"> 1291</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01292"></a><span class="lineno"> 1292</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01293"></a><span class="lineno"> 1293</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">m_TimeMajor</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l01294"></a><span class="lineno"> 1294</span> </div><div class="line"><a name="l01295"></a><span class="lineno"> 1295</span>  std::unique_ptr<armnn::IWorkload> workload</div><div class="line"><a name="l01296"></a><span class="lineno"> 1296</span>  = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">CreateWorkload</a>(<a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a>, data, info);</div><div class="line"><a name="l01297"></a><span class="lineno"> 1297</span>  inputHandle->Allocate();</div><div class="line"><a name="l01298"></a><span class="lineno"> 1298</span>  outputStateInHandle->Allocate();</div><div class="line"><a name="l01299"></a><span class="lineno"> 1299</span>  cellStateInHandle->Allocate();</div><div class="line"><a name="l01300"></a><span class="lineno"> 1300</span> </div><div class="line"><a name="l01301"></a><span class="lineno"> 1301</span>  outputHandle->Allocate();</div><div class="line"><a name="l01302"></a><span class="lineno"> 1302</span> </div><div class="line"><a name="l01303"></a><span class="lineno"> 1303</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), inputVector.data());</div><div class="line"><a name="l01304"></a><span class="lineno"> 1304</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(outputStateInHandle.get(), outputStateInVector.data());</div><div class="line"><a name="l01305"></a><span class="lineno"> 1305</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(cellStateInHandle.get(), cellStateInVector.data());</div><div class="line"><a name="l01306"></a><span class="lineno"> 1306</span> </div><div class="line"><a name="l01307"></a><span class="lineno"> 1307</span>  workload->Execute();</div><div class="line"><a name="l01308"></a><span class="lineno"> 1308</span> </div><div class="line"><a name="l01309"></a><span class="lineno"> 1309</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a>(actualOutput.data(), outputHandle.get());</div><div class="line"><a name="l01310"></a><span class="lineno"> 1310</span> </div><div class="line"><a name="l01311"></a><span class="lineno"> 1311</span>  <span class="keywordflow">return</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 3></a>(actualOutput,</div><div class="line"><a name="l01312"></a><span class="lineno"> 1312</span>  outputVector,</div><div class="line"><a name="l01313"></a><span class="lineno"> 1313</span>  outputHandle->GetShape(),</div><div class="line"><a name="l01314"></a><span class="lineno"> 1314</span>  outputTensorInfo.GetShape());</div><div class="line"><a name="l01315"></a><span class="lineno"> 1315</span> }</div><div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::LstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01114">Descriptors.hpp:1114</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a44eb7524badcca9b2073359e3814c98b"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00752">WorkloadData.hpp:752</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a86e88bef0df4df96df752b4b8955a3af"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a86e88bef0df4df96df752b4b8955a3af">armnn::LstmDescriptor::m_ClippingThresProj</a></div><div class="ttdeci">float m_ClippingThresProj</div><div class="ttdoc">Clipping threshold value for the projection. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01108">Descriptors.hpp:1108</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ac18c8b8b2039267d8282e91b4162d8aa"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">WorkloadData.hpp:747</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a9d02ea768c081d4bdb2b7cab0b3f510d">armnn::DataType::QAsymmS8</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ab160eba2493d5fe52185c0986dcb190c"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00741">WorkloadData.hpp:741</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a3dcd10ca3ea2e132558b1e2814668c15"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">armnn::LstmDescriptor::m_TimeMajor</a></div><div class="ttdeci">bool m_TimeMajor</div><div class="ttdoc">Enable/disable time major. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01118">Descriptors.hpp:1118</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">WorkloadData.hpp:54</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_afaaca8c3f3a467d124bba44067d2afa8"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a></div><div class="ttdeci">void AllocateAndCopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00019">TensorCopyUtils.cpp:19</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a5ff4158b1b363b898d0da04c42d37ce0"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">WorkloadData.hpp:755</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a17ba1c8bcc71a55a95b2a3913f8cb203"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">WorkloadData.hpp:744</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a841439e3b8dc157a7368b19c9ecb7d03"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">WorkloadData.hpp:743</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aab77f54a037658ca9b2bf9cc8a1fadf1"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">WorkloadData.hpp:742</a></div></div> +<div class="ttc" id="classarmnn_1_1_scoped_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_tensor_handle_8hpp_source.xhtml#l00115">TensorHandle.hpp:115</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::LstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01112">Descriptors.hpp:1112</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ab5dfed8358e500ed523d78090ec78e88"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *mem, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ae1b07ed928036004bd257169e5aeeef4"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">armnn::LstmDescriptor::m_ActivationFunc</a></div><div class="ttdeci">uint32_t m_ActivationFunc</div><div class="ttdoc">The activation function to use. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01104">Descriptors.hpp:1104</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a531a3907ec13d3772370da88030191a5"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">armnn::LstmDescriptor::m_ClippingThresCell</a></div><div class="ttdeci">float m_ClippingThresCell</div><div class="ttdoc">Clipping threshold value for the cell state. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01106">Descriptors.hpp:1106</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::LstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable cifg (coupled input & forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01110">Descriptors.hpp:1110</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a29fa293fffbf9c6f00cd75db1dc0a52a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">WorkloadData.hpp:753</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a6e9593869b82984de198fed27f72cdcf"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a></div><div class="ttdeci">const ConstTensorHandle * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">WorkloadData.hpp:754</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a299587d4f3fca029492700f3e2585bd8"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00745">WorkloadData.hpp:745</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00015">LayerTestResult.hpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00714">WorkloadData.hpp:714</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a4c27716f61bb68e8ea0bd4e8389ba01a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">WorkloadData.hpp:748</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a13060ebb89d2c21a7a5d897e99cccf72"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">armnn::IWorkloadFactory::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01541">WorkloadFactory.cpp:1541</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_adf8571dd1867ee91082bd005f94f2610"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">WorkloadData.hpp:746</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="ab8fb90e22b99c4d41ad3566fd5968829"></a> +<h2 class="memtitle"><span class="permalink"><a href="#ab8fb90e22b99c4d41ad3566fd5968829">◆ </a></span>UnidirectionalSequenceLstmLayerNoCifgWithPeepholeWithProjectionTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 3> UnidirectionalSequenceLstmLayerNoCifgWithPeepholeWithProjectionTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml#l00414">414</a> of file <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml">UnidirectionalSequenceLstmTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01541">IWorkloadFactory::CreateWorkload()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01104">LstmDescriptor::m_ActivationFunc</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00750">UnidirectionalSequenceLstmQueueDescriptor::m_CellToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00749">UnidirectionalSequenceLstmQueueDescriptor::m_CellToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00751">UnidirectionalSequenceLstmQueueDescriptor::m_CellToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01110">LstmDescriptor::m_CifgEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01106">LstmDescriptor::m_ClippingThresCell</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00752">UnidirectionalSequenceLstmQueueDescriptor::m_InputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00741">UnidirectionalSequenceLstmQueueDescriptor::m_InputToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01116">LstmDescriptor::m_LayerNormEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01112">LstmDescriptor::m_PeepholeEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00757">UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionBias</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01114">LstmDescriptor::m_ProjectionEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00756">UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00745">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01118">LstmDescriptor::m_TimeMajor</a>, and <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::UnidirectionalSequenceLstm</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00418"></a><span class="lineno"> 418</span> {</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 2;</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> timeSize = 3;</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = 5;</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputSize = 4;</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  <span class="keywordtype">unsigned</span> numUnits = 6;</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span> </div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({batchSize, timeSize, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> cellStateInTensorInfo({batchSize , numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputStateInTensorInfo({batchSize , outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({batchSize, timeSize, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span> </div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  <span class="keyword">const</span> std::vector<float> inputVector = { 1., 2., 3., 4., 5., 4.,</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  3., 2., 1., 2., 3., 4.,</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  5., 4., 3., 2., 1., 2.,</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  1., 2., 3., 4., 5., 4.};</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span> </div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  std::vector<float> cellStateInVector(batchSize * numUnits, 0.f);</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  std::vector<float> outputStateInVector(batchSize * outputSize, 0.f);</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> </div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  std::vector<float> actualOutput(outputTensorInfo.GetNumElements());</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span> </div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <span class="keyword">const</span> std::vector<float> expectedOutput = { -0.0135612f, -0.0263441f, 0.0314008f, -0.00883455f, 0.00763052f,</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  -0.00126877f, -0.0292959f, 0.0449957f, -0.00976195f, -0.00492338f,</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  -0.0175702f, -0.0431753f, 0.0597117f, -0.0169154f, 0.0142087f,</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  0.00472515f, -0.0196355f, 0.0342524f, -0.00407936f, -0.0253189f,</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  -0.00512944f, -0.0293754f, 0.0512771f, -0.0151874f, -0.0246433f,</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  -0.00744986f, -0.0345103f, 0.0450666f, -0.00944991f, 0.0127171f };</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span> </div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  std::unique_ptr<armnn::ITensorHandle> cellStateInHandle =</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(cellStateInTensorInfo);</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  std::unique_ptr<armnn::ITensorHandle> outputStateInHandle =</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputStateInTensorInfo);</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span> </div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  <a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a> data;</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span> </div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  AddInputToWorkload(data, info, outputStateInTensorInfo, outputStateInHandle.get());</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  AddInputToWorkload(data, info, cellStateInTensorInfo, cellStateInHandle.get());</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span> </div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo5({outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo6({numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo6x4({numUnits, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo6x5({numUnits, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo5x6({outputSize, numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span> </div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  std::vector<float> inputToInputWeights = { 0.021393683f, 0.06124551f, 0.046905167f, -0.014657677f,</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  -0.03149463f, 0.09171803f, 0.14647801f, 0.10797193f,</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  -0.0057968358f, 0.0019193048f, -0.2726754f, 0.10154029f,</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  -0.018539885f, 0.080349885f, -0.10262385f, -0.022599787f,</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  -0.09121155f, -0.008675967f, -0.045206103f, -0.0821282f,</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  -0.008045952f, 0.015478081f, 0.055217247f, 0.038719587f };</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span> </div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  std::vector<float> inputToForgetWeights = { -0.0018401089f, -0.004852237f, 0.03698424f, 0.014181704f,</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  0.028273236f, -0.016726194f, -0.05249759f, -0.10204261f,</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  0.00861066f, -0.040979505f, -0.009899187f, 0.01923892f,</div><div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  -0.028177269f, -0.08535103f, -0.14585495f, 0.10662567f,</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  -0.01909731f, -0.017883534f, -0.0047269356f, -0.045103323f,</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  0.0030784295f, 0.076784775f, 0.07463696f, 0.094531395f};</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span> </div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  std::vector<float> inputToCellWeights = { -0.04580283f, -0.09549462f, -0.032418985f, -0.06454633f,</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  -0.043528453f, 0.043018587f, -0.049152344f, -0.12418144f,</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  -0.078985475f, -0.07596889f, 0.019484362f, -0.11434962f,</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  -0.0074034138f, -0.06314844f, -0.092981495f, 0.0062155537f,</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  -0.025034338f, -0.0028890965f, 0.048929527f, 0.06235075f,</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  0.10665918f, -0.032036792f, -0.08505916f, -0.10843358f };</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span> </div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  std::vector<float> inputToOutputWeights = { -0.0998932f, -0.07201956f, -0.052803773f, -0.15629593f,</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  -0.15001918f, -0.07650751f, 0.02359855f, -0.075155355f,</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  -0.08037709f, -0.15093534f, 0.029517552f, -0.04751393f,</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  0.010350531f, -0.02664851f, -0.016839722f, -0.023121163f,</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  0.0077019283f, 0.012851257f, -0.05040649f, -0.0129761f,</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  -0.021737747f, -0.038305793f, -0.06870586f, -0.01481247f };</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span> </div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span>  std::vector<float> inputGateBias = { 0.02234832f, 0.14757581f, 0.18176508f,</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  0.10380666f, 0.053110216f, -0.06928846f };</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span> </div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  std::vector<float> forgetGateBias = { 0.035185695f, -0.042891346f, -0.03032477f,</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  0.23027696f, 0.11098921f, 0.08989442f };</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span> </div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  std::vector<float> cellBias = { -0.024379363f, 0.0055531194f, 0.23377132f,</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  0.033463873f, -0.1483596f, 0.029460307f };</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span> </div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  std::vector<float> outputGateBias = { 0.046159424f, -0.0012809046f, 0.03563469f,</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  0.12648113f, 0.027195795f, 0.35373217f };</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span> </div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  std::vector<float> recurrentToInputWeights = { -0.001374326f, -0.078856036f, 0.10672688f, 0.029162422f,</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  -0.11585556f, 0.02557986f, -0.13446963f, -0.035785314f,</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  -0.01244275f, 0.025961924f, -0.02337298f, -0.044228926f,</div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  -0.055839065f, -0.046598054f, -0.010546039f, -0.06900766f,</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  0.027239809f, 0.022582639f, -0.013296484f, -0.05459212f,</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  0.08981f, -0.045407712f, 0.08682226f, -0.06867011f,</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  -0.14390695f, -0.02916037f, 0.000996957f, 0.091420636f,</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  0.14283475f, -0.07390571f };</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span> </div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  std::vector<float> recurrentToCellWeights = { -0.037322544f, 0.018592842f, 0.0056175636f, -0.06253426f,</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  0.055647098f, -0.05713207f, -0.05626563f, 0.005559383f,</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  0.03375411f, -0.025757805f, -0.088049285f, 0.06017052f,</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  -0.06570978f, 0.007384076f, 0.035123326f, -0.07920549f,</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  0.053676967f, 0.044480428f, -0.07663568f, 0.0071805613f,</div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  0.08089997f, 0.05143358f, 0.038261272f, 0.03339287f,</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  -0.027673481f, 0.044746667f, 0.028349208f, 0.020090483f,</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  -0.019443132f, -0.030755889f };</div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span> </div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  std::vector<float> recurrentToForgetWeights = { -0.057784554f, -0.026057621f, -0.068447545f, -0.022581743f,</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  0.14811787f, 0.10826372f, 0.09471067f, 0.03987225f,</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  -0.0039523416f, 0.00030638507f, 0.053185795f, 0.10572994f,</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  0.08414449f, -0.022036452f, -0.00066928595f, -0.09203576f,</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  0.032950465f, -0.10985798f, -0.023809856f, 0.0021431844f,</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  -0.02196096f, -0.00326074f, 0.00058621005f, -0.074678116f,</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  -0.06193199f, 0.055729095f, 0.03736828f, 0.020123724f,</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  0.061878487f, -0.04729229f };</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span> </div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  std::vector<float> recurrentToOutputWeights = { 0.025825322f, -0.05813119f, 0.09495884f,</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  -0.045984812f,-0.01255415f, -0.0026479573f,</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  -0.08196161f, -0.054914974f, -0.0046604523f,</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  -0.029587349f, -0.044576716f, -0.07480124f,</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  -0.082868785f, 0.023254942f, 0.027502948f,</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  -0.0039728214f, -0.08683098f, -0.08116779f,</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  -0.014675607f, -0.037924774f, -0.023314456f,</div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  -0.007401714f, -0.09255757f, 0.029460307f,</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  -0.08829125f, -0.005139627f, -0.08989442f,</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  -0.0555066f, 0.13596267f, 0.025062224f };</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span> </div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  std::vector<float> cellToInputWeights = { 0.040369894f, 0.030746894f, 0.24704495f,</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  0.018586371f, -0.037586458f, -0.15312155f };</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span> </div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  std::vector<float> cellToForgetWeights = { -0.01998659f, -0.15568835f, -0.24248174f,</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  -0.012770197f, 0.041331276f, -0.072311886f };</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span> </div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  std::vector<float> cellToOutputWeights = { 0.08286371f, -0.08261836f, -0.51210177f,</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  0.002913762f, 0.17764764f, -0.5495371f };</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span> </div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  std::vector<float> projectionWeights = { -0.009802181f, 0.09401916f, 0.0717386f, -0.13895074f, 0.09641832f,</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  0.060420845f, 0.08539281f, 0.054285463f, 0.061395317f, 0.034448683f,</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  -0.042991187f, 0.019801661f, -0.16840284f, -0.015726732f, -0.23041931f,</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  -0.024478018f, -0.10959692f, -0.013875541f, 0.18600968f, -0.061274476f,</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  0.0138165f, -0.08160894f, -0.07661644f, 0.032372914f, 0.16169067f,</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  0.22465782f, -0.03993472f, -0.004017731f, 0.08633481f, -0.28869787f };</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span> </div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  std::vector<float> projectionBiasVector(outputSize, 0.f); <span class="comment">//{outputSize}</span></div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span> </div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToInputWeightsTensor(tensorInfo6x4);</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToForgetWeightsTensor(tensorInfo6x4);</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToCellWeightsTensor(tensorInfo6x4);</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToOutputWeightsTensor(tensorInfo6x4);</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToForgetWeightsTensor(tensorInfo6x5);</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToInputWeightsTensor(tensorInfo6x5);</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToCellWeightsTensor(tensorInfo6x5);</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToOutputWeightsTensor(tensorInfo6x5);</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToInputWeightsTensor(tensorInfo6);</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputGateBiasTensor(tensorInfo6);</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> forgetGateBiasTensor(tensorInfo6);</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellBiasTensor(tensorInfo6);</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> outputGateBiasTensor(tensorInfo6);</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToForgetWeightsTensor(tensorInfo6);</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToOutputWeightsTensor(tensorInfo6);</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> projectionWeightsTensor(tensorInfo5x6);</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> projectionBiasTensor(tensorInfo5);</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span> </div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToInputWeightsTensor, inputToInputWeights.data());</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToForgetWeightsTensor, inputToForgetWeights.data());</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToCellWeightsTensor, inputToCellWeights.data());</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToOutputWeightsTensor, inputToOutputWeights.data());</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToInputWeightsTensor, recurrentToInputWeights.data());</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToForgetWeightsTensor, recurrentToForgetWeights.data());</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToCellWeightsTensor, recurrentToCellWeights.data());</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToOutputWeightsTensor, recurrentToOutputWeights.data());</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToInputWeightsTensor, cellToInputWeights.data());</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputGateBiasTensor, inputGateBias.data());</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&forgetGateBiasTensor, forgetGateBias.data());</div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellBiasTensor, cellBias.data());</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&outputGateBiasTensor, outputGateBias.data());</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToForgetWeightsTensor, cellToForgetWeights.data());</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToOutputWeightsTensor, cellToOutputWeights.data());</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&projectionWeightsTensor, projectionWeights.data());</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&projectionBiasTensor, projectionBiasVector.data());</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span> </div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">m_InputToInputWeights</a> = &inputToInputWeightsTensor;</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">m_InputToForgetWeights</a> = &inputToForgetWeightsTensor;</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">m_InputToCellWeights</a> = &inputToCellWeightsTensor;</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">m_InputToOutputWeights</a> = &inputToOutputWeightsTensor;</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">m_RecurrentToInputWeights</a> = &recurrentToInputWeightsTensor;</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeightsTensor;</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">m_RecurrentToCellWeights</a> = &recurrentToCellWeightsTensor;</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeightsTensor;</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">m_CellToInputWeights</a> = &cellToInputWeightsTensor;</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">m_InputGateBias</a> = &inputGateBiasTensor;</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">m_ForgetGateBias</a> = &forgetGateBiasTensor;</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">m_CellBias</a> = &cellBiasTensor;</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">m_OutputGateBias</a> = &outputGateBiasTensor;</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">m_CellToForgetWeights</a> = &cellToForgetWeightsTensor;</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">m_CellToOutputWeights</a> = &cellToOutputWeightsTensor;</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">m_ProjectionWeights</a> = &projectionWeightsTensor;</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a> = &projectionBiasTensor;</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</span> </div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  <span class="comment">// Flags to set test configuration</span></div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = 4;</div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">m_TimeMajor</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a> = 10.0f;</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span> </div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span> </div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  std::unique_ptr<armnn::IWorkload> workload</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">CreateWorkload</a>(<a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a>, data, info);</div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  inputHandle->Allocate();</div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  outputStateInHandle->Allocate();</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  cellStateInHandle->Allocate();</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  outputHandle->Allocate();</div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span> </div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), inputVector.data());</div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(outputStateInHandle.get(), outputStateInVector.data());</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(cellStateInHandle.get(), cellStateInVector.data());</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span> </div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  workload->Execute();</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span> </div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a>(actualOutput.data(), outputHandle.get());</div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span> </div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  <span class="keywordflow">return</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 3></a>(actualOutput,</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  expectedOutput,</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  outputHandle->GetShape(),</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  outputTensorInfo.GetShape());</div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span> }</div><div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::LstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01114">Descriptors.hpp:1114</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a44eb7524badcca9b2073359e3814c98b"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00752">WorkloadData.hpp:752</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ac18c8b8b2039267d8282e91b4162d8aa"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">WorkloadData.hpp:747</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ab160eba2493d5fe52185c0986dcb190c"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00741">WorkloadData.hpp:741</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a3dcd10ca3ea2e132558b1e2814668c15"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">armnn::LstmDescriptor::m_TimeMajor</a></div><div class="ttdeci">bool m_TimeMajor</div><div class="ttdoc">Enable/disable time major. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01118">Descriptors.hpp:1118</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">WorkloadData.hpp:54</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_afaaca8c3f3a467d124bba44067d2afa8"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a></div><div class="ttdeci">void AllocateAndCopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00019">TensorCopyUtils.cpp:19</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a5ff4158b1b363b898d0da04c42d37ce0"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">WorkloadData.hpp:755</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ac668b31de6fb0f19d4c793d5ed3c3316"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ProjectionBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00757">WorkloadData.hpp:757</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a17ba1c8bcc71a55a95b2a3913f8cb203"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">WorkloadData.hpp:744</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a841439e3b8dc157a7368b19c9ecb7d03"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">WorkloadData.hpp:743</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aab77f54a037658ca9b2bf9cc8a1fadf1"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">WorkloadData.hpp:742</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a951b7c90b862138071a298065f16be61"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00749">WorkloadData.hpp:749</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a3ead2ef8da00b2709d561d85996fc513"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_ProjectionWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00756">WorkloadData.hpp:756</a></div></div> +<div class="ttc" id="classarmnn_1_1_scoped_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_tensor_handle_8hpp_source.xhtml#l00115">TensorHandle.hpp:115</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::LstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01112">Descriptors.hpp:1112</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ab5dfed8358e500ed523d78090ec78e88"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *mem, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ae1b07ed928036004bd257169e5aeeef4"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">armnn::LstmDescriptor::m_ActivationFunc</a></div><div class="ttdeci">uint32_t m_ActivationFunc</div><div class="ttdoc">The activation function to use. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01104">Descriptors.hpp:1104</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a531a3907ec13d3772370da88030191a5"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">armnn::LstmDescriptor::m_ClippingThresCell</a></div><div class="ttdeci">float m_ClippingThresCell</div><div class="ttdoc">Clipping threshold value for the cell state. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01106">Descriptors.hpp:1106</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::LstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable cifg (coupled input & forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01110">Descriptors.hpp:1110</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a29fa293fffbf9c6f00cd75db1dc0a52a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">WorkloadData.hpp:753</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a6e9593869b82984de198fed27f72cdcf"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a></div><div class="ttdeci">const ConstTensorHandle * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">WorkloadData.hpp:754</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a4a8ec49f130084445d44297549254780"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">armnn::LstmDescriptor::m_LayerNormEnabled</a></div><div class="ttdeci">bool m_LayerNormEnabled</div><div class="ttdoc">Enable/disable layer normalization. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01116">Descriptors.hpp:1116</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a299587d4f3fca029492700f3e2585bd8"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00745">WorkloadData.hpp:745</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00015">LayerTestResult.hpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a20c10fcb26657477377d07b7b1e13120"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00750">WorkloadData.hpp:750</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00714">WorkloadData.hpp:714</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a4c27716f61bb68e8ea0bd4e8389ba01a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">WorkloadData.hpp:748</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a13060ebb89d2c21a7a5d897e99cccf72"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">armnn::IWorkloadFactory::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01541">WorkloadFactory.cpp:1541</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_adf8571dd1867ee91082bd005f94f2610"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">WorkloadData.hpp:746</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aa09f7bdb9fd0d06b6386e412a4e72dd6"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00751">WorkloadData.hpp:751</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="adf8faacc3aacfa0b1342d78cfe1b61fe"></a> +<h2 class="memtitle"><span class="permalink"><a href="#adf8faacc3aacfa0b1342d78cfe1b61fe">◆ </a></span>UnidirectionalSequenceLstmLayerNoCifgWithPeepholeWithProjectionWithLayerNormTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 3> UnidirectionalSequenceLstmLayerNoCifgWithPeepholeWithProjectionWithLayerNormTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml#l00650">650</a> of file <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml">UnidirectionalSequenceLstmTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01541">IWorkloadFactory::CreateWorkload()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01104">LstmDescriptor::m_ActivationFunc</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00760">UnidirectionalSequenceLstmQueueDescriptor::m_CellLayerNormWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00750">UnidirectionalSequenceLstmQueueDescriptor::m_CellToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00749">UnidirectionalSequenceLstmQueueDescriptor::m_CellToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00751">UnidirectionalSequenceLstmQueueDescriptor::m_CellToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01110">LstmDescriptor::m_CifgEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01106">LstmDescriptor::m_ClippingThresCell</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00759">UnidirectionalSequenceLstmQueueDescriptor::m_ForgetLayerNormWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00752">UnidirectionalSequenceLstmQueueDescriptor::m_InputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00758">UnidirectionalSequenceLstmQueueDescriptor::m_InputLayerNormWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00741">UnidirectionalSequenceLstmQueueDescriptor::m_InputToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01116">LstmDescriptor::m_LayerNormEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00761">UnidirectionalSequenceLstmQueueDescriptor::m_OutputLayerNormWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01112">LstmDescriptor::m_PeepholeEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00757">UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionBias</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01114">LstmDescriptor::m_ProjectionEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00756">UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00745">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToInputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01118">LstmDescriptor::m_TimeMajor</a>, and <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::UnidirectionalSequenceLstm</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00654"></a><span class="lineno"> 654</span> {</div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 3;</div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> timeSize = 2;</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = 4;</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputSize = 3;</div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  <span class="keywordtype">unsigned</span> numUnits = 5;</div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span> </div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({batchSize, timeSize, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> cellStateInTensorInfo({batchSize , numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputStateInTensorInfo({batchSize , outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({batchSize, timeSize, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span> </div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  <span class="keyword">const</span> std::vector<float> inputVector = { 1., 2., 3., 4., 5., 4.,</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  3., 2., 1., 2., 3., 4.,</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  5., 4., 3., 2., 1., 2. };</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span> </div><div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  std::vector<float> cellStateInVector(batchSize * numUnits, 0.f);</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  std::vector<float> outputStateInVector(batchSize * outputSize, 0.f);</div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span> </div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  std::vector<float> actualOutput(outputTensorInfo.GetNumElements());</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span> </div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  <span class="keyword">const</span> std::vector<float> expectedOutput = { 0.0642256f, 0.0343966f, 0.184122f, 0.114717f,</div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span>  0.11458f, 0.0407109f, 0.300327f, 0.174301f,</div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  0.0864761f, 0.0362912f, 0.178635f, 0.115689f,</div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  0.108008f, 0.0386623f, 0.273471f, 0.167115f,</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  0.0859545f, 0.0331481f, 0.186051f, 0.11888f,</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  0.106649f, 0.0276847f, 0.229863f, 0.166958f };</div><div class="line"><a name="l00682"></a><span class="lineno"> 682</span> </div><div class="line"><a name="l00683"></a><span class="lineno"> 683</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  std::unique_ptr<armnn::ITensorHandle> cellStateInHandle =</div><div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(cellStateInTensorInfo);</div><div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  std::unique_ptr<armnn::ITensorHandle> outputStateInHandle =</div><div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputStateInTensorInfo);</div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span> </div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span> </div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  <a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a> data;</div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span> </div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  AddInputToWorkload(data, info, outputStateInTensorInfo, outputStateInHandle.get());</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  AddInputToWorkload(data, info, cellStateInTensorInfo, cellStateInHandle.get());</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span> </div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span> </div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo4({outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo5({numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo5x3({numUnits, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo5x4({numUnits, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo4x5({outputSize, numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span> </div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  std::vector<float> inputToInputWeights = { -0.49536117f, -0.0556083915f, -0.102400711f,</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  -0.117484632f, 0.3298470976f, -0.1179017122f,</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  0.214305695f, 0.42135173085f, 0.003878414626f,</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  -0.348303917f, -0.1881275477f, 0.0343011027f,</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  -0.38837709614f, -0.05636804124f, 0.4259087456f};</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span> </div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  std::vector<float> inputToForgetWeights = { 0.2415594226f, 0.15400093799f, 0.4566498398f,</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  -0.3810434485f, 0.268383264f, -0.009807467424f,</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  -0.3522925403f, -0.24275735512f, -0.28344226125f,</div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  0.13512269116f, -0.4932442977f, -0.10039821991f,</div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  0.2726137042f, 0.09216640889f, -0.06551410215f};</div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span> </div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  std::vector<float> inputToCellWeights = { -0.2504855627f, 0.184490025045f, -0.2480507493f,</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  0.386399507f, -0.259465157985f, -0.16545993089f,</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  -0.4230232555f, 0.341664791103f, -0.18127849691f,</div><div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  -0.2277662414f, -0.55275535589f, 0.34184026718f,</div><div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  0.3954237699f, -0.19407111404f, 0.30412107706f};</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span> </div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  std::vector<float> inputToOutputWeights = { 0.2303854227f, 0.5218806862f, -0.4865379333f,</div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  0.53969591851f, 0.23393625035f, -0.27140527306f,</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  0.50009280443f, 0.07511717046f, 0.3998299249f,</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  -0.51717478049f, 0.1889653282f, -0.367323637f,</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  -0.12584099173f, -0.12319286912f, 0.2407919466f};</div><div class="line"><a name="l00729"></a><span class="lineno"> 729</span> </div><div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  std::vector<float> inputGateBias{ 0.03f, 0.15f, 0.22f, 0.38f, 0.05f };</div><div class="line"><a name="l00731"></a><span class="lineno"> 731</span>  std::vector<float> forgetGateBias{ 0.1f, -0.3f, -0.2f, 0.1f, 0.4f };</div><div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  std::vector<float> cellBias{ -0.05f, 0.72f, 0.25f, 0.08f, 0.1f };</div><div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  std::vector<float> outputGateBias{ 0.05f, -0.01f, 0.2f, 0.1f, -0.2f };</div><div class="line"><a name="l00734"></a><span class="lineno"> 734</span> </div><div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  std::vector<float> recurrentToInputWeights = { -0.128009796112f, 0.1995525098f, -0.07745539397f, 0.1558421701f,</div><div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  -0.265254765766f, -0.38837709614f, -0.05636804124f, 0.4259087456f,</div><div class="line"><a name="l00737"></a><span class="lineno"> 737</span>  0.17628988623f, 0.3877420127f, 0.53300309181f, -0.0959980934f,</div><div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  0.00302857416f, 0.3266998827f, -0.142509296562f, -0.04433270756f,</div><div class="line"><a name="l00739"></a><span class="lineno"> 739</span>  0.54066205f, -0.32668582f, -0.43562764f, -0.56094903f };</div><div class="line"><a name="l00740"></a><span class="lineno"> 740</span> </div><div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  std::vector<float> recurrentToForgetWeights = { -0.09499983487f, -0.08814888417f, -0.04834804721f, 0.1516668247f,</div><div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  -0.3967529535f, -0.06463699788f, 0.4952811002f, 0.003274492938f,</div><div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  -0.0968840941f, 0.17928104102f, 0.0031281141592f, -0.3387276584f,</div><div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  -0.3587934076f, 0.06705895066f, 0.22463923692f, 0.1961955726f,</div><div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  0.01841056f, -0.32764608f, -0.33027974f, -0.10826075f };</div><div class="line"><a name="l00746"></a><span class="lineno"> 746</span> </div><div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  std::vector<float> recurrentToCellWeights = { -0.21938985582f, -0.3023648226f, -0.1170005202f, -0.3509177422f,</div><div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  -0.4286288613f, 0.2726137042f, 0.09216640889f, -0.06551410215f,</div><div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  0.20453298098f, 0.2393476665f, 0.11846517771f, 0.2630801796f,</div><div class="line"><a name="l00750"></a><span class="lineno"> 750</span>  0.3954237699f, -0.19407111404f, 0.30412107706f, -0.27342408554f,</div><div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  0.19069612f, -0.03026325f, -0.54532051f, 0.33003211f };</div><div class="line"><a name="l00752"></a><span class="lineno"> 752</span> </div><div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  std::vector<float> recurrentToOutputWeights = { -0.32921677827f, 0.32624614238f, -0.1388191282f, -0.17879831790f,</div><div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  -0.15185534954f, -0.16918526583f, -0.10087361183f, -0.5436913968f,</div><div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  0.016758225858f, 0.30454617738f, -0.41493862867f, -0.005565764375f,</div><div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  -0.12584099173f, -0.12319286912f, 0.2407919466f, -0.08879069983f,</div><div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  0.11178309f, 0.09481031f, -0.26424935f, 0.46261835f };</div><div class="line"><a name="l00758"></a><span class="lineno"> 758</span> </div><div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  std::vector<float> cellToInputWeights { 0.05f, 0.1f, 0.25f, 0.15f, -0.02f };</div><div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  std::vector<float> cellToForgetWeights { -0.02f, -0.15f, -0.25f, -0.03f, 0.15f };</div><div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  std::vector<float> cellToOutputWeights { 0.1f, -0.1f, -0.5f, 0.05f, 0.01f };</div><div class="line"><a name="l00762"></a><span class="lineno"> 762</span> </div><div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  std::vector<float> projectionWeights{ -0.1f, 0.2f, 0.01f, -0.2f,</div><div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  0.1f, 0.5f, 0.3f, 0.08f,</div><div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  0.07f, 0.2f, -0.4f, 0.2f,</div><div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  0.5f, -0.4f, 0.3f, -0.2f,</div><div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  0.3f, 0.08f, -0.07f, 0.2f};</div><div class="line"><a name="l00768"></a><span class="lineno"> 768</span> </div><div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  std::vector<float> projectionBiasVector(outputSize, 0.f); <span class="comment">//{outputSize}</span></div><div class="line"><a name="l00770"></a><span class="lineno"> 770</span> </div><div class="line"><a name="l00771"></a><span class="lineno"> 771</span>  std::vector<float> inputLayerNormWeights{ 0.1f, 0.2f, 0.3f, 0.5f, 0.8f };</div><div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  std::vector<float> forgetLayerNormWeights{ 0.1f, 0.2f, 0.3f, 0.5f, 0.2f };</div><div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  std::vector<float> cellLayerNormWeights{ 0.7f, 0.2f, 0.3f, 0.8f, 0.5f };</div><div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  std::vector<float> outputLayerNormWeights{ 0.6f, 0.2f, 0.2f, 0.5f, 0.1f };</div><div class="line"><a name="l00775"></a><span class="lineno"> 775</span> </div><div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToInputWeightsTensor(tensorInfo5x3);</div><div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToForgetWeightsTensor(tensorInfo5x3);</div><div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToCellWeightsTensor(tensorInfo5x3);</div><div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToOutputWeightsTensor(tensorInfo5x3);</div><div class="line"><a name="l00780"></a><span class="lineno"> 780</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToForgetWeightsTensor(tensorInfo5x4);</div><div class="line"><a name="l00781"></a><span class="lineno"> 781</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToInputWeightsTensor(tensorInfo5x4);</div><div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToCellWeightsTensor(tensorInfo5x4);</div><div class="line"><a name="l00783"></a><span class="lineno"> 783</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToOutputWeightsTensor(tensorInfo5x4);</div><div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToInputWeightsTensor(tensorInfo5);</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputGateBiasTensor(tensorInfo5);</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> forgetGateBiasTensor(tensorInfo5);</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellBiasTensor(tensorInfo5);</div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> outputGateBiasTensor(tensorInfo5);</div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToForgetWeightsTensor(tensorInfo5);</div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToOutputWeightsTensor(tensorInfo5);</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> projectionWeightsTensor(tensorInfo4x5);</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> projectionBiasTensor(tensorInfo4);</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span> </div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputLayerNormWeightsTensor(tensorInfo5);</div><div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> forgetLayerNormWeightsTensor(tensorInfo5);</div><div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellLayerNormWeightsTensor(tensorInfo5);</div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> outputLayerNormWeightsTensor(tensorInfo5);</div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span> </div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToInputWeightsTensor, inputToInputWeights.data());</div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToForgetWeightsTensor, inputToForgetWeights.data());</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToCellWeightsTensor, inputToCellWeights.data());</div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToOutputWeightsTensor, inputToOutputWeights.data());</div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToInputWeightsTensor, recurrentToInputWeights.data());</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToForgetWeightsTensor, recurrentToForgetWeights.data());</div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToCellWeightsTensor, recurrentToCellWeights.data());</div><div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToOutputWeightsTensor, recurrentToOutputWeights.data());</div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToInputWeightsTensor, cellToInputWeights.data());</div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputGateBiasTensor, inputGateBias.data());</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&forgetGateBiasTensor, forgetGateBias.data());</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellBiasTensor, cellBias.data());</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&outputGateBiasTensor, outputGateBias.data());</div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToForgetWeightsTensor, cellToForgetWeights.data());</div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToOutputWeightsTensor, cellToOutputWeights.data());</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&projectionWeightsTensor, projectionWeights.data());</div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&projectionBiasTensor, projectionBiasVector.data());</div><div class="line"><a name="l00816"></a><span class="lineno"> 816</span> </div><div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputLayerNormWeightsTensor, inputLayerNormWeights.data());</div><div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&forgetLayerNormWeightsTensor, forgetLayerNormWeights.data());</div><div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellLayerNormWeightsTensor, cellLayerNormWeights.data());</div><div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&outputLayerNormWeightsTensor, outputLayerNormWeights.data());</div><div class="line"><a name="l00821"></a><span class="lineno"> 821</span> </div><div class="line"><a name="l00822"></a><span class="lineno"> 822</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">m_InputToInputWeights</a> = &inputToInputWeightsTensor;</div><div class="line"><a name="l00823"></a><span class="lineno"> 823</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">m_InputToForgetWeights</a> = &inputToForgetWeightsTensor;</div><div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">m_InputToCellWeights</a> = &inputToCellWeightsTensor;</div><div class="line"><a name="l00825"></a><span class="lineno"> 825</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">m_InputToOutputWeights</a> = &inputToOutputWeightsTensor;</div><div class="line"><a name="l00826"></a><span class="lineno"> 826</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">m_RecurrentToInputWeights</a> = &recurrentToInputWeightsTensor;</div><div class="line"><a name="l00827"></a><span class="lineno"> 827</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeightsTensor;</div><div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">m_RecurrentToCellWeights</a> = &recurrentToCellWeightsTensor;</div><div class="line"><a name="l00829"></a><span class="lineno"> 829</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeightsTensor;</div><div class="line"><a name="l00830"></a><span class="lineno"> 830</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">m_CellToInputWeights</a> = &cellToInputWeightsTensor;</div><div class="line"><a name="l00831"></a><span class="lineno"> 831</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">m_InputGateBias</a> = &inputGateBiasTensor;</div><div class="line"><a name="l00832"></a><span class="lineno"> 832</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">m_ForgetGateBias</a> = &forgetGateBiasTensor;</div><div class="line"><a name="l00833"></a><span class="lineno"> 833</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">m_CellBias</a> = &cellBiasTensor;</div><div class="line"><a name="l00834"></a><span class="lineno"> 834</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">m_OutputGateBias</a> = &outputGateBiasTensor;</div><div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">m_CellToForgetWeights</a> = &cellToForgetWeightsTensor;</div><div class="line"><a name="l00836"></a><span class="lineno"> 836</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">m_CellToOutputWeights</a> = &cellToOutputWeightsTensor;</div><div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">m_ProjectionWeights</a> = &projectionWeightsTensor;</div><div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">m_ProjectionBias</a> = &projectionBiasTensor;</div><div class="line"><a name="l00839"></a><span class="lineno"> 839</span> </div><div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a1dbad32cad5c0437e1272f59fedf52ea">m_InputLayerNormWeights</a> = &inputLayerNormWeightsTensor;</div><div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ad9442e26aa79f896da5f404ab825a9c8">m_ForgetLayerNormWeights</a> = &forgetLayerNormWeightsTensor;</div><div class="line"><a name="l00842"></a><span class="lineno"> 842</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aeef6f1ac3efad8ec8b0a7118652b64c9">m_CellLayerNormWeights</a> = &cellLayerNormWeightsTensor;</div><div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a0e0f66bd03c88f3d2dc666f581d3cf12">m_OutputLayerNormWeights</a> = &outputLayerNormWeightsTensor;</div><div class="line"><a name="l00844"></a><span class="lineno"> 844</span> </div><div class="line"><a name="l00845"></a><span class="lineno"> 845</span>  <span class="comment">// Flags to set test configuration</span></div><div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = 4;</div><div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">m_LayerNormEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">m_TimeMajor</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a> = 10.0f;</div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span> </div><div class="line"><a name="l00854"></a><span class="lineno"> 854</span>  std::unique_ptr<armnn::IWorkload> workload</div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">CreateWorkload</a>(<a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a>, data, info);</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  inputHandle->Allocate();</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  outputStateInHandle->Allocate();</div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  cellStateInHandle->Allocate();</div><div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  outputHandle->Allocate();</div><div class="line"><a name="l00860"></a><span class="lineno"> 860</span> </div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), inputVector.data());</div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(outputStateInHandle.get(), outputStateInVector.data());</div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(cellStateInHandle.get(), cellStateInVector.data());</div><div class="line"><a name="l00864"></a><span class="lineno"> 864</span> </div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  workload->Execute();</div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span> </div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a>(actualOutput.data(), outputHandle.get());</div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span> </div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  <span class="keywordflow">return</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 3></a>(actualOutput,</div><div class="line"><a name="l00870"></a><span class="lineno"> 870</span>  expectedOutput,</div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  outputHandle->GetShape(),</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  outputTensorInfo.GetShape());</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span> }</div><div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::LstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01114">Descriptors.hpp:1114</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a44eb7524badcca9b2073359e3814c98b"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a44eb7524badcca9b2073359e3814c98b">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_InputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00752">WorkloadData.hpp:752</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ac18c8b8b2039267d8282e91b4162d8aa"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">WorkloadData.hpp:747</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ab160eba2493d5fe52185c0986dcb190c"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ab160eba2493d5fe52185c0986dcb190c">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00741">WorkloadData.hpp:741</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a3dcd10ca3ea2e132558b1e2814668c15"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">armnn::LstmDescriptor::m_TimeMajor</a></div><div class="ttdeci">bool m_TimeMajor</div><div class="ttdoc">Enable/disable time major. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01118">Descriptors.hpp:1118</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">WorkloadData.hpp:54</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_afaaca8c3f3a467d124bba44067d2afa8"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a></div><div class="ttdeci">void AllocateAndCopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00019">TensorCopyUtils.cpp:19</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a5ff4158b1b363b898d0da04c42d37ce0"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">WorkloadData.hpp:755</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ac668b31de6fb0f19d4c793d5ed3c3316"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac668b31de6fb0f19d4c793d5ed3c3316">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ProjectionBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00757">WorkloadData.hpp:757</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a17ba1c8bcc71a55a95b2a3913f8cb203"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">WorkloadData.hpp:744</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a841439e3b8dc157a7368b19c9ecb7d03"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">WorkloadData.hpp:743</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aab77f54a037658ca9b2bf9cc8a1fadf1"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">WorkloadData.hpp:742</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aeef6f1ac3efad8ec8b0a7118652b64c9"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aeef6f1ac3efad8ec8b0a7118652b64c9">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00760">WorkloadData.hpp:760</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a951b7c90b862138071a298065f16be61"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a951b7c90b862138071a298065f16be61">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00749">WorkloadData.hpp:749</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a3ead2ef8da00b2709d561d85996fc513"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a3ead2ef8da00b2709d561d85996fc513">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ProjectionWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_ProjectionWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00756">WorkloadData.hpp:756</a></div></div> +<div class="ttc" id="classarmnn_1_1_scoped_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_tensor_handle_8hpp_source.xhtml#l00115">TensorHandle.hpp:115</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::LstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01112">Descriptors.hpp:1112</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ab5dfed8358e500ed523d78090ec78e88"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *mem, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ae1b07ed928036004bd257169e5aeeef4"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">armnn::LstmDescriptor::m_ActivationFunc</a></div><div class="ttdeci">uint32_t m_ActivationFunc</div><div class="ttdoc">The activation function to use. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01104">Descriptors.hpp:1104</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a531a3907ec13d3772370da88030191a5"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">armnn::LstmDescriptor::m_ClippingThresCell</a></div><div class="ttdeci">float m_ClippingThresCell</div><div class="ttdoc">Clipping threshold value for the cell state. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01106">Descriptors.hpp:1106</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ad9442e26aa79f896da5f404ab825a9c8"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ad9442e26aa79f896da5f404ab825a9c8">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ForgetLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00759">WorkloadData.hpp:759</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a0e0f66bd03c88f3d2dc666f581d3cf12"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a0e0f66bd03c88f3d2dc666f581d3cf12">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_OutputLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00761">WorkloadData.hpp:761</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::LstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable cifg (coupled input & forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01110">Descriptors.hpp:1110</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a29fa293fffbf9c6f00cd75db1dc0a52a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">WorkloadData.hpp:753</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a6e9593869b82984de198fed27f72cdcf"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a></div><div class="ttdeci">const ConstTensorHandle * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">WorkloadData.hpp:754</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a4a8ec49f130084445d44297549254780"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a4a8ec49f130084445d44297549254780">armnn::LstmDescriptor::m_LayerNormEnabled</a></div><div class="ttdeci">bool m_LayerNormEnabled</div><div class="ttdoc">Enable/disable layer normalization. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01116">Descriptors.hpp:1116</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a299587d4f3fca029492700f3e2585bd8"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a299587d4f3fca029492700f3e2585bd8">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToInputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToInputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00745">WorkloadData.hpp:745</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00015">LayerTestResult.hpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a20c10fcb26657477377d07b7b1e13120"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00750">WorkloadData.hpp:750</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00714">WorkloadData.hpp:714</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a4c27716f61bb68e8ea0bd4e8389ba01a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">WorkloadData.hpp:748</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a13060ebb89d2c21a7a5d897e99cccf72"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">armnn::IWorkloadFactory::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01541">WorkloadFactory.cpp:1541</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_adf8571dd1867ee91082bd005f94f2610"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">WorkloadData.hpp:746</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aa09f7bdb9fd0d06b6386e412a4e72dd6"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00751">WorkloadData.hpp:751</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a1dbad32cad5c0437e1272f59fedf52ea"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a1dbad32cad5c0437e1272f59fedf52ea">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputLayerNormWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputLayerNormWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00758">WorkloadData.hpp:758</a></div></div> +</div><!-- fragment --> +</div> +</div> +<a id="a5c36dcbd8e95871d57e8a50222a02494"></a> +<h2 class="memtitle"><span class="permalink"><a href="#a5c36dcbd8e95871d57e8a50222a02494">◆ </a></span>UnidirectionalSequenceLstmWithCifgWithPeepholeNoProjectionTest()</h2> + +<div class="memitem"> +<div class="memproto"> + <table class="memname"> + <tr> + <td class="memname"><a class="el" href="struct_layer_test_result.xhtml">LayerTestResult</a><float, 3> UnidirectionalSequenceLstmWithCifgWithPeepholeNoProjectionTest </td> + <td>(</td> + <td class="paramtype"><a class="el" href="classarmnn_1_1_i_workload_factory.xhtml">armnn::IWorkloadFactory</a> & </td> + <td class="paramname"><em>workloadFactory</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_backend_internal.xhtml#a693b40e6b94e958836aeb0410ca186bd">armnn::IBackendInternal::IMemoryManagerSharedPtr</a> & </td> + <td class="paramname"><em>memoryManager</em>, </td> + </tr> + <tr> + <td class="paramkey"></td> + <td></td> + <td class="paramtype">const <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml">armnn::ITensorHandleFactory</a> & </td> + <td class="paramname"><em>tensorHandleFactory</em> </td> + </tr> + <tr> + <td></td> + <td>)</td> + <td></td><td></td> + </tr> + </table> +</div><div class="memdoc"> + +<p class="definition">Definition at line <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml#l00875">875</a> of file <a class="el" href="_unidirectional_sequence_lstm_test_impl_8cpp_source.xhtml">UnidirectionalSequenceLstmTestImpl.cpp</a>.</p> + +<p class="reference">References <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00019">AllocateAndCopyDataToITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00014">CopyDataFromITensorHandle()</a>, <a class="el" href="_tensor_copy_utils_8cpp_source.xhtml#l00009">CopyDataToITensorHandle()</a>, <a class="el" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">ITensorHandleFactory::CreateTensorHandle()</a>, <a class="el" href="_workload_factory_8cpp_source.xhtml#l01541">IWorkloadFactory::CreateWorkload()</a>, <a class="el" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::Float32</a>, <a class="el" href="_ignore_unused_8hpp_source.xhtml#l00014">armnn::IgnoreUnused()</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01104">LstmDescriptor::m_ActivationFunc</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00750">UnidirectionalSequenceLstmQueueDescriptor::m_CellToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00751">UnidirectionalSequenceLstmQueueDescriptor::m_CellToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01110">LstmDescriptor::m_CifgEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01106">LstmDescriptor::m_ClippingThresCell</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01108">LstmDescriptor::m_ClippingThresProj</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">QueueDescriptorWithParameters< LayerDescriptor >::m_Parameters</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01112">LstmDescriptor::m_PeepholeEnabled</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01114">LstmDescriptor::m_ProjectionEnabled</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a>, <a class="el" href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a>, <a class="el" href="_descriptors_8hpp_source.xhtml#l01118">LstmDescriptor::m_TimeMajor</a>, and <a class="el" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::UnidirectionalSequenceLstm</a>.</p> + +<p class="reference">Referenced by <a class="el" href="_ref_layer_tests_8cpp_source.xhtml#l00014">TEST_SUITE()</a>.</p> +<div class="fragment"><div class="line"><a name="l00879"></a><span class="lineno"> 879</span> {</div><div class="line"><a name="l00880"></a><span class="lineno"> 880</span>  <a class="code" href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">IgnoreUnused</a>(memoryManager);</div><div class="line"><a name="l00881"></a><span class="lineno"> 881</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batchSize = 3;</div><div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> timeSize = 2;</div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> inputSize = 3;</div><div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> outputSize = 4;</div><div class="line"><a name="l00885"></a><span class="lineno"> 885</span>  <span class="keywordtype">unsigned</span> numUnits = outputSize;</div><div class="line"><a name="l00886"></a><span class="lineno"> 886</span> </div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> inputTensorInfo({batchSize, timeSize, inputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> cellStateInTensorInfo({batchSize, numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00889"></a><span class="lineno"> 889</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputStateInTensorInfo({batchSize, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00890"></a><span class="lineno"> 890</span> </div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> outputTensorInfo({batchSize, timeSize, outputSize}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span> </div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  std::vector<float> inputVector = { 1., 2., 3., 4., 5., 4.,</div><div class="line"><a name="l00894"></a><span class="lineno"> 894</span>  3., 2., 1., 2., 3., 4.,</div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  5., 4., 3., 2., 1., 2. };</div><div class="line"><a name="l00896"></a><span class="lineno"> 896</span> </div><div class="line"><a name="l00897"></a><span class="lineno"> 897</span>  std::vector<float> cellStateInVector(batchSize * numUnits, 0.f);</div><div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  std::vector<float> outputStateInVector(batchSize * outputSize, 0.f);</div><div class="line"><a name="l00899"></a><span class="lineno"> 899</span> </div><div class="line"><a name="l00900"></a><span class="lineno"> 900</span>  std::vector<float> actualOutput(outputTensorInfo.GetNumElements());</div><div class="line"><a name="l00901"></a><span class="lineno"> 901</span> </div><div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  std::vector<float> outputVector = { -0.0129257f, -0.070531f, -0.153508f, -0.0392391f,</div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  -0.0300169f, -0.195717f, -0.528679f, -0.0818106f,</div><div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  -0.0332748f, 0.155429f, -0.353966f, -0.0801505f,</div><div class="line"><a name="l00905"></a><span class="lineno"> 905</span>  -0.032312f, -0.0407911f, -0.435053f, -0.0932317f,</div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  -0.0108233f, 0.165584f, -0.640424f, -0.0447535f,</div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  -0.031675f, 0.125987f, -0.526695f, -0.110093f };</div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span> </div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(inputTensorInfo);</div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  std::unique_ptr<armnn::ITensorHandle> cellStateInHandle =</div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(cellStateInTensorInfo);</div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span>  std::unique_ptr<armnn::ITensorHandle> outputStateInHandle =</div><div class="line"><a name="l00913"></a><span class="lineno"> 913</span>  tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputStateInTensorInfo);</div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span> </div><div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.<a class="code" href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">CreateTensorHandle</a>(outputTensorInfo);</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span> </div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  <a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a> data;</div><div class="line"><a name="l00918"></a><span class="lineno"> 918</span>  <a class="code" href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a> <a class="code" href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">info</a>;</div><div class="line"><a name="l00919"></a><span class="lineno"> 919</span> </div><div class="line"><a name="l00920"></a><span class="lineno"> 920</span>  AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());</div><div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  AddInputToWorkload(data, info, outputStateInTensorInfo, outputStateInHandle.get());</div><div class="line"><a name="l00922"></a><span class="lineno"> 922</span>  AddInputToWorkload(data, info, cellStateInTensorInfo, cellStateInHandle.get());</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span> </div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());</div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span> </div><div class="line"><a name="l00926"></a><span class="lineno"> 926</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo4({numUnits}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00927"></a><span class="lineno"> 927</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo12({numUnits, 3}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  <a class="code" href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a> tensorInfo16({numUnits, 4}, <a class="code" href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a>);</div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span> </div><div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  std::vector<float> inputToForgetWeights = { 0.2415594226f, 0.15400093799f, 0.4566498398f,</div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  -0.3810434485f, 0.268383264f, -0.009807467424f,</div><div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  -0.3522925403f, -0.24275735512f, -0.28344226125f,</div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span>  0.13512269116f, -0.4932442977f, -0.10039821991f };</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span> </div><div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  std::vector<float> inputToCellWeights = { -0.2504855627f, 0.184490025045f, -0.2480507493f,</div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  0.386399507f, -0.259465157985f, -0.16545993089f,</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span>  -0.4230232555f, 0.341664791103f, -0.18127849691f,</div><div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  -0.2277662414f, -0.55275535589f, 0.34184026718f };</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span> </div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  std::vector<float> inputToOutputWeights = { 0.2303854227f, 0.5218806862f, -0.4865379333f,</div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span>  0.53969591851f, 0.23393625035f, -0.27140527306f,</div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  0.50009280443f, 0.07511717046f, 0.3998299249f,</div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  -0.51717478049f, 0.1889653282f, -0.367323637f };</div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span> </div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  std::vector<float> recurrentToForgetWeights = { -0.09499983487f, -0.08814888417f, -0.04834804721f, 0.1516668247f,</div><div class="line"><a name="l00946"></a><span class="lineno"> 946</span>  -0.3967529535f, -0.06463699788f, 0.4952811002f, 0.003274492938f,</div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  -0.0968840941f, 0.17928104102f, 0.0031281141592f, -0.3387276584f,</div><div class="line"><a name="l00948"></a><span class="lineno"> 948</span>  -0.3587934076f, 0.06705895066f, 0.22463923692f, 0.1961955726f };</div><div class="line"><a name="l00949"></a><span class="lineno"> 949</span> </div><div class="line"><a name="l00950"></a><span class="lineno"> 950</span>  std::vector<float> recurrentToCellWeights = { -0.21938985582f, -0.3023648226f, -0.1170005202f, -0.3509177422f,</div><div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  -0.4286288613f, 0.2726137042f, 0.09216640889f, -0.06551410215f,</div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span>  0.20453298098f, 0.2393476665f, 0.11846517771f, 0.2630801796f,</div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  0.3954237699f, -0.19407111404f, 0.30412107706f, -0.27342408554f };</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</span> </div><div class="line"><a name="l00955"></a><span class="lineno"> 955</span>  std::vector<float> recurrentToOutputWeights = { -0.32921677827f, 0.32624614238f, -0.1388191282f, -0.17879831790f,</div><div class="line"><a name="l00956"></a><span class="lineno"> 956</span>  -0.15185534954f, -0.16918526583f, -0.10087361183f, -0.5436913968f,</div><div class="line"><a name="l00957"></a><span class="lineno"> 957</span>  0.016758225858f, 0.30454617738f, -0.41493862867f, -0.005565764375f,</div><div class="line"><a name="l00958"></a><span class="lineno"> 958</span>  -0.12584099173f, -0.12319286912f, 0.2407919466f, -0.08879069983f };</div><div class="line"><a name="l00959"></a><span class="lineno"> 959</span> </div><div class="line"><a name="l00960"></a><span class="lineno"> 960</span>  std::vector<float> cellToForgetWeights{ 0.47485286f, -0.51955009f, -0.24458408f, 0.31544167f };</div><div class="line"><a name="l00961"></a><span class="lineno"> 961</span> </div><div class="line"><a name="l00962"></a><span class="lineno"> 962</span>  std::vector<float> cellToOutputWeights{ -0.17135078f, 0.82760304f, 0.85573703f, -0.77109635f };</div><div class="line"><a name="l00963"></a><span class="lineno"> 963</span> </div><div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  std::vector<float> forgetGateBias = { 1., 1., 1., 1. };</div><div class="line"><a name="l00965"></a><span class="lineno"> 965</span> </div><div class="line"><a name="l00966"></a><span class="lineno"> 966</span>  std::vector<float> cellBias = { 0., 0., 0., 0. };</div><div class="line"><a name="l00967"></a><span class="lineno"> 967</span> </div><div class="line"><a name="l00968"></a><span class="lineno"> 968</span>  std::vector<float> outputGateBias = { 0., 0., 0., 0. };</div><div class="line"><a name="l00969"></a><span class="lineno"> 969</span> </div><div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToForgetWeightsTensor(tensorInfo12);</div><div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToCellWeightsTensor(tensorInfo12);</div><div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> inputToOutputWeightsTensor(tensorInfo12);</div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToForgetWeightsTensor(tensorInfo16);</div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToCellWeightsTensor(tensorInfo16);</div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> recurrentToOutputWeightsTensor(tensorInfo16);</div><div class="line"><a name="l00976"></a><span class="lineno"> 976</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToForgetWeightsTensor(tensorInfo4);</div><div class="line"><a name="l00977"></a><span class="lineno"> 977</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellToOutputWeightsTensor(tensorInfo4);</div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> forgetGateBiasTensor(tensorInfo4);</div><div class="line"><a name="l00979"></a><span class="lineno"> 979</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> cellBiasTensor(tensorInfo4);</div><div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  <a class="code" href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a> outputGateBiasTensor(tensorInfo4);</div><div class="line"><a name="l00981"></a><span class="lineno"> 981</span> </div><div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToForgetWeightsTensor, inputToForgetWeights.data());</div><div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToCellWeightsTensor, inputToCellWeights.data());</div><div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&inputToOutputWeightsTensor, inputToOutputWeights.data());</div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToForgetWeightsTensor, recurrentToForgetWeights.data());</div><div class="line"><a name="l00986"></a><span class="lineno"> 986</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToCellWeightsTensor, recurrentToCellWeights.data());</div><div class="line"><a name="l00987"></a><span class="lineno"> 987</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&recurrentToOutputWeightsTensor, recurrentToOutputWeights.data());</div><div class="line"><a name="l00988"></a><span class="lineno"> 988</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToForgetWeightsTensor, cellToForgetWeights.data());</div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellToOutputWeightsTensor, cellToOutputWeights.data());</div><div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&forgetGateBiasTensor, forgetGateBias.data());</div><div class="line"><a name="l00991"></a><span class="lineno"> 991</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&cellBiasTensor, cellBias.data());</div><div class="line"><a name="l00992"></a><span class="lineno"> 992</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a>(&outputGateBiasTensor, outputGateBias.data());</div><div class="line"><a name="l00993"></a><span class="lineno"> 993</span> </div><div class="line"><a name="l00994"></a><span class="lineno"> 994</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">m_InputToForgetWeights</a> = &inputToForgetWeightsTensor;</div><div class="line"><a name="l00995"></a><span class="lineno"> 995</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">m_InputToCellWeights</a> = &inputToCellWeightsTensor;</div><div class="line"><a name="l00996"></a><span class="lineno"> 996</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">m_InputToOutputWeights</a> = &inputToOutputWeightsTensor;</div><div class="line"><a name="l00997"></a><span class="lineno"> 997</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">m_RecurrentToForgetWeights</a> = &recurrentToForgetWeightsTensor;</div><div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">m_RecurrentToCellWeights</a> = &recurrentToCellWeightsTensor;</div><div class="line"><a name="l00999"></a><span class="lineno"> 999</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">m_RecurrentToOutputWeights</a> = &recurrentToOutputWeightsTensor;</div><div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">m_CellToForgetWeights</a> = &cellToForgetWeightsTensor;</div><div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">m_CellToOutputWeights</a> = &cellToOutputWeightsTensor;</div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">m_ForgetGateBias</a> = &forgetGateBiasTensor;</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">m_CellBias</a> = &cellBiasTensor;</div><div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>  data.<a class="code" href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">m_OutputGateBias</a> = &outputGateBiasTensor;</div><div class="line"><a name="l01005"></a><span class="lineno"> 1005</span> </div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>  <span class="comment">// Flags to set test configuration</span></div><div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">m_ClippingThresCell</a> = 10;</div><div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a86e88bef0df4df96df752b4b8955a3af">m_ClippingThresProj</a> = 0;</div><div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">m_ActivationFunc</a> = 4;</div><div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">m_CifgEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">m_PeepholeEnabled</a> = <span class="keyword">true</span>;</div><div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">m_ProjectionEnabled</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>  data.<a class="code" href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">m_Parameters</a>.<a class="code" href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">m_TimeMajor</a> = <span class="keyword">false</span>;</div><div class="line"><a name="l01014"></a><span class="lineno"> 1014</span> </div><div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>  std::unique_ptr<armnn::IWorkload> workload</div><div class="line"><a name="l01016"></a><span class="lineno"> 1016</span>  = workloadFactory.<a class="code" href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">CreateWorkload</a>(<a class="code" href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a>, data, info);</div><div class="line"><a name="l01017"></a><span class="lineno"> 1017</span>  inputHandle->Allocate();</div><div class="line"><a name="l01018"></a><span class="lineno"> 1018</span>  outputStateInHandle->Allocate();</div><div class="line"><a name="l01019"></a><span class="lineno"> 1019</span>  cellStateInHandle->Allocate();</div><div class="line"><a name="l01020"></a><span class="lineno"> 1020</span> </div><div class="line"><a name="l01021"></a><span class="lineno"> 1021</span>  outputHandle->Allocate();</div><div class="line"><a name="l01022"></a><span class="lineno"> 1022</span> </div><div class="line"><a name="l01023"></a><span class="lineno"> 1023</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(inputHandle.get(), inputVector.data());</div><div class="line"><a name="l01024"></a><span class="lineno"> 1024</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(outputStateInHandle.get(), outputStateInVector.data());</div><div class="line"><a name="l01025"></a><span class="lineno"> 1025</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a>(cellStateInHandle.get(), cellStateInVector.data());</div><div class="line"><a name="l01026"></a><span class="lineno"> 1026</span> </div><div class="line"><a name="l01027"></a><span class="lineno"> 1027</span>  workload->Execute();</div><div class="line"><a name="l01028"></a><span class="lineno"> 1028</span> </div><div class="line"><a name="l01029"></a><span class="lineno"> 1029</span>  <a class="code" href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a>(actualOutput.data(), outputHandle.get());</div><div class="line"><a name="l01030"></a><span class="lineno"> 1030</span> </div><div class="line"><a name="l01031"></a><span class="lineno"> 1031</span>  <span class="keywordflow">return</span> <a class="code" href="struct_layer_test_result.xhtml">LayerTestResult<float, 3></a>(actualOutput,</div><div class="line"><a name="l01032"></a><span class="lineno"> 1032</span>  outputVector,</div><div class="line"><a name="l01033"></a><span class="lineno"> 1033</span>  outputHandle->GetShape(),</div><div class="line"><a name="l01034"></a><span class="lineno"> 1034</span>  outputTensorInfo.GetShape());</div><div class="line"><a name="l01035"></a><span class="lineno"> 1035</span> }</div><div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a6c9de81fc65b3c4924cab11907075a17"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a6c9de81fc65b3c4924cab11907075a17">armnn::LstmDescriptor::m_ProjectionEnabled</a></div><div class="ttdeci">bool m_ProjectionEnabled</div><div class="ttdoc">Enable/disable the projection layer. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01114">Descriptors.hpp:1114</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a86e88bef0df4df96df752b4b8955a3af"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a86e88bef0df4df96df752b4b8955a3af">armnn::LstmDescriptor::m_ClippingThresProj</a></div><div class="ttdeci">float m_ClippingThresProj</div><div class="ttdoc">Clipping threshold value for the projection. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01108">Descriptors.hpp:1108</a></div></div> +<div class="ttc" id="classarmnn_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarmnn_1_1_tensor_info.xhtml">armnn::TensorInfo</a></div><div class="ttdef"><b>Definition:</b> <a href="_tensor_8hpp_source.xhtml#l00152">Tensor.hpp:152</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_ac18c8b8b2039267d8282e91b4162d8aa"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#ac18c8b8b2039267d8282e91b4162d8aa">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00747">WorkloadData.hpp:747</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a3dcd10ca3ea2e132558b1e2814668c15"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a3dcd10ca3ea2e132558b1e2814668c15">armnn::LstmDescriptor::m_TimeMajor</a></div><div class="ttdeci">bool m_TimeMajor</div><div class="ttdoc">Enable/disable time major. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01118">Descriptors.hpp:1118</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a44affeeb090c3c6a3062830562672e84"><div class="ttname"><a href="namespacearmnn.xhtml#a44affeeb090c3c6a3062830562672e84">armnn::IgnoreUnused</a></div><div class="ttdeci">void IgnoreUnused(Ts &&...)</div><div class="ttdef"><b>Definition:</b> <a href="_ignore_unused_8hpp_source.xhtml#l00014">IgnoreUnused.hpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_queue_descriptor_with_parameters_xhtml_aad91b9bbf7aa365d304febe79a3d1333"><div class="ttname"><a href="structarmnn_1_1_queue_descriptor_with_parameters.xhtml#aad91b9bbf7aa365d304febe79a3d1333">armnn::QueueDescriptorWithParameters::m_Parameters</a></div><div class="ttdeci">LayerDescriptor m_Parameters</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00054">WorkloadData.hpp:54</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_afaaca8c3f3a467d124bba44067d2afa8"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#afaaca8c3f3a467d124bba44067d2afa8">AllocateAndCopyDataToITensorHandle</a></div><div class="ttdeci">void AllocateAndCopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00019">TensorCopyUtils.cpp:19</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a5ff4158b1b363b898d0da04c42d37ce0"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a5ff4158b1b363b898d0da04c42d37ce0">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_OutputGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_OutputGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00755">WorkloadData.hpp:755</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a17ba1c8bcc71a55a95b2a3913f8cb203"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a17ba1c8bcc71a55a95b2a3913f8cb203">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00744">WorkloadData.hpp:744</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a841439e3b8dc157a7368b19c9ecb7d03"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a841439e3b8dc157a7368b19c9ecb7d03">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToCellWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToCellWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00743">WorkloadData.hpp:743</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aab77f54a037658ca9b2bf9cc8a1fadf1"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aab77f54a037658ca9b2bf9cc8a1fadf1">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_InputToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_InputToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00742">WorkloadData.hpp:742</a></div></div> +<div class="ttc" id="classarmnn_1_1_scoped_tensor_handle_xhtml"><div class="ttname"><a href="classarmnn_1_1_scoped_tensor_handle.xhtml">armnn::ScopedTensorHandle</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_tensor_handle_8hpp_source.xhtml#l00115">TensorHandle.hpp:115</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a2837b4396f20c956952d1a7286cab5f8"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a2837b4396f20c956952d1a7286cab5f8">armnn::LstmDescriptor::m_PeepholeEnabled</a></div><div class="ttdeci">bool m_PeepholeEnabled</div><div class="ttdoc">Enable/disable peephole. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01112">Descriptors.hpp:1112</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ab5dfed8358e500ed523d78090ec78e88"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ab5dfed8358e500ed523d78090ec78e88">CopyDataFromITensorHandle</a></div><div class="ttdeci">void CopyDataFromITensorHandle(void *mem, const armnn::ITensorHandle *tensorHandle)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00014">TensorCopyUtils.cpp:14</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ae1b07ed928036004bd257169e5aeeef4"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ae1b07ed928036004bd257169e5aeeef4">armnn::LstmDescriptor::m_ActivationFunc</a></div><div class="ttdeci">uint32_t m_ActivationFunc</div><div class="ttdoc">The activation function to use. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01104">Descriptors.hpp:1104</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_a531a3907ec13d3772370da88030191a5"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#a531a3907ec13d3772370da88030191a5">armnn::LstmDescriptor::m_ClippingThresCell</a></div><div class="ttdeci">float m_ClippingThresCell</div><div class="ttdoc">Clipping threshold value for the cell state. </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01106">Descriptors.hpp:1106</a></div></div> +<div class="ttc" id="structarmnn_1_1_lstm_descriptor_xhtml_ad474e5c51a0b194ef32e812b86c0cbdb"><div class="ttname"><a href="structarmnn_1_1_lstm_descriptor.xhtml#ad474e5c51a0b194ef32e812b86c0cbdb">armnn::LstmDescriptor::m_CifgEnabled</a></div><div class="ttdeci">bool m_CifgEnabled</div><div class="ttdoc">Enable/disable cifg (coupled input & forget gate). </div><div class="ttdef"><b>Definition:</b> <a href="_descriptors_8hpp_source.xhtml#l01110">Descriptors.hpp:1110</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a29fa293fffbf9c6f00cd75db1dc0a52a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a29fa293fffbf9c6f00cd75db1dc0a52a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_ForgetGateBias</a></div><div class="ttdeci">const ConstTensorHandle * m_ForgetGateBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00753">WorkloadData.hpp:753</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c"><div class="ttname"><a href="namespacearmnn.xhtml#a4dc0adc6737b5944e7671bee71788407acaf9b6b99962bf5c2264824231d7a40c">armnn::BoostLogSeverityMapping::info</a></div></div> +<div class="ttc" id="include_2armnn_test_utils_2_tensor_copy_utils_8hpp_xhtml_ae15f1a3c55d2db87683577de9fa4437c"><div class="ttname"><a href="include_2armnn_test_utils_2_tensor_copy_utils_8hpp.xhtml#ae15f1a3c55d2db87683577de9fa4437c">CopyDataToITensorHandle</a></div><div class="ttdeci">void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_copy_utils_8cpp_source.xhtml#l00009">TensorCopyUtils.cpp:9</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a6e9593869b82984de198fed27f72cdcf"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a6e9593869b82984de198fed27f72cdcf">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellBias</a></div><div class="ttdeci">const ConstTensorHandle * m_CellBias</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00754">WorkloadData.hpp:754</a></div></div> +<div class="ttc" id="namespacearmnn_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204"><div class="ttname"><a href="namespacearmnn.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a166495adc0d0f53bee6baecc577f5204">armnn::DataType::Float32</a></div></div> +<div class="ttc" id="structarmnn_1_1_workload_info_xhtml"><div class="ttname"><a href="structarmnn_1_1_workload_info.xhtml">armnn::WorkloadInfo</a></div><div class="ttdoc">Contains information about TensorInfos of a layer. </div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_info_8hpp_source.xhtml#l00016">WorkloadInfo.hpp:16</a></div></div> +<div class="ttc" id="struct_layer_test_result_xhtml"><div class="ttname"><a href="struct_layer_test_result.xhtml">LayerTestResult</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_test_utils_2_layer_test_result_8hpp_source.xhtml#l00015">LayerTestResult.hpp:15</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a20c10fcb26657477377d07b7b1e13120"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a20c10fcb26657477377d07b7b1e13120">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00750">WorkloadData.hpp:750</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml">armnn::UnidirectionalSequenceLstmQueueDescriptor</a></div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00714">WorkloadData.hpp:714</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_a4c27716f61bb68e8ea0bd4e8389ba01a"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#a4c27716f61bb68e8ea0bd4e8389ba01a">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00748">WorkloadData.hpp:748</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_workload_factory_xhtml_a13060ebb89d2c21a7a5d897e99cccf72"><div class="ttname"><a href="classarmnn_1_1_i_workload_factory.xhtml#a13060ebb89d2c21a7a5d897e99cccf72">armnn::IWorkloadFactory::CreateWorkload</a></div><div class="ttdeci">virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const</div><div class="ttdef"><b>Definition:</b> <a href="_workload_factory_8cpp_source.xhtml#l01541">WorkloadFactory.cpp:1541</a></div></div> +<div class="ttc" id="classarmnn_1_1_i_tensor_handle_factory_xhtml_a375f11dd42ff042435e8771cf287b20c"><div class="ttname"><a href="classarmnn_1_1_i_tensor_handle_factory.xhtml#a375f11dd42ff042435e8771cf287b20c">armnn::ITensorHandleFactory::CreateTensorHandle</a></div><div class="ttdeci">virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo) const =0</div></div> +<div class="ttc" id="namespacearmnn_xhtml_a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5"><div class="ttname"><a href="namespacearmnn.xhtml#a56943a0946e5f15e5e58054b8e7a04a4a300124b2433e0376ec4b19251ac3a9e5">armnn::LayerType::UnidirectionalSequenceLstm</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_adf8571dd1867ee91082bd005f94f2610"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#adf8571dd1867ee91082bd005f94f2610">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_RecurrentToForgetWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_RecurrentToForgetWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00746">WorkloadData.hpp:746</a></div></div> +<div class="ttc" id="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor_xhtml_aa09f7bdb9fd0d06b6386e412a4e72dd6"><div class="ttname"><a href="structarmnn_1_1_unidirectional_sequence_lstm_queue_descriptor.xhtml#aa09f7bdb9fd0d06b6386e412a4e72dd6">armnn::UnidirectionalSequenceLstmQueueDescriptor::m_CellToOutputWeights</a></div><div class="ttdeci">const ConstTensorHandle * m_CellToOutputWeights</div><div class="ttdef"><b>Definition:</b> <a href="include_2armnn_2backends_2_workload_data_8hpp_source.xhtml#l00751">WorkloadData.hpp:751</a></div></div> +</div><!-- fragment --> +</div> +</div> +</div><!-- contents --> +</div><!-- doc-content --> +<!-- start footer part --> +<div id="nav-path" class="navpath"><!-- id is needed for treeview function! --> + <ul> + <li class="navelem"><a class="el" href="dir_68267d1309a1af8e8297ef4c3efbcdba.xhtml">src</a></li><li class="navelem"><a class="el" href="dir_0f3cdec46afbc61a1ded8e1687c9c9a0.xhtml">backends</a></li><li class="navelem"><a class="el" href="dir_797a213d7d01b98ef12d53b0820ea64e.xhtml">backendsCommon</a></li><li class="navelem"><a class="el" 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