diff options
author | Francis Murtagh <francis.murtagh@arm.com> | 2019-08-14 09:51:36 +0100 |
---|---|---|
committer | Áron Virginás-Tar <aron.virginas-tar@arm.com> | 2019-08-14 10:37:35 +0000 |
commit | bb590b42b6a877e7caf0c5e73070bab42f44c760 (patch) | |
tree | 99b82801365a5fb25ea17725755244fb5f6f9692 /src | |
parent | d65cb800d2c5acca3f31e9358fa5bfbe153e3aa9 (diff) | |
download | armnn-bb590b42b6a877e7caf0c5e73070bab42f44c760.tar.gz |
IVGCVSW-3474 Refactor Lstm and QuantizedLstm Param Getters
* Change Getter Signatures to follow coding guidelines
Change-Id: Ic02621e834dbf79b9df63f8b4c6339f71651e944
Signed-off-by: Francis Murtagh <francis.murtagh@arm.com>
Diffstat (limited to 'src')
-rw-r--r-- | src/armnn/Network.cpp | 24 | ||||
-rw-r--r-- | src/armnnSerializer/Serializer.cpp | 28 | ||||
-rw-r--r-- | src/backends/cl/workloads/ClLstmFloatWorkload.cpp | 42 | ||||
-rw-r--r-- | src/backends/cl/workloads/ClQuantizedLstmWorkload.cpp | 24 | ||||
-rw-r--r-- | src/backends/neon/workloads/NeonLstmFloatWorkload.cpp | 42 | ||||
-rw-r--r-- | src/backends/neon/workloads/NeonQuantizedLstmWorkload.cpp | 24 | ||||
-rw-r--r-- | src/backends/reference/RefLayerSupport.cpp | 42 |
7 files changed, 113 insertions, 113 deletions
diff --git a/src/armnn/Network.cpp b/src/armnn/Network.cpp index b30cd9f3c2..932f9eb49e 100644 --- a/src/armnn/Network.cpp +++ b/src/armnn/Network.cpp @@ -1468,33 +1468,33 @@ IConnectableLayer* Network::AddQuantizedLstmLayer(const QuantizedLstmInputParams // InputToX weights layer->m_QuantizedLstmParameters.m_InputToInputWeights = - std::make_unique<ScopedCpuTensorHandle>(params.get_InputToInputWeights()); + std::make_unique<ScopedCpuTensorHandle>(params.GetInputToInputWeights()); layer->m_QuantizedLstmParameters.m_InputToForgetWeights = - std::make_unique<ScopedCpuTensorHandle>(params.get_InputToForgetWeights()); + std::make_unique<ScopedCpuTensorHandle>(params.GetInputToForgetWeights()); layer->m_QuantizedLstmParameters.m_InputToCellWeights = - std::make_unique<ScopedCpuTensorHandle>(params.get_InputToCellWeights()); + std::make_unique<ScopedCpuTensorHandle>(params.GetInputToCellWeights()); layer->m_QuantizedLstmParameters.m_InputToOutputWeights = - std::make_unique<ScopedCpuTensorHandle>(params.get_InputToOutputWeights()); + std::make_unique<ScopedCpuTensorHandle>(params.GetInputToOutputWeights()); // RecurrentToX weights layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights = - std::make_unique<ScopedCpuTensorHandle>(params.get_RecurrentToInputWeights()); + std::make_unique<ScopedCpuTensorHandle>(params.GetRecurrentToInputWeights()); layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights = - std::make_unique<ScopedCpuTensorHandle>(params.get_RecurrentToForgetWeights()); + std::make_unique<ScopedCpuTensorHandle>(params.GetRecurrentToForgetWeights()); layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights = - std::make_unique<ScopedCpuTensorHandle>(params.get_RecurrentToCellWeights()); + std::make_unique<ScopedCpuTensorHandle>(params.GetRecurrentToCellWeights()); layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights = - std::make_unique<ScopedCpuTensorHandle>(params.get_RecurrentToOutputWeights()); + std::make_unique<ScopedCpuTensorHandle>(params.GetRecurrentToOutputWeights()); // Bias layer->m_QuantizedLstmParameters.m_InputGateBias = - std::make_unique<ScopedCpuTensorHandle>(params.get_InputGateBias()); + std::make_unique<ScopedCpuTensorHandle>(params.GetInputGateBias()); layer->m_QuantizedLstmParameters.m_ForgetGateBias = - std::make_unique<ScopedCpuTensorHandle>(params.get_ForgetGateBias()); + std::make_unique<ScopedCpuTensorHandle>(params.GetForgetGateBias()); layer->m_QuantizedLstmParameters.m_CellBias = - std::make_unique<ScopedCpuTensorHandle>(params.get_CellBias()); + std::make_unique<ScopedCpuTensorHandle>(params.GetCellBias()); layer->m_QuantizedLstmParameters.m_OutputGateBias = - std::make_unique<ScopedCpuTensorHandle>(params.get_OutputGateBias()); + std::make_unique<ScopedCpuTensorHandle>(params.GetOutputGateBias()); return layer; } diff --git a/src/armnnSerializer/Serializer.cpp b/src/armnnSerializer/Serializer.cpp index af4dc7a926..d35be6f6d8 100644 --- a/src/armnnSerializer/Serializer.cpp +++ b/src/armnnSerializer/Serializer.cpp @@ -1049,20 +1049,20 @@ void SerializerVisitor::VisitQuantizedLstmLayer(const armnn::IConnectableLayer* auto fbQuantizedLstmBaseLayer = CreateLayerBase(layer, serializer::LayerType::LayerType_QuantizedLstm); // Get input parameters - auto inputToInputWeights = CreateConstTensorInfo(params.get_InputToInputWeights()); - auto inputToForgetWeights = CreateConstTensorInfo(params.get_InputToForgetWeights()); - auto inputToCellWeights = CreateConstTensorInfo(params.get_InputToCellWeights()); - auto inputToOutputWeights = CreateConstTensorInfo(params.get_InputToOutputWeights()); - - auto recurrentToInputWeights = CreateConstTensorInfo(params.get_RecurrentToInputWeights()); - auto recurrentToForgetWeights = CreateConstTensorInfo(params.get_RecurrentToForgetWeights()); - auto recurrentToCellWeights = CreateConstTensorInfo(params.get_RecurrentToCellWeights()); - auto recurrentToOutputWeights = CreateConstTensorInfo(params.get_RecurrentToOutputWeights()); - - auto inputGateBias = CreateConstTensorInfo(params.get_InputGateBias()); - auto forgetGateBias = CreateConstTensorInfo(params.get_ForgetGateBias()); - auto cellBias = CreateConstTensorInfo(params.get_CellBias()); - auto outputGateBias = CreateConstTensorInfo(params.get_OutputGateBias()); + auto inputToInputWeights = CreateConstTensorInfo(params.GetInputToInputWeights()); + auto inputToForgetWeights = CreateConstTensorInfo(params.GetInputToForgetWeights()); + auto inputToCellWeights = CreateConstTensorInfo(params.GetInputToCellWeights()); + auto inputToOutputWeights = CreateConstTensorInfo(params.GetInputToOutputWeights()); + + auto recurrentToInputWeights = CreateConstTensorInfo(params.GetRecurrentToInputWeights()); + auto recurrentToForgetWeights = CreateConstTensorInfo(params.GetRecurrentToForgetWeights()); + auto recurrentToCellWeights = CreateConstTensorInfo(params.GetRecurrentToCellWeights()); + auto recurrentToOutputWeights = CreateConstTensorInfo(params.GetRecurrentToOutputWeights()); + + auto inputGateBias = CreateConstTensorInfo(params.GetInputGateBias()); + auto forgetGateBias = CreateConstTensorInfo(params.GetForgetGateBias()); + auto cellBias = CreateConstTensorInfo(params.GetCellBias()); + auto outputGateBias = CreateConstTensorInfo(params.GetOutputGateBias()); auto fbQuantizedLstmParams = serializer::CreateQuantizedLstmInputParams( m_flatBufferBuilder, diff --git a/src/backends/cl/workloads/ClLstmFloatWorkload.cpp b/src/backends/cl/workloads/ClLstmFloatWorkload.cpp index f5d081e778..2f3ba75275 100644 --- a/src/backends/cl/workloads/ClLstmFloatWorkload.cpp +++ b/src/backends/cl/workloads/ClLstmFloatWorkload.cpp @@ -272,20 +272,20 @@ arm_compute::Status ClLstmFloatWorkloadValidate(const TensorInfo& input, const T // Basic parameters const arm_compute::TensorInfo aclInputToForgetWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToForgetWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToForgetWeights()); const arm_compute::TensorInfo aclInputToCellWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToCellWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToCellWeights()); const arm_compute::TensorInfo aclInputToOutputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToOutputWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToOutputWeights()); const arm_compute::TensorInfo aclRecurrentToForgetWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToForgetWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToForgetWeights()); const arm_compute::TensorInfo aclRecurrentToCellWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToCellWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToCellWeights()); const arm_compute::TensorInfo aclRecurrentToOutputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToOutputWeights()); - const arm_compute::TensorInfo aclForgetGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.get_ForgetGateBias()); - const arm_compute::TensorInfo aclCellBiasInfo = BuildArmComputeTensorInfo(paramsInfo.get_CellBias()); - const arm_compute::TensorInfo aclOutputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.get_OutputGateBias()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToOutputWeights()); + const arm_compute::TensorInfo aclForgetGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetForgetGateBias()); + const arm_compute::TensorInfo aclCellBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellBias()); + const arm_compute::TensorInfo aclOutputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetOutputGateBias()); arm_compute::TensorInfo aclInputToInputWeightsInfo; arm_compute::TensorInfo aclRecurrentToInputWeightsInfo; @@ -302,14 +302,14 @@ arm_compute::Status ClLstmFloatWorkloadValidate(const TensorInfo& input, const T if (!descriptor.m_CifgEnabled) { - aclInputToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_InputToInputWeights()); - aclRecurrentToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToInputWeights()); + aclInputToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputToInputWeights()); + aclRecurrentToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToInputWeights()); if (paramsInfo.m_CellToInputWeights != nullptr) { - aclCellToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_CellToInputWeights()); + aclCellToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToInputWeights()); } - aclInputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.get_InputGateBias()); + aclInputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputGateBias()); lstm_params_info.set_cifg_params(&aclInputToInputWeightsInfo, &aclRecurrentToInputWeightsInfo, paramsInfo.m_CellToInputWeights != nullptr ? &aclCellToInputWeightsInfo: nullptr, @@ -318,11 +318,11 @@ arm_compute::Status ClLstmFloatWorkloadValidate(const TensorInfo& input, const T if (descriptor.m_ProjectionEnabled) { - aclProjectionWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_ProjectionWeights()); + aclProjectionWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetProjectionWeights()); if (paramsInfo.m_ProjectionBias != nullptr) { - aclProjectionBiasInfo = BuildArmComputeTensorInfo(paramsInfo.get_InputGateBias()); + aclProjectionBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputGateBias()); } lstm_params_info.set_projection_params(&aclProjectionWeightsInfo, paramsInfo.m_ProjectionBias != nullptr ? @@ -331,8 +331,8 @@ arm_compute::Status ClLstmFloatWorkloadValidate(const TensorInfo& input, const T if (descriptor.m_PeepholeEnabled) { - aclCellToForgetWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_CellToForgetWeights()); - aclCellToOutputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_CellToOutputWeights()); + aclCellToForgetWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToForgetWeights()); + aclCellToOutputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToOutputWeights()); lstm_params_info.set_peephole_params(&aclCellToForgetWeightsInfo, &aclCellToOutputWeightsInfo); } @@ -374,14 +374,14 @@ arm_compute::Status ClLstmFloatWorkloadValidate(const TensorInfo& input, const T { if (!descriptor.m_CifgEnabled) { - aclInputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_InputLayerNormWeights()); + aclInputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputLayerNormWeights()); } - aclForgetLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_ForgetLayerNormWeights()); + aclForgetLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetForgetLayerNormWeights()); - aclCellLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_CellLayerNormWeights()); + aclCellLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellLayerNormWeights()); - aclOutputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_OutputLayerNormWeights()); + aclOutputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetOutputLayerNormWeights()); lstm_params_info.set_layer_normalization_params(descriptor.m_CifgEnabled ? nullptr : &aclInputLayerNormWeightsInfo, diff --git a/src/backends/cl/workloads/ClQuantizedLstmWorkload.cpp b/src/backends/cl/workloads/ClQuantizedLstmWorkload.cpp index 76a6694153..688ebf9184 100644 --- a/src/backends/cl/workloads/ClQuantizedLstmWorkload.cpp +++ b/src/backends/cl/workloads/ClQuantizedLstmWorkload.cpp @@ -31,25 +31,25 @@ arm_compute::Status ClQuantizedLstmWorkloadValidate(const TensorInfo& input, con // Basic parameters const arm_compute::TensorInfo aclInputToInputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToInputWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToInputWeights()); const arm_compute::TensorInfo aclInputToForgetWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToForgetWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToForgetWeights()); const arm_compute::TensorInfo aclInputToCellWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToCellWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToCellWeights()); const arm_compute::TensorInfo aclInputToOutputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToOutputWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToOutputWeights()); const arm_compute::TensorInfo aclRecurrentToInputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToInputWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToInputWeights()); const arm_compute::TensorInfo aclRecurrentToForgetWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToForgetWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToForgetWeights()); const arm_compute::TensorInfo aclRecurrentToCellWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToCellWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToCellWeights()); const arm_compute::TensorInfo aclRecurrentToOutputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToOutputWeights()); - const arm_compute::TensorInfo aclInputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.get_InputGateBias()); - const arm_compute::TensorInfo aclForgetGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.get_ForgetGateBias()); - const arm_compute::TensorInfo aclCellBiasInfo = BuildArmComputeTensorInfo(paramsInfo.get_CellBias()); - const arm_compute::TensorInfo aclOutputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.get_OutputGateBias()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToOutputWeights()); + const arm_compute::TensorInfo aclInputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputGateBias()); + const arm_compute::TensorInfo aclForgetGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetForgetGateBias()); + const arm_compute::TensorInfo aclCellBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellBias()); + const arm_compute::TensorInfo aclOutputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetOutputGateBias()); return arm_compute::CLLSTMLayerQuantized::validate(&aclInputInfo, &aclInputToInputWeightsInfo, &aclInputToForgetWeightsInfo, &aclInputToCellWeightsInfo, diff --git a/src/backends/neon/workloads/NeonLstmFloatWorkload.cpp b/src/backends/neon/workloads/NeonLstmFloatWorkload.cpp index 6dd9f4f698..2f29610e71 100644 --- a/src/backends/neon/workloads/NeonLstmFloatWorkload.cpp +++ b/src/backends/neon/workloads/NeonLstmFloatWorkload.cpp @@ -291,23 +291,23 @@ arm_compute::Status NeonLstmFloatWorkloadValidate(const TensorInfo& input, // Basic parameters const arm_compute::TensorInfo aclInputToForgetWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToForgetWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToForgetWeights()); const arm_compute::TensorInfo aclInputToCellWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToCellWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToCellWeights()); const arm_compute::TensorInfo aclInputToOutputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToOutputWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToOutputWeights()); const arm_compute::TensorInfo aclRecurrentToForgetWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToForgetWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToForgetWeights()); const arm_compute::TensorInfo aclRecurrentToCellWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToCellWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToCellWeights()); const arm_compute::TensorInfo aclRecurrentToOutputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToOutputWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToOutputWeights()); const arm_compute::TensorInfo aclForgetGateBiasInfo - = BuildArmComputeTensorInfo(paramsInfo.get_ForgetGateBias()); + = BuildArmComputeTensorInfo(paramsInfo.GetForgetGateBias()); const arm_compute::TensorInfo aclCellBiasInfo - = BuildArmComputeTensorInfo(paramsInfo.get_CellBias()); + = BuildArmComputeTensorInfo(paramsInfo.GetCellBias()); const arm_compute::TensorInfo aclOutputGateBiasInfo - = BuildArmComputeTensorInfo(paramsInfo.get_OutputGateBias()); + = BuildArmComputeTensorInfo(paramsInfo.GetOutputGateBias()); arm_compute::TensorInfo aclInputToInputWeightsInfo; arm_compute::TensorInfo aclRecurrentToInputWeightsInfo; @@ -328,11 +328,11 @@ arm_compute::Status NeonLstmFloatWorkloadValidate(const TensorInfo& input, { if (descriptor.m_PeepholeEnabled) { - aclCellToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_CellToInputWeights()); + aclCellToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToInputWeights()); } - aclInputToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_InputToInputWeights()); - aclRecurrentToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToInputWeights()); - aclInputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.get_InputGateBias()); + aclInputToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputToInputWeights()); + aclRecurrentToInputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToInputWeights()); + aclInputGateBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputGateBias()); lstm_params_info.set_cifg_params(&aclInputToInputWeightsInfo, &aclRecurrentToInputWeightsInfo, descriptor.m_PeepholeEnabled ? &aclCellToInputWeightsInfo : nullptr, @@ -343,9 +343,9 @@ arm_compute::Status NeonLstmFloatWorkloadValidate(const TensorInfo& input, { if (paramsInfo.m_ProjectionBias != nullptr) { - aclProjectionBiasInfo = BuildArmComputeTensorInfo(paramsInfo.get_ProjectionBias()); + aclProjectionBiasInfo = BuildArmComputeTensorInfo(paramsInfo.GetProjectionBias()); } - aclProjectionWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_ProjectionWeights()); + aclProjectionWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetProjectionWeights()); lstm_params_info.set_projection_params(&aclProjectionWeightsInfo, paramsInfo.m_ProjectionBias != nullptr ? @@ -354,8 +354,8 @@ arm_compute::Status NeonLstmFloatWorkloadValidate(const TensorInfo& input, if (descriptor.m_PeepholeEnabled) { - aclCellToForgetWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_CellToForgetWeights()); - aclCellToOutputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_CellToOutputWeights()); + aclCellToForgetWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToForgetWeights()); + aclCellToOutputWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellToOutputWeights()); lstm_params_info.set_peephole_params(&aclCellToForgetWeightsInfo, &aclCellToOutputWeightsInfo); } @@ -364,11 +364,11 @@ arm_compute::Status NeonLstmFloatWorkloadValidate(const TensorInfo& input, { if (!descriptor.m_CifgEnabled) { - aclInputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_InputLayerNormWeights()); + aclInputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetInputLayerNormWeights()); } - aclForgetLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_ForgetLayerNormWeights()); - aclCellLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_CellLayerNormWeights()); - aclOutputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.get_OutputLayerNormWeights()); + aclForgetLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetForgetLayerNormWeights()); + aclCellLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetCellLayerNormWeights()); + aclOutputLayerNormWeightsInfo = BuildArmComputeTensorInfo(paramsInfo.GetOutputLayerNormWeights()); lstm_params_info.set_layer_normalization_params(descriptor.m_CifgEnabled ? nullptr : &aclInputLayerNormWeightsInfo, diff --git a/src/backends/neon/workloads/NeonQuantizedLstmWorkload.cpp b/src/backends/neon/workloads/NeonQuantizedLstmWorkload.cpp index d4319d414d..4c2ba7513d 100644 --- a/src/backends/neon/workloads/NeonQuantizedLstmWorkload.cpp +++ b/src/backends/neon/workloads/NeonQuantizedLstmWorkload.cpp @@ -143,31 +143,31 @@ arm_compute::Status NeonQuantizedLstmWorkloadValidate(const TensorInfo& input, // Basic parameters const arm_compute::TensorInfo aclInputToInputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToInputWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToInputWeights()); const arm_compute::TensorInfo aclInputToForgetWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToForgetWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToForgetWeights()); const arm_compute::TensorInfo aclInputToCellWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToCellWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToCellWeights()); const arm_compute::TensorInfo aclInputToOutputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputToOutputWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputToOutputWeights()); const arm_compute::TensorInfo aclRecurrentToInputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToInputWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToInputWeights()); const arm_compute::TensorInfo aclRecurrentToForgetWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToForgetWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToForgetWeights()); const arm_compute::TensorInfo aclRecurrentToCellWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToCellWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToCellWeights()); const arm_compute::TensorInfo aclRecurrentToOutputWeightsInfo - = BuildArmComputeTensorInfo(paramsInfo.get_RecurrentToOutputWeights()); + = BuildArmComputeTensorInfo(paramsInfo.GetRecurrentToOutputWeights()); const arm_compute::TensorInfo aclInputGateBiasInfo - = BuildArmComputeTensorInfo(paramsInfo.get_InputGateBias()); + = BuildArmComputeTensorInfo(paramsInfo.GetInputGateBias()); const arm_compute::TensorInfo aclForgetGateBiasInfo - = BuildArmComputeTensorInfo(paramsInfo.get_ForgetGateBias()); + = BuildArmComputeTensorInfo(paramsInfo.GetForgetGateBias()); const arm_compute::TensorInfo aclCellBiasInfo - = BuildArmComputeTensorInfo(paramsInfo.get_CellBias()); + = BuildArmComputeTensorInfo(paramsInfo.GetCellBias()); const arm_compute::TensorInfo aclOutputGateBiasInfo - = BuildArmComputeTensorInfo(paramsInfo.get_OutputGateBias()); + = BuildArmComputeTensorInfo(paramsInfo.GetOutputGateBias()); return arm_compute::NELSTMLayerQuantized::validate(&aclInputInfo, &aclInputToInputWeightsInfo, diff --git a/src/backends/reference/RefLayerSupport.cpp b/src/backends/reference/RefLayerSupport.cpp index 2648f459d6..56ca437b21 100644 --- a/src/backends/reference/RefLayerSupport.cpp +++ b/src/backends/reference/RefLayerSupport.cpp @@ -808,54 +808,54 @@ bool RefLayerSupport::IsLstmSupported(const TensorInfo& input, supported &= CheckSupportRule(TypesAreEqual(input, output), reasonIfUnsupported, "Reference Lstm: input and output types are mismatched"); // check layer parameters - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_InputToForgetWeights()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetInputToForgetWeights()), reasonIfUnsupported, "Reference Lstm: input and InputToForgetWeights types are mismatched"); - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_InputToCellWeights()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetInputToCellWeights()), reasonIfUnsupported, "Reference Lstm: input and InputToCellWeights types are mismatched"); - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_InputToOutputWeights()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetInputToOutputWeights()), reasonIfUnsupported, "Reference Lstm: input and InputToOutputWeights types are mismatched"); - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_RecurrentToForgetWeights()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetRecurrentToForgetWeights()), reasonIfUnsupported, "Reference Lstm: input and RecurrentToForgetWeights types are mismatched"); - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_RecurrentToCellWeights()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetRecurrentToCellWeights()), reasonIfUnsupported, "Reference Lstm: input and RecurrentToCellWeights types are mismatched"); - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_RecurrentToOutputWeights()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetRecurrentToOutputWeights()), reasonIfUnsupported, "Reference Lstm: input and RecurrentToOutputWeights types are mismatched"); - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_ForgetGateBias()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetForgetGateBias()), reasonIfUnsupported, "Reference Lstm: input and ForgetGateBias types are mismatched"); - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_CellBias()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetCellBias()), reasonIfUnsupported, "Reference Lstm: input and CellBias types are mismatched"); - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_OutputGateBias()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetOutputGateBias()), reasonIfUnsupported, "Reference Lstm: input and OutputGateBias types are mismatched"); if (!descriptor.m_CifgEnabled) { - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_InputToInputWeights()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetInputToInputWeights()), reasonIfUnsupported, "Reference Lstm: input and InputToInputWeights types are mismatched"); - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_RecurrentToInputWeights()), + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetRecurrentToInputWeights()), reasonIfUnsupported, "Reference Lstm: input and RecurrentToInputWeights types are mismatched"); - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_InputGateBias()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetInputGateBias()), reasonIfUnsupported, "Reference Lstm: input and InputGateBias types are mismatched"); if (descriptor.m_PeepholeEnabled) { - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_CellToInputWeights()), + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetCellToInputWeights()), reasonIfUnsupported, "Reference Lstm: input and CellToInputWeights types are mismatched"); } } if (descriptor.m_PeepholeEnabled) { - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_CellToForgetWeights()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetCellToForgetWeights()), reasonIfUnsupported, "Reference Lstm: input and CellToForgetWeights types are mismatched"); - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_CellToOutputWeights()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetCellToOutputWeights()), reasonIfUnsupported, "Reference Lstm: input and CellToOutputWeights types are mismatched"); } if (descriptor.m_ProjectionEnabled) { - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_ProjectionWeights()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetProjectionWeights()), reasonIfUnsupported, "Reference Lstm: input and mProjectionWeights types are mismatched"); if (paramsInfo.m_ProjectionBias != nullptr) { - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_ProjectionBias()), reasonIfUnsupported, + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetProjectionBias()), reasonIfUnsupported, "Reference Lstm: input and ProjectionBias types are mismatched"); } } @@ -863,17 +863,17 @@ bool RefLayerSupport::IsLstmSupported(const TensorInfo& input, { if (!descriptor.m_CifgEnabled) { - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_InputLayerNormWeights()), + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetInputLayerNormWeights()), reasonIfUnsupported, "Reference Lstm: input and InputLayerNormWeights types are mismatched"); } - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_ForgetLayerNormWeights()), + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetForgetLayerNormWeights()), reasonIfUnsupported, "Reference Lstm: input and ForgetLayerNormWeights types are mismatched"); - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_CellLayerNormWeights()), + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetCellLayerNormWeights()), reasonIfUnsupported, "Reference Lstm: input and CellLayerNormWeights types are mismatched"); - supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.get_OutputLayerNormWeights()), + supported &= CheckSupportRule(TypesAreEqual(input, paramsInfo.GetOutputLayerNormWeights()), reasonIfUnsupported, "Reference Lstm: input and OutputLayerNormWeights types are mismatched"); } |