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author | Nikhil Raj <nikhil.raj@arm.com> | 2021-11-05 12:26:41 +0000 |
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committer | Jim Flynn <jim.flynn@arm.com> | 2021-11-06 09:20:24 +0000 |
commit | 3f22d27f51c493e37b9da0692b6bf776f4430dcf (patch) | |
tree | 9fa3a05ff5bc9298ca768db8aa18b8a935e19daf /docs/02_operator_list.dox | |
parent | d3b94d305fddd3bbbdf718685084087e4b92ca7f (diff) | |
download | armnn-3f22d27f51c493e37b9da0692b6bf776f4430dcf.tar.gz |
IVGCVSW-6372 Change order in doxygen tree view
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: Ia765d335ef998e7e47a1c0c81a375645972f4e1d
Diffstat (limited to 'docs/02_operator_list.dox')
-rw-r--r-- | docs/02_operator_list.dox | 3333 |
1 files changed, 3333 insertions, 0 deletions
diff --git a/docs/02_operator_list.dox b/docs/02_operator_list.dox new file mode 100644 index 0000000000..90aee130bf --- /dev/null +++ b/docs/02_operator_list.dox @@ -0,0 +1,3333 @@ +/// Copyright (c) 2021 ARM Limited and Contributors. All rights reserved. +/// +/// SPDX-License-Identifier: MIT +/// + +namespace armnn +{ +/** +@page operator_list Arm NN Operators + +@tableofcontents + +@section S5_1_operator_list Arm NN Operators + +Arm NN supports operators that are listed in below table. + +Arm NN supports a wide list of data-types. +The main data-types that the Machine Learning functions support are the following: + <ul> + <li><b>BFLOAT16:</b> 16-bit non-standard brain floating point + <li><b>QASYMMU8:</b> 8-bit unsigned asymmetric quantized + <li><b>QASYMMS8:</b> 8-bit signed asymmetric quantized + <li><b>QUANTIZEDSYMM8PERAXIS:</b> 8-bit signed symmetric quantized + <li><b>QSYMMS8:</b> 8-bit unsigned symmetric quantized + <li><b>QSYMMS16:</b> 16-bit unsigned symmetric quantized + <li><b>FLOAT32:</b> 32-bit single precision floating point + <li><b>FLOAT16:</b> 16-bit half precision floating point + <li><b>SIGNED32:</b> 32-bit signed integer + <li><b>BOOLEAN:</b> 8-bit unsigned char + <li><b>All:</b> Agnostic to any specific data type + </ul> + +Arm NN supports the following data layouts (fast changing dimension from right to left): + <ul> + <li><b>NHWC:</b> Layout where channels are in the fastest changing dimension + <li><b>NCHW:</b> Layout where width is in the fastest changing dimension + <li><b>All:</b> Agnostic to any specific data layout + </ul> +where N = batches, C = channels, H = height, W = width + +<table> +<caption id="multi_row"></caption> +<tr> + <th>Operator + <th>Description + <th>Equivalent Android NNAPI Operator + <th>Backends + <th>Data Layouts + <th>Data Types +<tr> + <td rowspan="3">AbsLayer + <td rowspan="3"> Layer to perform absolute operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_ABS + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>SIGNED32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">ActivationLayer + <td rowspan="3" style="width:200px;"> Layer to simulate an activation layer with the specified activation function. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_ABS + <li>ANEURALNETWORKS_ELU + <li>ANEURALNETWORKS_HARD_SWISH + <li>ANEURALNETWORKS_LOGISTIC + <li>ANEURALNETWORKS_PRELU + <li>ANEURALNETWORKS_RELU + <li>ANEURALNETWORKS_RELU1 + <li>ANEURALNETWORKS_RELU6 + <li>ANEURALNETWORKS_SQRT + <li>ANEURALNETWORKS_TANH + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QSYMMS16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QSYMMS16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">AdditionLayer + <td rowspan="3" style="width:200px;"> Layer to add 2 tensors. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_ADD + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">ArgMinMaxLayer + <td rowspan="3" style="width:200px;"> Layer to calculate the index of the minimum or maximum values in a tensor + based on an axis. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_ARGMAX + <li>ANEURALNETWORKS_ARGMIN + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + <tr><td>SIGNED64 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">BatchNormalizationLayer + <td rowspan="3" style="width:200px;"> Layer to perform batch normalization. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT32 + <tr><td>FLOAT16 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT32 + <tr><td>FLOAT16 + </table> +<tr> + <td rowspan="3">BatchToSpaceNdLayer + <td rowspan="3" style="width:200px;"> Layer to perform a batch to space transformation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_BATCH_TO_SPACE_ND + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">CastLayer + <td rowspan="3" style="width:200px;"> Layer to cast a tensor to a type. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_CAST + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QSYMMS8 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>FLOAT16 + <tr><td>SIGNED32 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">ChannelShuffleLayer + <td rowspan="3" style="width:200px;"> Layer to reorganize the channels of a tensor. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_CHANNEL_SHUFFLE + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QSYMMS8 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">ComparisonLayer + <td rowspan="3" style="width:200px;"> Layer to compare 2 tensors. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_EQUAL + <li>ANEURALNETWORKS_GREATER + <li>ANEURALNETWORKS_GREATER_EQUAL + <li>ANEURALNETWORKS_LESS + <li>ANEURALNETWORKS_LESS_EQUAL + <li>ANEURALNETWORKS_NOT_EQUAL + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>BOOLEAN + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">ConcatLayer + <td rowspan="3" style="width:200px;"> Layer to concatenate tensors along a given axis. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_CONCATENATION + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">ConstantLayer + <td rowspan="3" style="width:200px;"> Layer to provide a constant tensor. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">ConvertBf16ToFp32Layer + <td rowspan="3" style="width:200px;"> Layer to convert BFloat16 tensor to Float32 tensor. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">ConvertFp16ToFp32Layer + <td rowspan="3" style="width:200px;"> Layer to convert Float16 tensor to Float32 tensor. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">ConvertFp32ToBf16Layer + <td rowspan="3" style="width:200px;"> Layer to convert Float32 tensor to BFloat16 tensor. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">ConvertFp32ToFp16Layer + <td rowspan="3" style="width:200px;"> Layer to convert Float32 tensor to Float16 tensor. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">Convolution2dLayer + <td rowspan="3" style="width:200px;"> Layer to compute a convolution operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_CONV_2D + <li>ANEURALNETWORKS_GROUPED_CONV_2D + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QUANTIZEDSYMM8PERAXIS + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QUANTIZEDSYMM8PERAXIS + </table> +<tr> + <td rowspan="3">Convolution3dLayer + <td rowspan="3" style="width:200px;"> Layer to compute a 3D convolution operation. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>NDHWC + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>N/A + </ul> + <td> + <ul> + <li>N/A + </ul> +<tr> + <td>GpuAcc + <td> + <ul> + <li>N/A + </ul> + <td> + <ul> + <li>N/A + </ul> +<tr> + <td rowspan="1">DebugLayer + <td rowspan="1" style="width:200px;"> Layer to print out inter layer tensor information. + <td rowspan="1"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td rowspan="3">DepthToSpaceLayer + <td rowspan="3" style="width:200px;"> Layer to perform Depth to Space transformation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_DEPTH_TO_SPACE + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">DepthwiseConvolution2dLayer + <td rowspan="3" style="width:200px;"> Layer to compute a deconvolution or transpose convolution. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_DEPTHWISE_CONV_2D + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>SIGNED32 + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QUANTIZEDSYMM8PERAXIS + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>SIGNED32 + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QUANTIZEDSYMM8PERAXIS + </table> +<tr> + <td rowspan="3">DequantizeLayer + <td rowspan="3" style="width:200px;"> Layer to dequantize the values in a tensor. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_DEQUANTIZE + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QUANTIZEDSYMM8PERAXIS + <tr><td>QSYMMS8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QUANTIZEDSYMM8PERAXIS + <tr><td>QSYMMS8 + <tr><td>QSYMMS16 + </table> +<tr> + <td rowspan="2">DetectionPostProcessLayer + <td rowspan="2" style="width:200px;"> Layer to generate the detection output based on center size encoded boxes, class prediction and anchors by doing non maximum suppression (NMS). + <td rowspan="2"> + <ul> + <li>ANEURALNETWORKS_DETECTION_POSTPROCESSING + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">DivisionLayer + <td rowspan="3" style="width:200px;"> Layer to divide 2 tensors. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_DIV + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">ElementwiseBaseLayer + <td rowspan="3" style="width:200px;"> Layer to perform Add - Div - Max - Min - Mul operations. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_ADD + <li>ANEURALNETWORKS_DIV + <li>ANEURALNETWORKS_MAXIMUM + <li>ANEURALNETWORKS_MINIMUM + <li>ANEURALNETWORKS_MUL + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">ElementwiseUnaryLayer + <td rowspan="3" style="width:200px;"> Layer to perform Rsqrt - Exp - Neg - Log - Abs - Sin - Sqrt operations. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_ABS + <li>ANEURALNETWORKS_EXP + <li>ANEURALNETWORKS_LOG + <li>ANEURALNETWORKS_NEG + <li>ANEURALNETWORKS_RSQRT + <li>ANEURALNETWORKS_SIN + <li>ANEURALNETWORKS_SQRT + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>SIGNED32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="1">FakeQuantizationLayer + <td rowspan="1" style="width:200px;"> Layer to quantize float values and dequantize afterwards. The current implementation does not dequantize the values. + <td rowspan="1"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">FillLayer + <td rowspan="3" style="width:200px;"> Layer to set the values of a tensor with a given value. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_FILL + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">FloorLayer + <td rowspan="3" style="width:200px;"> Layer to round the value to the lowest whole number. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_FLOOR + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT32 + <tr><td>FLOAT16 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT32 + <tr><td>FLOAT16 + </table> +<tr> + <td rowspan="3">FullyConnectedLayer + <td rowspan="3" style="width:200px;"> Layer to perform a fully connected / dense operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_FULLY_CONNECTED + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + </table> +<tr> + <td rowspan="3">GatherLayer + <td rowspan="3" style="width:200px;"> Layer to perform the gather operation along the chosen axis. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_GATHER + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="1">InputLayer + <td rowspan="1" style="width:200px;"> Special layer used to provide input data to the computational network. + <td rowspan="1"> + <ul> + <li>N/A + </ul> + <td>All + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">InstanceNormalizationLayer + <td rowspan="3" style="width:200px;"> Layer to perform an instance normalization on a given axis. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_INSTANCE_NORMALIZATION + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">L2NormalizationLayer + <td rowspan="3" style="width:200px;"> Layer to perform an L2 normalization on a given axis. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_L2_NORMALIZATION + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">LogSoftmaxLayer + <td rowspan="3" style="width:200px;"> Layer to perform the log softmax activations given logits. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">LogicalBinaryLayer + <td rowspan="3" style="width:200px;"> Layer to perform Logical AND - Logical NOT - Logical OR operations. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_LOGICAL_AND + <li>ANEURALNETWORKS_LOGICAL_NOT + <li>ANEURALNETWORKS_LOGICAL_OR + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BOOLEAN + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BOOLEAN + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BOOLEAN + </table> +<tr> + <td rowspan="3">LstmLayer + <td rowspan="3" style="width:200px;"> Layer to perform a single time step in a Long Short-Term Memory (LSTM) operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_LSTM + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">MapLayer + <td rowspan="3" style="width:200px;"> Layer to perform map operation on tensor. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">MaximumLayer + <td rowspan="3" style="width:200px;"> Layer to perform an elementwise maximum of two tensors. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>SIGNED32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QSYMMS16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>SIGNED32 + </table> +<tr> + <td rowspan="3">MeanLayer + <td rowspan="3" style="width:200px;"> Layer to perform reduce mean operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_MEAN + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">MemCopyLayer + <td rowspan="3" style="width:200px;"> Layer to perform memory copy operation. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>BOOLEAN + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">MemImportLayer + <td rowspan="3" style="width:200px;"> Layer to perform memory import operation. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">MergeLayer + <td rowspan="3" style="width:200px;"> Layer to concatenate tensors along a given axis. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_CONCATENATION + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">MinimumLayer + <td rowspan="3" style="width:200px;"> Layer to perform an elementwise minimum of two tensors. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_MINIMUM + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QSYMMS16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QSYMMS16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>SIGNED32 + </table> +<tr> + <td rowspan="3">MultiplicationLayer + <td rowspan="3" style="width:200px;"> Layer to perform an elementwise multiplication of two tensors. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_MUL + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>SIGNED32 + </table> +<tr> + <td rowspan="3">NormalizationLayer + <td rowspan="3" style="width:200px;"> Layer to compute normalization operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_LOCAL_RESPONSE_NORMALIZATION + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT32 + <tr><td>FLOAT16 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT32 + <tr><td>FLOAT16 + </table> +<tr> + <td rowspan="1">OutputLayer + <td rowspan="1" style="width:200px;"> A special layer providing access to a user supplied buffer into which the output of a network can be written. + <td rowspan="1"> + <ul> + <li>N/A + </ul> + <td>All + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">PadLayer + <td rowspan="3" style="width:200px;"> Layer to pad a tensor. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_PAD + <li>ANEURALNETWORKS_PAD_V2 + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">PermuteLayer + <td rowspan="3" style="width:200px;"> Layer to transpose an ND tensor. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_TRANSPOSE + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">Pooling2dLayer + <td rowspan="3" style="width:200px;"> Layer to perform pooling with the specified pooling operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_AVERAGE_POOL_2D + <li>ANEURALNETWORKS_L2_POOL_2D + <li>ANEURALNETWORKS_MAX_POOL_2D + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="1">PreCompiledLayer + <td rowspan="1" style="width:200px;"> Opaque layer provided by a backend which provides an executable representation of a subgraph from the original network. + <td rowspan="1"> + <ul> + <li>N/A + </ul> + <td>N/A + <td>N/A + <td>N/A +<tr> + <td rowspan="3">PreluLayer + <td rowspan="3" style="width:200px;"> Layer to compute the activation layer with the PRELU activation function. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_PRELU + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">QLstmLayer + <td rowspan="3" style="width:200px;"> Layer to perform quantized LSTM (Long Short-Term Memory) operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_QUANTIZED_LSTM + <li>ANEURALNETWORKS_QUANTIZED_16BIT_LSTM + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>SIGNED32 + <tr><td>QSYMMS16 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>SIGNED32 + <tr><td>QSYMMS16 + </table> +<tr> + <td rowspan="3">QuantizeLayer + <td rowspan="3" style="width:200px;"> Layer to perform quantization operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_QUANTIZE + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QASYMM16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QASYMM16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">QuantizedLstmLayer + <td rowspan="3" style="width:200px;"> Layer to perform quantized LSTM (Long Short-Term Memory) operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_QUANTIZED_LSTM + <li>ANEURALNETWORKS_QUANTIZED_16BIT_LSTM + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>SIGNED32 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>SIGNED32 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td rowspan="3">RankLayer + <td rowspan="3" style="width:200px;"> Layer to perform a rank operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_RANK + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">ReduceLayer + <td rowspan="3" style="width:200px;"> Layer to perform reduce with the following operations - ARG_IDX_MAX: Index of the max value - ARG_IDX_MIN: Index of the min value - MEAN_SUM: Mean of sum - PROD: Product - SUM_SQUARE: Sum of squares - SUM: Sum - MIN: Min - MAX: Max + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_REDUCE_MAX + <li>ANEURALNETWORKS_REDUCE_MIN + <li>ANEURALNETWORKS_REDUCE_SUM + <li>ANEURALNETWORKS_REDUCE_PROD + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>SIGNED32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>SIGNED32 + </table> +<tr> + <td rowspan="3">ReshapeLayer + <td rowspan="3" style="width:200px;"> Layer to reshape a tensor. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_RESHAPE + <li>ANEURALNETWORKS_SQUEEZE + <li>ANEURALNETWORKS_EXPAND_DIMS + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + <tr><td>BOOLEAN + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">ResizeLayer + <td rowspan="3" style="width:200px;"> Layer to perform resize of a tensor using one of the interpolation methods: - Bilinear - Nearest Neighbor. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_RESIZE_BILINEAR + <li>ANEURALNETWORKS_RESIZE_NEAREST_NEIGHBOR + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">RsqrtLayer + <td rowspan="3" style="width:200px;"> Layer to perform Rsqrt operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_RSQRT + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>SIGNED32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">ShapeLayer + <td rowspan="3" style="width:200px;"> Layer to return the shape of the input tensor. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">SliceLayer + <td rowspan="3" style="width:200px;"> Layer to perform tensor slicing. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_SLICE + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">SoftmaxLayer + <td rowspan="3" style="width:200px;"> Layer to perform softmax, log-softmax operation over the specified axis. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_LOG_SOFTMAX + <li>ANEURALNETWORKS_SOFTMAX + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">SpaceToBatchNdLayer + <td rowspan="3" style="width:200px;"> Layer to divide spatial dimensions of the tensor into a grid of blocks and interleaves these blocks with the batch dimension. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_SPACE_TO_BATCH_ND + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">SpaceToDepthLayer + <td rowspan="3" style="width:200px;"> Layer to rearrange blocks of spatial data into depth. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_SPACE_TO_DEPTH + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">SplitterLayer + <td rowspan="3" style="width:200px;"> Layer to split a tensor along a given axis. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_SPLIT + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">StackLayer + <td rowspan="3" style="width:200px;"> Layer to stack tensors along an axis. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="1">StandInLayer + <td rowspan="1" style="width:200px;"> A layer to represent "unknown" or "unsupported" operations in the input graph. It has a configurable number of input and output slots and an optional name. + <td rowspan="1"> + <ul> + <li>N/A + </ul> + <td>N/A + <td>N/A + <td>N/A +<tr> + <td rowspan="3">StridedSliceLayer + <td rowspan="3" style="width:200px;"> Layer to extract a strided slice of a tensor. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_STRIDED_SLICE + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">SubtractionLayer + <td rowspan="3" style="width:200px;"> Layer to perform an elementwise subtract of 2 tensors. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_SUB + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QSYMMS16 + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + </table> +<tr> + <td rowspan="3">TransposeConvolution2dLayer + <td rowspan="3" style="width:200px;"> Layer to perform 2D transpose convolution (deconvolution) operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_TRANSPOSE_CONV_2D + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QUANTIZEDSYMM8PERAXIS + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>SIGNED32 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMU8 + <tr><td>QASYMMS8 + <tr><td>QUANTIZEDSYMM8PERAXIS + </table> +<tr> + <td rowspan="3">TransposeLayer + <td rowspan="3" style="width:200px;"> Layer to transpose a tensor. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_TRANSPOSE + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>BFLOAT16 + <tr><td>FLOAT16 + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + <tr><td>QASYMMU8 + <tr><td>QSYMMS16 + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td rowspan="3">UnidirectionalSquenceLstmLayer + <td rowspan="3" style="width:200px;"> Layer to perform unidirectional sequence LSTM operation. + <td rowspan="3"> + <ul> + <li>ANEURALNETWORKS_UNIDIRECTIONAL_SEQUENCE_LSTM + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>Input Types + <tr><td>FLOAT32 + </table> + <table> + <tr><th>Weight Types + <tr><td>FLOAT32 + <tr><td>QASYMMS8 + </table> +<tr> + <td rowspan="3">UnmapLayer + <td rowspan="3" style="width:200px;"> Layer to perform unmap operation on tensor. + <td rowspan="3"> + <ul> + <li>N/A + </ul> + <td>CpuRef + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>CpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +<tr> + <td>GpuAcc + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th> + <tr><td>All + </table> +</table> + +*/ +} // namespace
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