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| author | Georgios Pinitas <georgios.pinitas@arm.com> | 2018-07-17 12:28:42 +0100 |
|---|---|---|
| committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:54:54 +0000 |
| commit | 7d66a8e3f603f2cd363f04a750847e3f9eabdfd4 (patch) | |
| tree | 0d7e1ad5bf0ecd32cd919074f756d27c351d7638 /arm_compute/core | |
| parent | ae54e026c86aec7d6819ee3ef76372c1a3c92467 (diff) | |
| download | ComputeLibrary-7d66a8e3f603f2cd363f04a750847e3f9eabdfd4.tar.gz | |
COMPMID-1386: Add support for converting weights for CL.
Change-Id: I62e3ead903366baeeb1488f233a9b8b0c388c9de
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/140403
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'arm_compute/core')
| -rw-r--r-- | arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h | 4 | ||||
| -rw-r--r-- | arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h | 4 | ||||
| -rw-r--r-- | arm_compute/core/Types.h | 9 |
3 files changed, 13 insertions, 4 deletions
diff --git a/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h b/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h index b85f93e992..40c9dc826f 100644 --- a/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h +++ b/arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h @@ -57,7 +57,7 @@ public: * * @param[in] input Source weights tensor to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32. * @param[out] output The converted weights tensor. Shape and Data Type: Same as @p input. - * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). Must be in NCHW format. + * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). * @param[in] data_layout The data layout the weights have been trained in. */ void configure(const ICLTensor *input, ICLTensor *output, const TensorShape &original_input_shape, DataLayout data_layout); @@ -65,7 +65,7 @@ public: * * @param[in] input Source weights tensor info to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32. * @param[in] output The converted weights tensor info. Shape and Data Type: Same as @p input. - * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). Must be in NCHW format. + * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). * @param[in] data_layout The data layout the weights have been trained in. */ static Status validate(const ITensorInfo *input, const ITensorInfo *output, const TensorShape &original_input_shape, DataLayout data_layout); diff --git a/arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h b/arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h index 1a276c353e..5b8d7fd457 100644 --- a/arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h +++ b/arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h @@ -61,7 +61,7 @@ public: * * @param[in] input Source weights tensor to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32. * @param[out] output The converted weights tensor. Shape and Data Type: Same as @p input. - * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). Must be in NCHW format. + * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). * @param[in] data_layout The data layout the weights have been trained in. */ void configure(const ITensor *input, ITensor *output, const TensorShape &original_input_shape, DataLayout data_layout); @@ -69,7 +69,7 @@ public: * * @param[in] input Source weights tensor info to convert. Must be 2 dimensional. Data types supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32. * @param[in] output The converted weights tensor info. Shape and Data Type: Same as @p input. - * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). Must be in NCHW format. + * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer). * @param[in] data_layout The data layout the weights have been trained in. */ static Status validate(const ITensorInfo *input, const ITensorInfo *output, const TensorShape &original_input_shape, DataLayout data_layout); diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h index 1363324e3b..343952f0b2 100644 --- a/arm_compute/core/Types.h +++ b/arm_compute/core/Types.h @@ -682,6 +682,15 @@ private: DimensionRoundingType _round_type; }; +/** Fully connected layer info */ +struct FullyConnectedLayerInfo +{ + DataLayout weights_trained_layout{ DataLayout::NCHW }; /**< Layout that the weights have been trained with. */ + bool transpose_weights{ true }; /**< Transpose weights if true. */ + bool are_weights_reshaped{ false }; /**< Reshape the weights tensor if false. */ + bool retain_internal_weights{ false }; /**< Retain internal reshaped weights. */ +}; + /** Pooling Layer Information class */ class PoolingLayerInfo { |