diff options
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 | |
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')
10 files changed, 67 insertions, 54 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 { diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h index 16536bcb65..978d3bc1a8 100644 --- a/arm_compute/graph/backends/FunctionHelpers.h +++ b/arm_compute/graph/backends/FunctionHelpers.h @@ -524,10 +524,11 @@ std::unique_ptr<IFunction> create_fully_connected_layer(FullyConnectedLayerNode typename TargetInfo::TensorType *weights = get_backing_tensor<TargetInfo>(node.input(1)); typename TargetInfo::TensorType *biases = get_backing_tensor<TargetInfo>(node.input(2)); typename TargetInfo::TensorType *output = get_backing_tensor<TargetInfo>(node.output(0)); + const FullyConnectedLayerInfo fc_info = node.info(); // Create and configure function auto func = support::cpp14::make_unique<FullyConnectedLayerFunction>(get_memory_manager(ctx, TargetInfo::TargetType)); - func->configure(input, weights, biases, output); + func->configure(input, weights, biases, output, fc_info); ARM_COMPUTE_ERROR_ON(input == nullptr); ARM_COMPUTE_ERROR_ON(weights == nullptr); ARM_COMPUTE_ERROR_ON(output == nullptr); diff --git a/arm_compute/graph/nodes/FullyConnectedLayerNode.h b/arm_compute/graph/nodes/FullyConnectedLayerNode.h index 3d1b68909a..79201c8bdc 100644 --- a/arm_compute/graph/nodes/FullyConnectedLayerNode.h +++ b/arm_compute/graph/nodes/FullyConnectedLayerNode.h @@ -37,8 +37,9 @@ public: /** Constructor * * @param[in] num_outputs Number of neurons in the layer + * @param[in] fc_info (Optional) Additional information about the fully connected layer */ - FullyConnectedLayerNode(unsigned int num_outputs); + FullyConnectedLayerNode(unsigned int num_outputs, FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo()); /** Computes weights descriptor * * @warning Works for inputs with 1D batch space @@ -59,6 +60,11 @@ public: * @return Output descriptor */ static TensorDescriptor compute_output_descriptor(const TensorDescriptor &input_descriptor, unsigned int num_outputs); + /** Fully connected layer addition information + * + * @return Additional information about the fully connected layer + */ + FullyConnectedLayerInfo info() const; // Inherited overridden methods: NodeType type() const override; @@ -67,7 +73,8 @@ public: void accept(INodeVisitor &v) override; private: - unsigned int _num_outputs; + unsigned int _num_outputs; + FullyConnectedLayerInfo _info; }; } // namespace graph } // namespace arm_compute diff --git a/arm_compute/runtime/CL/functions/CLConvertFullyConnectedWeights.h b/arm_compute/runtime/CL/functions/CLConvertFullyConnectedWeights.h index 77e9d15e7f..9bfade4894 100644 --- a/arm_compute/runtime/CL/functions/CLConvertFullyConnectedWeights.h +++ b/arm_compute/runtime/CL/functions/CLConvertFullyConnectedWeights.h @@ -39,7 +39,7 @@ 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); @@ -47,7 +47,7 @@ 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/runtime/CL/functions/CLFullyConnectedLayer.h b/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h index 3357868968..6b8d7a97ec 100644 --- a/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h +++ b/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h @@ -31,6 +31,7 @@ #include "arm_compute/core/CL/kernels/CLTransposeKernel.h" #include "arm_compute/runtime/CL/CLMemoryGroup.h" #include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/CL/functions/CLConvertFullyConnectedWeights.h" #include "arm_compute/runtime/CL/functions/CLGEMM.h" #include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h" #include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h" @@ -86,32 +87,26 @@ public: CLFullyConnectedLayer &operator=(CLFullyConnectedLayer &&) = default; /** Set the input and output tensors. * - * @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. - * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input - * @param[in] biases Bias tensor. It can be nullptr. Data type supported:Same as @p input. - * @param[out] output Destination tensor. Data type supported: Same as @p input. - * @param[in] transpose_weights (Optional) Transpose weights if true. Defaults to true. - * @param[in] are_weights_reshaped (Optional) Reshape the weights tensor if false. Defaults to false. - * @param[in] retain_internal_weights (Optional) Retain internal reshaped weights. Defaults to false. - * Used for reconfiguration purposes. + * @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. + * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input + * @param[in] biases Bias tensor. It can be nullptr. Data type supported:Same as @p input. + * @param[out] output Destination tensor. Data type supported: Same as @p input. + * @param[in] fc_info (Optional) Fully connected layer additional info */ - void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, bool transpose_weights = true, bool are_weights_reshaped = false, - bool retain_internal_weights = false); + void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, + FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo()); /** Static function to check if given info will lead to a valid configuration of @ref CLFullyConnectedLayer * - * @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. - * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input - * @param[in] biases Bias tensor. It can be nullptr. Data type supported:Same as @p input. - * @param[in] output Destination tensor. Data type supported: Same as @p input. - * @param[in] transpose_weights (Optional) Transpose weights if true. Defaults to true. - * @param[in] are_weights_reshaped (Optional) Reshape the weights tensor if false. Defaults to false. - * @param[in] retain_internal_weights (Optional) Retain internal reshaped weights. Defaults to false. - * Used for reconfiguration purposes. + * @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. + * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input + * @param[in] biases Bias tensor. It can be nullptr. Data type supported:Same as @p input. + * @param[in] output Destination tensor. Data type supported: Same as @p input. + * @param[in] fc_info (Optional) Fully connected layer additional info * * @return a status */ - static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, bool transpose_weights = true, bool are_weights_reshaped = false, - bool retain_internal_weights = false); + static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, + FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo()); //Inherited methods override void run() override; @@ -124,6 +119,7 @@ private: CLMemoryGroup _memory_group; CLIm2ColKernel _im2col_kernel; + CLConvertFullyConnectedWeights _convert_weights; CLFullyConnectedLayerReshapeWeights _reshape_weights_kernel; CLGEMM _mm_gemm; CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp; @@ -131,11 +127,14 @@ private: CLGEMMMatrixAccumulateBiasesKernel _accumulate_biases_kernel; CLTensor _im2col_output; CLTensor _gemmlowp_output; + CLTensor _converted_weights_output; CLTensor _reshape_weights_output; + bool _are_weights_converted; bool _are_weights_reshaped; bool _is_fc_after_conv; bool _accumulate_biases; bool _is_quantized; + bool _is_prepared; const ICLTensor *_original_weights; }; } diff --git a/arm_compute/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.h b/arm_compute/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.h index cd108c3eab..63565df1a7 100644 --- a/arm_compute/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.h +++ b/arm_compute/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.h @@ -75,17 +75,14 @@ public: GCFullyConnectedLayer &operator=(GCFullyConnectedLayer &&) = default; /** Set the input and output tensors. * - * @param[in] input Source tensor. Data type supported: F16/F32. - * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input - * @param[in] biases Bias tensor. It can be nullptr. Data type supported:Same as @p input. - * @param[out] output Destination tensor. Data type supported: Same as @p input. - * @param[in] transpose_weights (Optional) Transpose weights if true. Defaults to true. - * @param[in] are_weights_reshaped (Optional) Reshape the weights tensor if false. Defaults to false. - * @param[in] retain_internal_weights (Optional) Retain internal reshaped weights. Defaults to false. - * Used for reconfiguration purposes. + * @param[in] input Source tensor. Data type supported: F16/F32. + * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input + * @param[in] biases Bias tensor. It can be nullptr. Data type supported:Same as @p input. + * @param[out] output Destination tensor. Data type supported: Same as @p input. + * @param[in] fc_info (Optional) Fully connected layer additional info */ void configure(const IGCTensor *input, const IGCTensor *weights, const IGCTensor *biases, IGCTensor *output, - bool transpose_weights = true, bool are_weights_reshaped = false, bool retain_internal_weights = false); + FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo()); //Inherited methods override void run() override; diff --git a/arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h b/arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h index acbba28040..8f261421e6 100644 --- a/arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h +++ b/arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h @@ -42,7 +42,7 @@ 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); @@ -50,7 +50,7 @@ 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/runtime/NEON/functions/NEFullyConnectedLayer.h b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h index 33ac8ecb8a..ea0762ea79 100644 --- a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h +++ b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h @@ -104,26 +104,26 @@ public: NEFullyConnectedLayer &operator=(NEFullyConnectedLayer &&) = default; /** Set the input and output tensors. * - * @param[in] input Source tensor. Data type supported: F16/F32. - * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input. - * @param[in] biases Bias tensor. Can be nullptr. Data type supported:Same as @p input. - * @param[out] output Destination tensor. Data type supported: Same as @p input. - * @param[in] transpose_weights (Optional) Transpose the weights tensor if true. Defaults to true. - * @param[in] are_weights_reshaped (Optional) Reshape the weights tensor if false. Defaults to false. + * @param[in] input Source tensor. Data type supported: F16/F32. + * @param[in] weights Weights tensor. The weights must be 2 dimensional. Data type supported: Same as @p input. + * @param[in] biases Bias tensor. Can be nullptr. Data type supported:Same as @p input. + * @param[out] output Destination tensor. Data type supported: Same as @p input. + * @param[in] fc_info (Optional) Fully connected layer additional info */ - void configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, bool transpose_weights = true, bool are_weights_reshaped = false); + void configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, + FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo()); /** Static function to check if given info will lead to a valid configuration of @ref CLFullyConnectedLayer * - * @param[in] input Source tensor info. Data type supported: F16/F32. - * @param[in] weights Weights tensor info. The weights must be 2 dimensional. Data type supported: Same as @p input - * @param[in] biases Bias tensor info. It can be nullptr. Data type supported:Same as @p input. - * @param[in] output Destination tensor info. Data type supported: Same as @p input. - * @param[in] transpose_weights (Optional) Transpose weights if true. Defaults to true. - * @param[in] are_weights_reshaped (Optional) Reshape the weights tensor if false. Defaults to false. + * @param[in] input Source tensor info. Data type supported: F16/F32. + * @param[in] weights Weights tensor info. The weights must be 2 dimensional. Data type supported: Same as @p input + * @param[in] biases Bias tensor info. It can be nullptr. Data type supported:Same as @p input. + * @param[in] output Destination tensor info. Data type supported: Same as @p input. + * @param[in] fc_info (Optional) Fully connected layer additional info * * @return a status */ - static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, bool transpose_weights = true, bool are_weights_reshaped = false); + static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, + FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo()); //Inherited methods override void run() override; |