diff options
Diffstat (limited to 'arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h')
| -rw-r--r-- | arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h | 270 |
1 files changed, 68 insertions, 202 deletions
diff --git a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h index 6d1181eefe..70ceb1513b 100644 --- a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h +++ b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 ARM Limited. + * Copyright (c) 2017-2021, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -21,146 +21,28 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ -#ifndef ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H -#define ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H +#ifndef ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLGEMMCONVOLUTIONLAYER_H +#define ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLGEMMCONVOLUTIONLAYER_H -#include "arm_compute/runtime/IFunction.h" - -#include "arm_compute/core/CL/kernels/CLCol2ImKernel.h" -#include "arm_compute/core/CL/kernels/CLIm2ColKernel.h" -#include "arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h" -#include "arm_compute/core/Types.h" +#include "arm_compute/function_info/ActivationLayerInfo.h" #include "arm_compute/runtime/CL/CLTensor.h" -#include "arm_compute/runtime/CL/functions/CLActivationLayer.h" -#include "arm_compute/runtime/CL/functions/CLGEMM.h" -#include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h" +#include "arm_compute/runtime/CL/CLTypes.h" +#include "arm_compute/runtime/IFunction.h" #include "arm_compute/runtime/IMemoryManager.h" -#include "arm_compute/runtime/ITransformWeights.h" #include "arm_compute/runtime/IWeightsManager.h" -#include "arm_compute/runtime/MemoryGroup.h" #include <memory> namespace arm_compute { +// Forward declarations +class CLCompileContext; class ICLTensor; - -/** Function to reshape and transpose the weights. This function calls the following kernels: - * -# @ref CLWeightsReshapeKernel - */ -class CLConvolutionLayerReshapeWeights : public IFunction -{ -public: - /** Constructor */ - CLConvolutionLayerReshapeWeights(); - /** Set the input and output tensors. - * - * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. - * Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32. - * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. - * @param[out] output Destination tensor. Data types supported: Same as @p weights. - * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout - */ - void configure(const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups = 1); - /** Set the input and output tensors. - * - * @param[in] compile_context The compile context to be used. - * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. - * Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32. - * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. - * @param[out] output Destination tensor. Data types supported: Same as @p weights. - * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout - */ - void configure(const CLCompileContext &compile_context, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups = 1); - /** Static function to check if given info will lead to a valid configuration of @ref CLConvolutionLayerReshapeWeights - * - * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. - * Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/F16/F32. - * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. - * @param[in] output Destination tensor. Data types supported: Same as @p weights. - * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout - * - * @return a status - */ - static Status validate(const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, unsigned int num_groups = 1); - // Inherited methods overridden: - void run() override; - -private: - CLWeightsReshapeKernel _weights_reshape_kernel; -}; - -namespace weights_transformations -{ -/** Basic function to manage the reshape weights generated from @ref CLConvolutionLayerReshapeWeights */ -class CLConvolutionLayerReshapeWeightsTransform : public ITransformWeights -{ -public: - /** Configures the @ref CLConvolutionLayerReshapeWeights function - * - * @param[in] input Input tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32. - * @param[in] biases Biases tensor. Data type supported: Same as @p input. - * @param[in] num_groups Number of groups when performing a grouped convolution. - */ - void configure(const ICLTensor *input, const ICLTensor *biases, unsigned int num_groups) - { - configure(CLKernelLibrary::get().get_compile_context(), input, biases, num_groups); - } - /** Configures the @ref CLConvolutionLayerReshapeWeights function - * - * @param[in] compile_context The compile context to be used. - * @param[in] input Input tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32. - * @param[in] biases Biases tensor. Data type supported: Same as @p input. - * @param[in] num_groups Number of groups when performing a grouped convolution. - */ - void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *biases, unsigned int num_groups) - { - _bias_bit = (biases != nullptr) ? 1 : 0; - _num_groups = num_groups; - _func.configure(compile_context, input, biases, &_output, num_groups); - } - - //Inherited method override - void run() override - { - _output.allocator()->allocate(); - _func.run(); - _reshape_run = true; - } - - //Inherited method override - ICLTensor *get_weights() override - { - return &_output; - } - - //Inherited method override - void release() override - { - _output.allocator()->free(); - } - - //Inherited method override - uint32_t uid() override - { - return ((0x9) | (_bias_bit << 7) | (_num_groups << 8)); - } - -private: - CLTensor _output{}; - CLConvolutionLayerReshapeWeights _func{}; - int32_t _bias_bit{ 0 }; - unsigned int _num_groups{ 0 }; -}; -} // namespace weights_transformations +class ITensorInfo; /** Basic function to compute the convolution layer. This function calls the following OpenCL kernels/functions: * - * -# @ref CLIm2ColKernel - * -# @ref CLGEMM (if the data type is FP32 or FP16) - * -# @ref CLGEMMLowpMatrixMultiplyCore (if the data type is QASYMM8) - * -# @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint (if the data type is QASYMM8) - * -# @ref CLCol2ImKernel (if NCHW data layout) + * -# @ref opencl::ClGemmConv2d */ class CLGEMMConvolutionLayer : public IFunction { @@ -170,7 +52,8 @@ public: * @param[in] memory_manager (Optional) Memory manager. * @param[in] weights_manager (Optional) Weights manager. */ - CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr, IWeightsManager *weights_manager = nullptr); + CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr, + IWeightsManager *weights_manager = nullptr); /** Prevent instances of this class from being copied (As this class contains pointers) */ CLGEMMConvolutionLayer(const CLGEMMConvolutionLayer &) = delete; /** Default move constructor */ @@ -179,15 +62,31 @@ public: CLGEMMConvolutionLayer &operator=(const CLGEMMConvolutionLayer &) = delete; /** Default move assignment operator */ CLGEMMConvolutionLayer &operator=(CLGEMMConvolutionLayer &&) = default; + /**Default destructor */ + ~CLGEMMConvolutionLayer(); /** Set the input and output tensors. * + * Valid data layouts: + * - NHWC + * - NCHW + * + * Valid data type configurations: + * |src0 |src1 |src2 |dst | + * |:--------------|:------------------|:--------|:--------------| + * |F16 |F16 |F16 |F16 | + * |F32 |F32 |F32 |F32 | + * |QASYMM8 |QASYMM8 |S32 |QASYMM8 | + * |QASYMM8 |QSYMM8_PER_CHANNEL |S32 |QASYMM8 | + * |QASYMM8_SIGNED |QASYMM8_SIGNED |S32 |QASYMM8_SIGNED | + * |QASYMM8_SIGNED |QSYMM8_PER_CHANNEL |S32 |QASYMM8_SIGNED | + * * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], * while every optional dimension from 4 and above represent a batch of inputs. - * Data types supported: QASYMM8/F16/F32. + * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. - * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8. + * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED. * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. - * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type. + * Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type. * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. * Data types supported: Same as @p input. * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. @@ -197,18 +96,25 @@ public: * @param[in] act_info (Optional) Activation layer information in case of a fused activation. * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout */ - void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo(), - const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1); + void configure(const ICLTensor *input, + const ICLTensor *weights, + const ICLTensor *biases, + ICLTensor *output, + const PadStrideInfo &conv_info, + const WeightsInfo &weights_info = WeightsInfo(), + const Size2D &dilation = Size2D(1U, 1U), + const ActivationLayerInfo &act_info = ActivationLayerInfo(), + unsigned int num_groups = 1); /** Set the input and output tensors. * * @param[in] compile_context The compile context to be used. * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], * while every optional dimension from 4 and above represent a batch of inputs. - * Data types supported: QASYMM8/F16/F32. + * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. - * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8. + * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED. * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. - * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type. + * Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type. * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. * Data types supported: Same as @p input. * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. @@ -218,18 +124,25 @@ public: * @param[in] act_info (Optional) Activation layer information in case of a fused activation. * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout */ - void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, - const WeightsInfo &weights_info = WeightsInfo(), - const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1); + void configure(const CLCompileContext &compile_context, + const ICLTensor *input, + const ICLTensor *weights, + const ICLTensor *biases, + ICLTensor *output, + const PadStrideInfo &conv_info, + const WeightsInfo &weights_info = WeightsInfo(), + const Size2D &dilation = Size2D(1U, 1U), + const ActivationLayerInfo &act_info = ActivationLayerInfo(), + unsigned int num_groups = 1); /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer. * * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], * while every optional dimension from 4 and above represent a batch of inputs. - * Data types supported: QASYMM8/F16/F32. + * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. - * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8. + * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED. * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. - * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type. + * Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type. * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. * Data types supported: Same as @p input. * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. @@ -241,70 +154,23 @@ public: * * @return a status */ - static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1); + static Status validate(const ITensorInfo *input, + const ITensorInfo *weights, + const ITensorInfo *biases, + const ITensorInfo *output, + const PadStrideInfo &conv_info, + const WeightsInfo &weights_info = WeightsInfo(), + const Size2D &dilation = Size2D(1U, 1U), + const ActivationLayerInfo &act_info = ActivationLayerInfo(), + unsigned int num_groups = 1); // Inherited methods overridden: void run() override; void prepare() override; private: - /** Configures the appropriate matrix multiply routine - * - * @param[in] compile_context The compile context to be used. - * @param[in] input Input tensor. Data types supported: QASYMM8/F16/F32. - * @param[in] weights Weights tensor. Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8. - * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. - * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type. - * @param[in, out] output Output tensor. Data types supported: Same as @p input, - * except for input of QASYMM8 type where output should be of S32 type. - * @param[in] gemmlowp_output_stage GEMMLowp output stage info - * @param[in] gemm_3d_depth Depth of GEMM 3D - * @param[in] act_info Activation to apply after the matrix multiplication - */ - void configure_mm(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, - const GEMMLowpOutputStageInfo &gemmlowp_output_stage, - int gemm_3d_depth, const ActivationLayerInfo &act_info); - /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer matrix multiply routines - * - * @param[in] input Input tensor info. Data types supported: QASYMM8/F16/F32. - * @param[in] weights Weights tensor info. Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8. - * @param[in] biases Biases tensor info. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. - * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type. - * @param[in] output Output tensor info. Data types supported: Same as @p input, - * except for input of QASYMM8 type where output should be of S32 type. - * @param[in] gemmlowp_output_stage GEMMLowp output stage info - * @param[in] gemm_3d_depth Depth of GEMM 3D - * @param[in] skip_im2col Flag which specifies if im2col has to be skipped. i.e. 1x1 convolution with NHWC data layout. - * @param[in] act_info Activation to apply after the matrix multiplication - * - * @return a status - */ - static Status validate_mm(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const GEMMLowpOutputStageInfo &gemmlowp_output_stage, - int gemm_3d_depth, bool skip_im2col, const ActivationLayerInfo &act_info); - -private: - MemoryGroup _memory_group; - IWeightsManager *_weights_manager; - CLConvolutionLayerReshapeWeights _reshape_weights; - weights_transformations::CLConvolutionLayerReshapeWeightsTransform _reshape_weights_managed; - CLIm2ColKernel _im2col_kernel; - CLGEMM _mm_gemm; - CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp; - CLCol2ImKernel _col2im_kernel; - CLActivationLayer _activationlayer_function; - - const ICLTensor *_original_weights; - - CLTensor _im2col_output; - CLTensor _weights_reshaped; - CLTensor _gemm_output; - - bool _skip_im2col; - bool _skip_col2im; - bool _is_quantized; - bool _fuse_activation; - bool _is_prepared; + struct Impl; + std::unique_ptr<Impl> _impl; }; } // namespace arm_compute -#endif /* ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H */ +#endif // ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLGEMMCONVOLUTIONLAYER_H |