From 05069f07bcf95676597698a79926327555276362 Mon Sep 17 00:00:00 2001 From: Manuel Bottini Date: Thu, 26 Sep 2019 17:18:26 +0100 Subject: COMPMID-2515: Merge optimized depthwise convolution to the generic depthwise convolution function 3RDPARTY_UPDATE Change-Id: Iff9e915c5329c617527b6f5042979f4e21a8b2b8 Signed-off-by: Manuel Bottini Reviewed-on: https://review.mlplatform.org/c/2022 Comments-Addressed: Arm Jenkins Reviewed-by: Giorgio Arena Tested-by: Arm Jenkins Reviewed-by: Georgios Pinitas --- .../CL/functions/CLDepthwiseConvolutionLayer.h | 298 ++++++++++++++++----- 1 file changed, 224 insertions(+), 74 deletions(-) (limited to 'arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h') diff --git a/arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h index 98581a21fe..b8b11f08b2 100644 --- a/arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h +++ b/arm_compute/runtime/CL/functions/CLDepthwiseConvolutionLayer.h @@ -40,151 +40,301 @@ namespace arm_compute { class ICLTensor; -/** Basic function to execute a depthwise convolution for kernel size 3x3xC (when data layout NCHW) or Cx3x3 (when data layout NHWC). This function calls the following OpenCL kernels: - * - * -# @ref CLDepthwiseConvolutionLayer3x3NCHWKernel (if data_layout == NCHW) - * -# @ref CLDepthwiseConvolutionLayer3x3NHWCKernel (if data_layout == NHWC) - * -# @ref CLDepthwiseConvolutionLayerReshapeWeightsKernel (if data_layout == NHWC) - * -# @ref CLFillBorderKernel (if pad_x or pad_y > 0) - * +/** Function to execute a depthwise convolution */ -class CLDepthwiseConvolutionLayer3x3 : public IFunction +class CLDepthwiseConvolutionLayer : public IFunction { public: /** Default constructor */ - CLDepthwiseConvolutionLayer3x3(std::shared_ptr memory_manager = nullptr); + CLDepthwiseConvolutionLayer(std::shared_ptr memory_manager = nullptr); /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLDepthwiseConvolutionLayer3x3(const CLDepthwiseConvolutionLayer3x3 &) = delete; + CLDepthwiseConvolutionLayer(const CLDepthwiseConvolutionLayer &) = delete; /** Default move constructor */ - CLDepthwiseConvolutionLayer3x3(CLDepthwiseConvolutionLayer3x3 &&) = default; + CLDepthwiseConvolutionLayer(CLDepthwiseConvolutionLayer &&) = default; /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLDepthwiseConvolutionLayer3x3 &operator=(const CLDepthwiseConvolutionLayer3x3 &) = delete; + CLDepthwiseConvolutionLayer &operator=(const CLDepthwiseConvolutionLayer &) = delete; /** Default move assignment operator */ - CLDepthwiseConvolutionLayer3x3 &operator=(CLDepthwiseConvolutionLayer3x3 &&) = default; - /** Initialize the function's source, destination, conv and border_size. + CLDepthwiseConvolutionLayer &operator=(CLDepthwiseConvolutionLayer &&) = default; + /** Initialize the function's source, destination, weights and convolution information. * - * @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). - * @param[in] weights Weights tensor. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input. + * @param[in, out] input Source tensor. Data type supported: QASYMM8/FP16/FP32. Data layout supported: NHWC, NCHW + * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input. * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. - * Data type supported: Same as @p input. + * Data type supported: Same as @p input, S32 when input is QASYMM8. * @param[out] output Destination tensor. Data type supported: same as @p input. * @param[in] conv_info Padding and stride information to use for the convolution. * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). */ void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); - /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3 + /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer * - * @param[in] input Source tensor info. Data type supported: QASYMM8 for all layouts, F16/F32 for NCHW. - * @param[in] weights Weights tensor info. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input. + * @param[in] input Source tensor info. Data type supported: QASYMM8/FP16/FP32. Data layout supported: NHWC, NCHW + * @param[in] weights Weights tensor info. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input. * @param[in] biases Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed. * Data type supported: Same as @p input, S32 when input is QASYMM8. * @param[in] output Destination tensor. Data type supported: same as @p input. * @param[in] conv_info Padding and stride information to use for the convolution. * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. - * @param[in] gpu_target (Optional) GPU target to validate the kernel for. Defaults to midgard. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). * * @return a status */ static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, - ActivationLayerInfo act_info = ActivationLayerInfo(), GPUTarget gpu_target = GPUTarget::MIDGARD, const Size2D &dilation = Size2D(1U, 1U)); + ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); + // Inherited methods overriden: void run() override; void prepare() override; private: - MemoryGroup _memory_group; - std::unique_ptr _kernel; - CLFillBorderKernel _border_handler; - CLPermute _permute_input_to_nchw; - CLPermute _permute_weights_to_nchw; - CLPermute _permute_output_to_nhwc; - CLDepthwiseConvolutionLayerReshapeWeightsKernel _reshape_weights; - CLTensor _permuted_input; - CLTensor _permuted_weights; - CLTensor _permuted_output; - const ITensor *_original_weights; - bool _needs_permute; - bool _needs_weights_reshape; - bool _is_prepared; + /** Static function to choose the best depthwise convolution function for @ref CLDepthwiseConvolutionLayer + * + * @param[in] input Source tensor info. Data type supported: QASYMM8/FP16/FP32. Data layout supported: NHWC, NCHW + * @param[in] weights Weights tensor info. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input. + * @param[in] biases Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed. + * Data type supported: Same as @p input, S32 when input is QASYMM8. + * @param[in] output Destination tensor. Data type supported: same as @p input. + * @param[in] conv_info Padding and stride information to use for the convolution. + * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. + * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). + * @param[in] gpu_target (Optional) GPU target to validate the kernel for. Defaults to midgard. + * + * @return a Depthwise Convolution Function + */ + static DepthwiseConvolutionFunction get_depthwiseconvolution_function(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, + const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, + ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U), GPUTarget gpu_target = GPUTarget::MIDGARD); + + /** Basic function to execute a depthwise convolution for kernel size 3x3xC (when data layout NCHW) or Cx3x3 (when data layout NHWC). This function calls the following OpenCL kernels: + * + * -# @ref CLDepthwiseConvolutionLayer3x3NCHWKernel (if data_layout == NCHW) + * -# @ref CLDepthwiseConvolutionLayer3x3NHWCKernel (if data_layout == NHWC) + * -# @ref CLDepthwiseConvolutionLayerReshapeWeightsKernel (if data_layout == NHWC) + * -# @ref CLFillBorderKernel (if pad_x or pad_y > 0) + * + */ + class CLDepthwiseConvolutionLayerInternal3x3 : public IFunction + { + public: + /** Default constructor */ + CLDepthwiseConvolutionLayerInternal3x3(std::shared_ptr memory_manager = nullptr); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDepthwiseConvolutionLayerInternal3x3(const CLDepthwiseConvolutionLayerInternal3x3 &) = delete; + /** Default move constructor */ + CLDepthwiseConvolutionLayerInternal3x3(CLDepthwiseConvolutionLayerInternal3x3 &&) = default; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDepthwiseConvolutionLayerInternal3x3 &operator=(const CLDepthwiseConvolutionLayerInternal3x3 &) = delete; + /** Default move assignment operator */ + CLDepthwiseConvolutionLayerInternal3x3 &operator=(CLDepthwiseConvolutionLayerInternal3x3 &&) = default; + /** Initialize the function's source, destination, conv and border_size. + * + * @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). + * @param[in] weights Weights tensor. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input. + * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. + * Data type supported: Same as @p input. + * @param[out] output Destination tensor. Data type supported: same as @p input. + * @param[in] conv_info Padding and stride information to use for the convolution. + * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. + * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). + */ + void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, + ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); + + /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3 + * + * @param[in] input Source tensor info. Data type supported: QASYMM8 for all layouts, F16/F32 for NCHW. + * @param[in] weights Weights tensor info. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input. + * @param[in] biases Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed. + * Data type supported: Same as @p input, S32 when input is QASYMM8. + * @param[in] output Destination tensor. Data type supported: same as @p input. + * @param[in] conv_info Padding and stride information to use for the convolution. + * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. + * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). + * + * @return a status + */ + static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, + ActivationLayerInfo act_info = ActivationLayerInfo(), GPUTarget gpu_target = GPUTarget::MIDGARD, const Size2D &dilation = Size2D(1U, 1U)); + + // Inherited methods overriden: + void run() override; + void prepare() override; + + void set_memory_group(std::shared_ptr memory_manager) + { + _memory_group = MemoryGroup(std::move(memory_manager)); + }; + + private: + MemoryGroup _memory_group; + std::unique_ptr _kernel; + CLFillBorderKernel _border_handler; + CLPermute _permute_input_to_nchw; + CLPermute _permute_weights_to_nchw; + CLPermute _permute_output_to_nhwc; + CLDepthwiseConvolutionLayerReshapeWeightsKernel _reshape_weights; + CLTensor _permuted_input; + CLTensor _permuted_weights; + CLTensor _permuted_output; + const ITensor *_original_weights; + bool _needs_permute; + bool _needs_weights_reshape; + bool _is_prepared; + }; + + /** Basic function to execute a generic depthwise convolution. This function calls the following OpenCL kernels: + * + * -# @ref CLDepthwiseConvolutionLayerNativeKernel + * -# @ref CLPermute (x 3) if the data layout is NCHW + * + */ + class CLDepthwiseConvolutionLayerGeneric : public IFunction + { + public: + /** Default constructor */ + CLDepthwiseConvolutionLayerGeneric(std::shared_ptr memory_manager = nullptr); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDepthwiseConvolutionLayerGeneric(const CLDepthwiseConvolutionLayerGeneric &) = delete; + /** Default move constructor */ + CLDepthwiseConvolutionLayerGeneric(CLDepthwiseConvolutionLayerGeneric &&) = default; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDepthwiseConvolutionLayerGeneric &operator=(const CLDepthwiseConvolutionLayerGeneric &) = delete; + /** Default move assignment operator */ + CLDepthwiseConvolutionLayerGeneric &operator=(CLDepthwiseConvolutionLayerGeneric &&) = default; + /** Initialize the function's source, destination, weights and convolution information. + * + * @param[in, out] input Source tensor. Data type supported: QASYMM8/F32. (Written to only for border filling). + * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input. + * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. + * Data type supported: Same as @p input, S32 when input is QASYMM8. + * @param[out] output Destination tensor. Data type supported: same as @p input. + * @param[in] conv_info Padding and stride information to use for the convolution. + * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. + * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). + */ + void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, + unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); + + /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayerGeneric + * + * @param[in] input Source tensor info. Data type supported: QASYMM8/F32. + * @param[in] weights Weights tensor info. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input. + * @param[in] biases Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed. + * Data type supported: Same as @p input, S32 when input is QASYMM8. + * @param[in] output Destination tensor. Data type supported: same as @p input. + * @param[in] conv_info Padding and stride information to use for the convolution. + * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. + * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). + * + * @return a status + */ + static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, + unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); + + // Inherited methods overriden: + void run() override; + void prepare() override; + + void set_memory_group(std::shared_ptr memory_manager) + { + _memory_group = MemoryGroup(std::move(memory_manager)); + }; + + private: + MemoryGroup _memory_group; + + CLDepthwiseConvolutionLayerNativeKernel _dwc_native_kernel; + CLPermute _permute_input_to_nhwc; + CLPermute _permute_weights_to_nhwc; + CLPermute _permute_output_to_nchw; + + CLTensor _permuted_input; + CLTensor _permuted_weights; + CLTensor _permuted_output; + const ITensor *_original_weights; + + bool _needs_permute; + bool _is_prepared; + }; + + std::shared_ptr _memory_manager; + + DepthwiseConvolutionFunction _depth_conv_func; + CLDepthwiseConvolutionLayerInternal3x3 _func_3x3; + CLDepthwiseConvolutionLayerGeneric _func_generic; }; -/** Basic function to execute a generic depthwise convolution. This function calls the following OpenCL kernels: +/** Basic function to execute a depthwise convolution for kernel size 3x3xC (when data layout NCHW) or Cx3x3 (when data layout NHWC). This function calls the following OpenCL kernels: * - * -# @ref CLDepthwiseConvolutionLayerNativeKernel - * -# @ref CLPermute (x 3) if the data layout is NCHW + * -# @ref CLDepthwiseConvolutionLayer3x3NCHWKernel (if data_layout == NCHW) + * -# @ref CLDepthwiseConvolutionLayer3x3NHWCKernel (if data_layout == NHWC) + * -# @ref CLDepthwiseConvolutionLayerReshapeWeightsKernel (if data_layout == NHWC) + * -# @ref CLFillBorderKernel (if pad_x or pad_y > 0) * */ -class CLDepthwiseConvolutionLayer : public IFunction +class CLDepthwiseConvolutionLayer3x3 : public IFunction { public: /** Default constructor */ - CLDepthwiseConvolutionLayer(std::shared_ptr memory_manager = nullptr); + CLDepthwiseConvolutionLayer3x3(std::shared_ptr memory_manager = nullptr); /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLDepthwiseConvolutionLayer(const CLDepthwiseConvolutionLayer &) = delete; + CLDepthwiseConvolutionLayer3x3(const CLDepthwiseConvolutionLayer3x3 &) = delete; /** Default move constructor */ - CLDepthwiseConvolutionLayer(CLDepthwiseConvolutionLayer &&) = default; + CLDepthwiseConvolutionLayer3x3(CLDepthwiseConvolutionLayer3x3 &&) = default; /** Prevent instances of this class from being copied (As this class contains pointers) */ - CLDepthwiseConvolutionLayer &operator=(const CLDepthwiseConvolutionLayer &) = delete; + CLDepthwiseConvolutionLayer3x3 &operator=(const CLDepthwiseConvolutionLayer3x3 &) = delete; /** Default move assignment operator */ - CLDepthwiseConvolutionLayer &operator=(CLDepthwiseConvolutionLayer &&) = default; - /** Initialize the function's source, destination, weights and convolution information. + CLDepthwiseConvolutionLayer3x3 &operator=(CLDepthwiseConvolutionLayer3x3 &&) = default; + /** Initialize the function's source, destination, conv and border_size. * - * @param[in, out] input Source tensor. Data type supported: QASYMM8/F32. (Written to only for border filling). - * @param[in] weights Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input. + * @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling). + * @param[in] weights Weights tensor. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input. * @param[in] biases Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed. - * Data type supported: Same as @p input, S32 when input is QASYMM8. + * Data type supported: Same as @p input. * @param[out] output Destination tensor. Data type supported: same as @p input. * @param[in] conv_info Padding and stride information to use for the convolution. * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). */ - void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); + ARM_COMPUTE_DEPRECATED_REL_REPLACE(20.02, CLDepthwiseConvolutionLayer) + void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, + ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); - /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer + /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3 * - * @param[in] input Source tensor info. Data type supported: QASYMM8/F32. - * @param[in] weights Weights tensor info. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input. + * @param[in] input Source tensor info. Data type supported: QASYMM8 for all layouts, F16/F32 for NCHW. + * @param[in] weights Weights tensor info. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input. * @param[in] biases Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed. * Data type supported: Same as @p input, S32 when input is QASYMM8. * @param[in] output Destination tensor. Data type supported: same as @p input. * @param[in] conv_info Padding and stride information to use for the convolution. * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1. - * @param[in] act_info (Optional) Activation layer information in case of a fused activation. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported. + * @param[in] gpu_target (Optional) GPU target to validate the kernel for. Defaults to midgard. * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). * * @return a status */ - static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U)); + static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1, + ActivationLayerInfo act_info = ActivationLayerInfo(), GPUTarget gpu_target = GPUTarget::MIDGARD, const Size2D &dilation = Size2D(1U, 1U)); // Inherited methods overriden: void run() override; void prepare() override; private: - MemoryGroup _memory_group; - - std::unique_ptr _optimised_function; - CLDepthwiseConvolutionLayerNativeKernel _dwc_native_kernel; - CLPermute _permute_input_to_nhwc; - CLPermute _permute_weights_to_nhwc; - CLPermute _permute_output_to_nchw; - - CLTensor _permuted_input; - CLTensor _permuted_weights; - CLTensor _permuted_output; - const ITensor *_original_weights; - - bool _needs_permute; - bool _is_prepared; + CLDepthwiseConvolutionLayer _func; }; } // namespace arm_compute #endif /*__ARM_COMPUTE_CLDEPTHWISECONVOLUTION_H__ */ -- cgit v1.2.1