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/*
* Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef __ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H__
#define __ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H__
#include "arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayer3x3Kernel.h"
#include "arm_compute/core/NEON/kernels/NEDepthwiseIm2ColKernel.h"
#include "arm_compute/core/NEON/kernels/NEDepthwiseVectorToTensorKernel.h"
#include "arm_compute/core/NEON/kernels/NEDepthwiseWeightsReshapeKernel.h"
#include "arm_compute/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h"
#include "arm_compute/core/NEON/kernels/NEFillBorderKernel.h"
#include "arm_compute/core/NEON/kernels/NEGEMMMatrixVectorMultiplyKernel.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/IMemoryManager.h"
#include "arm_compute/runtime/MemoryGroup.h"
#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
#include "arm_compute/runtime/NEON/functions/NEPermute.h"
#include "arm_compute/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.h"
#include "arm_compute/runtime/Tensor.h"
namespace arm_compute
{
class ITensor;
/** Basic function to execute a depthwise convolution for kernel size 3x3xC. This function calls the following NEON kernels:
*
* -# @ref NEDepthwiseConvolutionLayer3x3
* -# @ref NEFillBorderKernel (if pad_x or pad_y > 0)
*
*/
class NEDepthwiseConvolutionLayer3x3 : public IFunction
{
public:
/** Default constructor */
NEDepthwiseConvolutionLayer3x3(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEDepthwiseConvolutionLayer3x3(const NEDepthwiseConvolutionLayer3x3 &) = delete;
/** Default move constructor */
NEDepthwiseConvolutionLayer3x3(NEDepthwiseConvolutionLayer3x3 &&) = default;
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEDepthwiseConvolutionLayer3x3 &operator=(const NEDepthwiseConvolutionLayer3x3 &) = delete;
/** Default move assignment operator */
NEDepthwiseConvolutionLayer3x3 &operator=(NEDepthwiseConvolutionLayer3x3 &&) = default;
/** Initialize the function's source, destination, kernels 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. These are 3D tensors 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.
* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). Currently supports (1,1) only.
*/
void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *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 NEDepthwiseConvolutionLayer3x3
*
* @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
* @param[in] weights Weights tensor. These are 3D tensors 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[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). Currently supports (1,1) only.
*
* @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;
private:
/** Configure the kernels/functions for the generic pipeline.
*
* @param[in, out] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
* @param[in] weights Weights tensor. These are 3D tensors 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 Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
* @param[in] act_info Activation layer information in case of a fused activation.
*/
void configure_generic(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info,
unsigned int depth_multiplier, const ActivationLayerInfo &act_info);
/** Configure the kernels/functions for the optimized pipeline.
*
* @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
* @param[in] weights Weights tensor. These are 3D tensors 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 Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
* @param[in] act_info Activation layer information in case of a fused activation.
*/
void configure_optimized(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info,
unsigned int depth_multiplier, const ActivationLayerInfo &act_info);
/** Run generic kernel */
void run_generic();
/** Run optimized function */
void run_optimized();
private:
MemoryGroup _memory_group;
NEDepthwiseConvolutionLayer3x3Kernel _dwc_kernel;
NEDepthwiseConvolutionAssemblyDispatch _dwc_optimized_func;
NEDirectConvolutionLayerOutputStageKernel _output_stage_kernel;
NEFillBorderKernel _border_handler;
NEPermute _permute_input;
NEPermute _permute_weights;
NEPermute _permute_output;
NEActivationLayer _activationlayer_function;
Tensor _accumulator;
Tensor _permuted_input;
Tensor _permuted_weights;
Tensor _permuted_output;
const ITensor *_original_weights;
bool _has_bias;
bool _is_quantized;
bool _is_optimized;
bool _is_nchw;
bool _permute;
bool _is_activationlayer_enabled;
bool _is_prepared;
};
/** Basic function to execute a generic depthwise convolution. This function calls the following NEON kernels:
*
* -# @ref NEDepthwiseIm2ColKernel
* -# @ref NEDepthwiseWeightsReshapeKernel
* -# @ref NEGEMMMatrixVectorMultiplyKernel
* -# @ref NEFillBorderKernel (if pad_x or pad_y > 0)
*
*/
class NEDepthwiseConvolutionLayer : public IFunction
{
public:
/** Default constructor */
NEDepthwiseConvolutionLayer();
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEDepthwiseConvolutionLayer(const NEDepthwiseConvolutionLayer &) = delete;
/** Default move constructor */
NEDepthwiseConvolutionLayer(NEDepthwiseConvolutionLayer &&) = default;
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEDepthwiseConvolutionLayer &operator=(const NEDepthwiseConvolutionLayer &) = delete;
/** Default move assignment operator */
NEDepthwiseConvolutionLayer &operator=(NEDepthwiseConvolutionLayer &&) = 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[out] output Destination tensor. Data type supported: same as @p input.
* @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 (Optional) 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[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). Currently supports (1,1) only.
*/
void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *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 NEDepthwiseConvolutionLayer
*
* @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
* @param[in] output Destination tensor. Data type supported: same as @p input.
* @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 (Optional) 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[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). Currently supports (1,1) only.
*
* @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;
private:
NEDepthwiseIm2ColKernel _im2col_kernel;
NEDepthwiseWeightsReshapeKernel _weights_reshape_kernel;
NEGEMMMatrixVectorMultiplyKernel _v2mm_kernel;
NEDepthwiseVectorToTensorKernel _vector_to_tensor_kernel;
NEDirectConvolutionLayerOutputStageKernel _output_stage_kernel;
NEFillBorderKernel _v2mm_input_fill_border;
NEFillBorderKernel _v2mm_weights_fill_border;
NEPermute _permute_input;
NEPermute _permute_weights;
NEPermute _permute_output;
NEActivationLayer _activationlayer_function;
Tensor _input_reshaped;
Tensor _weights_reshaped;
Tensor _v2mm_output;
Tensor _output_reshaped;
Tensor _permuted_input;
Tensor _permuted_weights;
Tensor _permuted_output;
bool _is_prepared;
bool _is_quantized;
bool _is_nhwc;
bool _is_activationlayer_enabled;
const ITensor *_original_weights;
};
} // namespace arm_compute
#endif /* __ARM_COMPUTE_NEDEPTHWISECONVOLUTION_H__ */
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