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/*
* Copyright (c) 2019-2020 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_NEFFTCONVOLUTIONLAYER_H
#define ARM_COMPUTE_NEFFTCONVOLUTIONLAYER_H
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
#include "arm_compute/runtime/NEON/functions/NEArithmeticAddition.h"
#include "arm_compute/runtime/NEON/functions/NEFFT2D.h"
#include "arm_compute/runtime/NEON/functions/NEPadLayer.h"
#include "arm_compute/runtime/NEON/functions/NEPermute.h"
#include "arm_compute/runtime/NEON/functions/NEPixelWiseMultiplication.h"
#include "arm_compute/runtime/NEON/functions/NEReductionOperation.h"
#include "arm_compute/runtime/NEON/functions/NEReshapeLayer.h"
#include "arm_compute/runtime/NEON/functions/NEReverse.h"
#include "arm_compute/runtime/NEON/functions/NESlice.h"
namespace arm_compute
{
// Forward declarations
class ITensor;
/** Basic function to execute FFT-based convolution on NEON. This function calls the following NEON functions/kernels:
*
* -# @ref NEPermute Permute input if NHWC(only NCHW is supported).
* -# @ref NEPadLayer Pad input.
* -# @ref NEFFT2D Forward transform to the frequency domain.
* -# @ref NEComplexPixelWiseMultiplication Complex element-wise product of input and the weights.
* -# @ref NEReductionOperation Reduction across channels.
* -# @ref NEFFT2D Inverse transform back to the time domain.
* -# @ref NEStridedSlice Extract valid output.
* -# @ref NEArithmeticAddition Add bias.
* -# @ref NEActivationLayer Perform activation.
* -# @ref NEPermute Permute output if NHWC(only NCHW is supported).
*/
class NEFFTConvolutionLayer : public IFunction
{
public:
/** Default constructor */
NEFFTConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEFFTConvolutionLayer(const NEFFTConvolutionLayer &) = delete;
/** Prevent instances of this class from being moved (As this class contains non movable objects) */
NEFFTConvolutionLayer(NEFFTConvolutionLayer &&) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEFFTConvolutionLayer &operator=(const NEFFTConvolutionLayer &) = delete;
/** Prevent instances of this class from being moved (As this class contains non movable objects) */
NEFFTConvolutionLayer &operator=(NEFFTConvolutionLayer &&) = delete;
/** Default destructor */
~NEFFTConvolutionLayer();
/** Set the input and output tensors.
*
* @note: This function only works with any square kernel size and unit strides for both NCHW and NHWC data layout
*
* @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: 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.
* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p input
* @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.
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
* @param[in] enable_fast_math (Optional) Enable fast math computation. Unused for NEON backend.
*/
void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info,
const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false);
/** Static function to check if given info will lead to a valid configuration of @ref NEFFTConvolutionLayer
*
* @note: This function only works with any square kernel size and unit strides for both NCHW and NHWC data layout
*
* @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: 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.
* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p input
* @param[in] 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.
* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
* @param[in] enable_fast_math (Optional) Enable fast math computation. Unused for NEON backend.
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false);
// Inherited methods overridden:
void run() override;
void prepare() override;
private:
MemoryGroup _memory_group;
NEReverse _flip_weights_func;
NEPermute _permute_input_func;
NEPermute _permute_output_func;
NEPermute _permute_weights_func;
NEPermute _permute_bias_func;
NEPadLayer _pad_input_func;
NEPadLayer _pad_weights_func;
NEFFT2D _transform_input_func;
std::unique_ptr<NEFFT2D> _transform_weights_func;
NEFFT2D _itransform_output_func;
NEComplexPixelWiseMultiplication _prod_func;
NEReductionOperation _reduce_func;
NESlice _extract_output_func;
NEArithmeticAddition _bias_add_func;
NEActivationLayer _activation_layer_func;
Tensor _permuted_input;
Tensor _permuted_weights;
Tensor _permuted_bias;
Tensor _permuted_output;
Tensor _padded_input;
Tensor _padded_weights;
Tensor _flip_axis;
Tensor _flipped_weights;
Tensor _transformed_input;
Tensor _transformed_weights;
Tensor _input_weights_product;
Tensor _output_product;
Tensor _output_reduced;
Tensor _itransformed_output;
Tensor _reshaped_output;
Tensor _bias_output;
const ITensor *_original_weights;
const ITensor *_original_bias;
bool _is_activationlayer_enabled;
bool _needs_permute;
bool _has_bias;
bool _is_prepared;
};
} // namespace arm_compute
#endif /* ARM_COMPUTE_NEFFTCONVOLUTIONLAYER_H */
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