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/*
* Copyright (c) 2017-2021, 2023 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_CL_FULLY_CONNECTED_H
#define ARM_COMPUTE_CL_FULLY_CONNECTED_H
#include "arm_compute/core/TensorInfo.h"
#include "src/gpu/cl/ClCompileContext.h"
#include "src/gpu/cl/IClOperator.h"
#include <memory>
namespace arm_compute
{
namespace opencl
{
// Forward declarations
class ClConvertFullyConnectedWeights;
class ClFlatten;
class ClGemm;
class ClGemmLowpMatrixMultiplyCore;
class ClTranspose;
/** Basic function to compute a Fully Connected layer on OpenCL. This function calls the following OpenCL kernels:
*
* -# @ref opencl::kernels::ClIm2ColKernel (called when the input comes from a convolutional layer)
* -# @ref CLTranspose (if @p are_weights_reshaped is set to false and transpose_weights is set to true ) (called once)
* -# @ref opencl::ClGemm or @ref CLGEMMLowpMatrixMultiplyCore (if quantized asymmetric)
*
* @note The fully connected layer accepts "weights" tensors only with 2 dimensions.
*/
class ClFullyConnected : public IClOperator
{
public:
ClFullyConnected();
~ClFullyConnected();
/** 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_SIGNED |QASYMM8_SIGNED |S32 |QASYMM8_SIGNED |
*
* @param[in] compile_context The compile context to be used.
* @param[in] src Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] weights Weights tensor. The weights must be 2 dimensional.
* If this function is called after a Convolution Layer, the (transposed) weights will have as many rows as the product of the first 3 input's dimensions.
* If it is called after another FullyConnected Layer, the (transposed) weights will have as many rows as the input's first dimension.
* Data type supported: Same as @p src.
* @param[in] biases Bias tensor. Can be nullptr. Data type supported:Same as @p src.
* @param[out] dst Destination tensor. Its shape should be equal to the output of a matrix multiplication between:
* - The output of im2col on the input and the (transposed) 2D weights, if the function is called after a Convolution Layer
* - The input tensor and the (transposed) 2D weights, if the function is called after another FullyConnected Layer.
* Data type supported: Same as @p src.
* @param[in] fc_info (Optional) Fully connected layer additional info
*/
void configure(const CLCompileContext &compile_context, ITensorInfo *src, ITensorInfo *weights, ITensorInfo *biases, ITensorInfo *dst,
FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo());
/** Static function to check if given info will lead to a valid configuration
*
* Similar to ClFullyConnected::configure()
*
* @return a status
*/
static Status validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst,
FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo());
// Inherited methods overriden
void run(ITensorPack &tensors) override;
void prepare(ITensorPack &tensors) override;
experimental::MemoryRequirements workspace() const override;
private:
void configure_fc_fc(const CLCompileContext &compile_context, ITensorInfo *src, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *dst, const FullyConnectedLayerInfo &fc_info);
void configure_conv_fc(const CLCompileContext &compile_context, ITensorInfo *src, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *dst, const FullyConnectedLayerInfo &fc_info);
void configure_mm(const CLCompileContext &compile_context, ITensorInfo *src, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *dst, const FullyConnectedLayerInfo &fc_info);
private:
enum AuxTensorIdx
{
TransposedWeights = 10,
ConvertedWeights = 11,
FlattenedSrc = 12,
Count = 13
};
std::unique_ptr<ClConvertFullyConnectedWeights> _convert_weights;
std::unique_ptr<ClFlatten> _flatten;
std::unique_ptr<ClTranspose> _reshape_weights;
std::unique_ptr<ClGemm> _mm_gemm;
std::unique_ptr<ClGemmLowpMatrixMultiplyCore> _mm_gemmlowp;
experimental::MemoryRequirements _aux_mem{};
TensorInfo _flattened_src{};
TensorInfo _converted_weights{};
TensorInfo _reshaped_weights{};
TensorInfo _weights_to_use{};
int _weights_to_use_idx{ ACL_SRC_1 };
bool _are_weights_converted{ true };
bool _are_weights_reshaped{ true };
bool _is_fc_after_conv{ true };
bool _is_quantized{ false };
bool _is_prepared{ false };
bool _dynamic_weights{ false };
#ifdef ARM_COMPUTE_ASSERTS_ENABLED
int _asrt_run_count{};
int _asrt_prepare_count{};
#endif // ARM_COMPUTE_ASSERTS_ENABLED
};
} // namespace opencl
} // namespace arm_compute
#endif /* ARM_COMPUTE_CL_FULLY_CONNECTED_H */