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/*
* Copyright (c) 2018-2019 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_NECONVERTFULLYCONNECTEDWEIGHTS_H
#define ARM_COMPUTE_NECONVERTFULLYCONNECTEDWEIGHTS_H
#include "arm_compute/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/ITransformWeights.h"
#include "arm_compute/runtime/NEON/NEScheduler.h"
#include "arm_compute/runtime/Tensor.h"
namespace arm_compute
{
// Forward declarations
class ITensor;
/** Basic function to run @ref NEConvertFullyConnectedWeightsKernel. */
class NEConvertFullyConnectedWeights : public IFunction
{
public:
/** Default constructor */
NEConvertFullyConnectedWeights();
/** Initialize the function.
*
* @param[in] input Source weights tensor to convert. Must be 2 dimensional. Data types supported: All.
* @param[out] output The converted weights tensor. Shape and Data Type: Same as @p input.
* @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer).
* @param[in] data_layout The data layout the weights have been trained in.
*/
void configure(const ITensor *input, ITensor *output, const TensorShape &original_input_shape, DataLayout data_layout);
/** Static function to check if given info will lead to a valid configuration of @ref NEConvertFullyConnectedWeights
*
* @param[in] input Source weights tensor info to convert. Must be 2 dimensional. Data types supported: All.
* @param[in] output The converted weights tensor info. Shape and Data Type: Same as @p input.
* @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer).
* @param[in] data_layout The data layout the weights have been trained in.
*
* @return A Status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *output, const TensorShape &original_input_shape, DataLayout data_layout);
// Inherited methods overriden:
void run() override;
private:
NEConvertFullyConnectedWeightsKernel _kernel;
};
namespace weights_transformations
{
/** Basic function to run @ref NEConvertFullyConnectedWeightsKernel. */
class NEConvertFullyConnectedWeightsManaged : public ITransformWeights
{
public:
void run() override
{
_output.allocator()->allocate();
_func.run();
_reshape_run = true;
}
void release() override
{
_output.allocator()->free();
}
ITensor *get_weights() override
{
return &_output;
}
uint32_t uid() override
{
return _uid;
}
void configure(const ITensor *input, const TensorShape &original_input_shape, DataLayout data_layout)
{
_func.configure(input, &_output, original_input_shape, data_layout);
}
private:
static constexpr uint32_t _uid = 0x4;
Tensor _output{};
NEConvertFullyConnectedWeights _func{};
};
} // namespace weights_transformations
} // namespace arm_compute
#endif /* ARM_COMPUTE_NECONVERTFULLYCONNECTEDWEIGHTS_H */
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