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/*
* Copyright (c) 2018-2021 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.
*/
#include "src/cpu/kernels/CpuConvertFullyConnectedWeightsKernel.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Types.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
namespace arm_compute
{
namespace cpu
{
namespace kernels
{
void CpuConvertFullyConnectedWeightsKernel::configure(const ITensorInfo *src,
ITensorInfo *dst,
const TensorShape &original_input_shape,
DataLayout data_layout)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
// Output tensor auto initialisation if not yet initialized
auto_init_if_empty(*dst, *src->clone());
ARM_COMPUTE_ERROR_THROW_ON(
CpuConvertFullyConnectedWeightsKernel::validate(src, dst, original_input_shape, data_layout));
const DataLayout input_data_layout = (data_layout == DataLayout::NCHW) ? DataLayout::NHWC : DataLayout::NCHW;
const int width_idx = get_data_layout_dimension_index(input_data_layout, DataLayoutDimension::WIDTH);
const int height_idx = get_data_layout_dimension_index(input_data_layout, DataLayoutDimension::HEIGHT);
const int channel_idx = get_data_layout_dimension_index(input_data_layout, DataLayoutDimension::CHANNEL);
const unsigned int num_elems_per_input_plane = original_input_shape[width_idx] * original_input_shape[height_idx];
const unsigned int num_channels = original_input_shape[channel_idx];
_factor1 = (data_layout == DataLayout::NCHW) ? num_elems_per_input_plane : num_channels;
_factor2 = (data_layout == DataLayout::NCHW) ? num_channels : num_elems_per_input_plane;
// Configure kernel window
Window win = calculate_max_window(*src, Steps());
ICpuKernel::configure(win);
}
Status CpuConvertFullyConnectedWeightsKernel::validate(const ITensorInfo *src,
const ITensorInfo *dst,
const TensorShape &original_input_shape,
DataLayout data_layout)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src);
ARM_COMPUTE_RETURN_ERROR_ON(src->data_type() == DataType::UNKNOWN);
ARM_COMPUTE_RETURN_ERROR_ON(src->num_dimensions() != 2);
ARM_COMPUTE_RETURN_ERROR_ON(src->dimension(1) != original_input_shape.total_size_lower(3));
ARM_COMPUTE_RETURN_ERROR_ON(data_layout == DataLayout::UNKNOWN);
// Checks performed when dst is configured
if ((dst != nullptr) && (dst->total_size() != 0))
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src, dst);
}
return Status{};
}
void CpuConvertFullyConnectedWeightsKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window);
const auto src = tensors.get_const_tensor(TensorType::ACL_SRC);
auto dst = tensors.get_tensor(TensorType::ACL_DST);
const unsigned int dst_stride_x = dst->info()->strides_in_bytes().x();
const unsigned int dst_stride_y = dst->info()->strides_in_bytes().y();
const unsigned int element_size = src->info()->element_size();
Iterator input(src, window);
Iterator output(dst, window);
execute_window_loop(
window,
[&](const Coordinates &id)
{
memcpy(output.ptr() + id.x() * dst_stride_x +
(id.y() % _factor1 * _factor2 + id.y() / _factor1) * dst_stride_y,
input.ptr(), element_size);
},
input);
}
const char *CpuConvertFullyConnectedWeightsKernel::name() const
{
return "CpuConvertFullyConnectedWeightsKernel";
}
} // namespace kernels
} // namespace cpu
} // namespace arm_compute
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