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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.
*/
#include "arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h"
#include "arm_compute/core/CL/CLHelpers.h"
#include "arm_compute/core/CL/CLKernelLibrary.h"
#include "arm_compute/core/CL/CLValidate.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/CL/OpenCL.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
using namespace arm_compute;
using namespace arm_compute::misc::shape_calculator;
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *biases, const ITensorInfo *output, unsigned int num_groups)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON(num_groups == 0);
ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() == DataLayout::NHWC && num_groups > 1);
ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4 && num_groups > 1);
ARM_COMPUTE_RETURN_ERROR_ON((input->dimension(3) % num_groups) != 0);
if(biases != nullptr)
{
ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_asymmetric(input->data_type()));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, biases);
ARM_COMPUTE_RETURN_ERROR_ON((input->num_dimensions() == 4) && (biases->num_dimensions() != 1));
ARM_COMPUTE_RETURN_ERROR_ON((input->num_dimensions() == 5) && (biases->num_dimensions() != 2));
ARM_COMPUTE_RETURN_ERROR_ON((input->num_dimensions() == 4) && (biases->dimension(0) != input->tensor_shape()[3]));
ARM_COMPUTE_RETURN_ERROR_ON((input->num_dimensions() == 5) && (biases->dimension(0) != input->tensor_shape()[3] || biases->dimension(1) != input->tensor_shape()[4]));
}
// Checks performed when output is configured
if(output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), compute_weights_reshaped_shape(*input, biases != nullptr, num_groups));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
}
return Status{};
}
} // namespace
CLWeightsReshapeKernel::CLWeightsReshapeKernel()
: _input(nullptr), _biases(nullptr), _output(nullptr)
{
}
void CLWeightsReshapeKernel::configure(const ICLTensor *input, const ICLTensor *biases, ICLTensor *output, unsigned int num_groups)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
// Output tensor auto inizialitation if not yet initialized
auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(compute_weights_reshaped_shape(*input->info(), (biases != nullptr), num_groups)));
// Perform validation step
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(),
(biases != nullptr) ? biases->info() : nullptr,
output->info(), num_groups));
const DataType data_type = input->info()->data_type();
_biases = biases;
_output = output;
_input = input;
// Create build options
CLBuildOptions build_opts;
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type));
build_opts.add_option("-DNUM_GROUPS=" + support::cpp11::to_string(num_groups));
build_opts.add_option_if(biases != nullptr, "-DHAS_BIAS");
// Create kernel
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("reshape_to_columns", build_opts.options()));
// Configure window
Window win = calculate_max_window(*input->info(), Steps());
// The CLWeightsReshapeKernel doesn't need padding so update_window_and_padding() can be skipped
output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape()));
ICLKernel::configure_internal(win);
}
Status CLWeightsReshapeKernel::validate(const ITensorInfo *input, const ITensorInfo *biases, const ITensorInfo *output, unsigned int num_groups)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, biases, output, num_groups));
return Status{};
}
void CLWeightsReshapeKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(ICLKernel::window(), window);
Window out_window;
out_window.use_tensor_dimensions(_output->info()->tensor_shape());
Window in_slice = window.first_slice_window_3D();
Window out_slice = out_window.first_slice_window_2D();
Window biases_window;
Window biases_slice;
unsigned int idx = num_arguments_per_3D_tensor() + num_arguments_per_2D_tensor();
idx += (_biases != nullptr) ? num_arguments_per_1D_tensor() : 0;
_kernel.setArg<cl_uint>(idx++, _input->info()->dimension(0));
_kernel.setArg<cl_uint>(idx++, _input->info()->dimension(1));
_kernel.setArg<cl_uint>(idx++, _input->info()->dimension(2));
_kernel.setArg<cl_uint>(idx++, _input->info()->dimension(3));
_kernel.setArg<cl_uint>(idx++, _output->info()->strides_in_bytes().z());
if(_biases != nullptr)
{
biases_window.use_tensor_dimensions(_biases->info()->tensor_shape());
biases_slice = biases_window.first_slice_window_1D();
}
do
{
// Set arguments
unsigned idx = 0;
add_3D_tensor_argument(idx, _input, in_slice);
add_2D_tensor_argument(idx, _output, out_slice);
if(_biases != nullptr)
{
add_1D_tensor_argument(idx, _biases, biases_slice);
ARM_COMPUTE_UNUSED(biases_window.slide_window_slice_1D(biases_slice));
}
// Run kernel
enqueue(queue, *this, in_slice);
}
while(window.slide_window_slice_4D(in_slice) && out_window.slide_window_slice_2D(out_slice));
}