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/*
* Copyright (c) 2017-2020 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.
*/
#include "arm_compute/core/CL/kernels/CLDequantizationLayerKernel.h"
#include "arm_compute/core/AccessWindowStatic.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/TensorInfo.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/Window.h"
#include "support/StringSupport.h"
namespace arm_compute
{
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM8_PER_CHANNEL, DataType::QSYMM8, DataType::QSYMM16);
if(output->tensor_shape().total_size() > 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(output);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output);
}
return Status{};
}
std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output)
{
// Configure kernel window
Window win = calculate_max_window(*input, Steps());
// Output tensor auto initialization if not yet initialized
auto_init_if_empty(*output, input->tensor_shape(), 1, DataType::F32);
// CLDequantizationLayerKernel doesn't need padding so update_window_and_padding() can be skipped
Coordinates coord;
coord.set_num_dimensions(output->num_dimensions());
output->set_valid_region(ValidRegion(coord, output->tensor_shape()));
return std::make_tuple(Status{}, win);
}
} // namespace
CLDequantizationLayerKernel::CLDequantizationLayerKernel()
: _input(nullptr), _output(nullptr)
{
}
void CLDequantizationLayerKernel::configure(const ICLTensor *input, ICLTensor *output)
{
configure(CLKernelLibrary::get().get_compile_context(), input, output);
}
void CLDequantizationLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info()));
_input = input;
_output = output;
const int vec_size_x = 16 / output->info()->element_size();
const int output_width_x = output->info()->tensor_shape().x();
const bool multi_access_x = (output_width_x / vec_size_x > 0);
// Create and update the window (if needed)
Window win = calculate_max_window(*output->info());
if(multi_access_x)
{
win.set(Window::DimX,
Window::Dimension(win.x().start(), ceil_to_multiple(win.x().end(), vec_size_x), vec_size_x));
}
ICLKernel::configure_internal(win);
const bool is_quantized_per_channel = is_data_type_quantized_per_channel(input->info()->data_type());
std::string kernel_name = "dequantization_layer";
// Create kernel
CLBuildOptions build_opts;
if(!is_quantized_per_channel)
{
const UniformQuantizationInfo qinfo = input->info()->quantization_info().uniform();
const int qoffset = is_data_type_quantized_asymmetric(input->info()->data_type()) ? qinfo.offset : 0;
build_opts.add_option("-DSCALE=" + float_to_string_with_full_precision(qinfo.scale));
build_opts.add_option("-DOFFSET=" + support::cpp11::to_string(qoffset));
}
else
{
kernel_name += "_per_channel";
kernel_name += input->info()->data_layout() == DataLayout::NCHW ? "_nchw" : "_nhwc";
}
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(vec_size_x));
build_opts.add_option("-DDATA_TYPE_SRC=" + get_cl_type_from_data_type(input->info()->data_type()));
build_opts.add_option("-DDATA_TYPE_DST=" + get_cl_type_from_data_type(output->info()->data_type()));
build_opts.add_option_if(multi_access_x, "-DLAST_ACCESSED_X=" + support::cpp11::to_string(std::max<int>(output_width_x - vec_size_x, 0)));
// Create kernel name
_kernel = create_kernel(compile_context, kernel_name, build_opts.options());
}
Status CLDequantizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output));
ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get())));
return Status{};
}
void CLDequantizationLayerKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
const bool is_quantized_per_channel = is_data_type_quantized_per_channel(_input->info()->data_type());
// Collapse windo
Window new_window = is_quantized_per_channel ? window.collapse_if_possible(ICLKernel::window(), 4) : window.collapse_if_possible(ICLKernel::window(), 3);
Window slice = new_window.first_slice_window_3D();
if(is_quantized_per_channel)
{
unsigned int idx = num_arguments_per_3D_tensor() * 2; //Skip the input and output parameters
_kernel.setArg(idx++, _input->quantization().scale->cl_buffer());
}
do
{
unsigned int idx = 0;
add_3D_tensor_argument(idx, _input, slice);
add_3D_tensor_argument(idx, _output, slice);
enqueue(queue, *this, slice, lws_hint());
}
while(new_window.slide_window_slice_3D(slice));
}
} // namespace arm_compute
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