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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.
*/
#include "arm_compute/core/CL/kernels/CLDirectConvolutionLayerOutputStageKernel.h"
#include "arm_compute/core/AccessWindowStatic.h"
#include "arm_compute/core/CL/CLValidate.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Window.h"
#include <cstddef>
#include <cstdint>
using namespace arm_compute;
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::S32, DataType::F16,
DataType::F32);
if(bias != nullptr)
{
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(bias);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bias, 1, DataType::S32, DataType::F16, DataType::F32);
if(is_data_type_quantized_asymmetric(input->data_type()))
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bias, 1, DataType::S32);
}
else
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias);
}
ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() > 1);
}
else
{
ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_data_type_float(input->data_type()),
"Calling output stage kernel with floating point arguments");
}
// Checks performed on output
if(input->data_type() == DataType::S32)
{
// Quantized configuration checks
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8);
}
else
{
// In case of out-of-place computation (supported for non-quantized configurations)
if((output != nullptr) && (output->total_size() != 0))
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
}
}
return Status{};
}
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *bias, ITensorInfo *output)
{
bool window_changed = false;
unsigned int num_elems_processed_per_iteration = 16 / element_size_from_data_type(input->data_type());
// Configure kernel window
Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration));
// Input window
AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration);
window_changed = window_changed || update_window_and_padding(win, input_access);
// Bias window
if(bias != nullptr)
{
AccessWindowStatic bias_access(bias, 0, 0, ceil_to_multiple(bias->dimension(0), num_elems_processed_per_iteration), bias->dimension(1));
window_changed = window_changed || update_window_and_padding(win, bias_access);
}
// Output window
if(output != nullptr && (output->total_size() != 0))
{
AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
window_changed = window_changed || update_window_and_padding(win, output_access);
output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape()));
}
else
{
input_access.set_valid_region(win, ValidRegion(Coordinates(), input->tensor_shape()));
}
Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
return std::make_pair(err, win);
}
} // namespace
CLDirectConvolutionLayerOutputStageKernel::CLDirectConvolutionLayerOutputStageKernel()
: _input(nullptr), _bias(nullptr), _output(nullptr), _result_fixedpoint_multiplier(0), _result_shift(0), _result_offset_after_shift(0)
{
}
void CLDirectConvolutionLayerOutputStageKernel::configure(ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input);
// Auto-initialize output if required
if(output != nullptr)
{
// Work out expected output data type
const DataType output_dt = (input->info()->data_type() == DataType::S32) ? DataType::QASYMM8 : input->info()->data_type();
// Output tensor auto initialization if not yet initialized
auto_init_if_empty(*output->info(), input->info()->clone()->set_data_type(output_dt));
}
// Perform validation step
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (bias == nullptr) ? nullptr : bias->info(), (output == nullptr) ? nullptr : output->info()));
_bias = bias;
_input = input;
_output = output;
_result_fixedpoint_multiplier = result_fixedpoint_multiplier;
_result_shift = result_shift;
_result_offset_after_shift = result_offset_after_shift;
const unsigned int num_elems_accessed_per_iteration = 16 / element_size_from_data_type(input->info()->data_type());
// Create kernel
CLBuildOptions build_opts;
build_opts.add_option_if(bias != nullptr, "-DHAS_BIAS");
build_opts.add_option("-D" + string_from_data_layout(input->info()->data_layout()));
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_accessed_per_iteration));
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("output_stage_quantized", build_opts.options()));
// Set static kernel arguments
int idx = 2 * num_arguments_per_3D_tensor() + ((bias != nullptr) ? num_arguments_per_1D_tensor() : 0);
_kernel.setArg<int>(idx++, _result_offset_after_shift);
_kernel.setArg<int>(idx++, _result_fixedpoint_multiplier);
_kernel.setArg<int>(idx++, _result_shift);
// Configure kernel window
auto win_config = validate_and_configure_window(input->info(), (bias == nullptr) ? nullptr : bias->info(), (output == nullptr) ? nullptr : output->info());
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure_internal(win_config.second);
}
Status CLDirectConvolutionLayerOutputStageKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, bias, output));
ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), bias == nullptr ? nullptr : bias->clone().get(), output == nullptr ? nullptr : output->clone().get()).first);
return Status{};
}
void CLDirectConvolutionLayerOutputStageKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(ICLKernel::window(), window);
Window slice = window.first_slice_window_3D();
// Set bias vector
if(_bias != nullptr)
{
unsigned int idx1 = 2 * num_arguments_per_3D_tensor();
Window slice_biases;
slice_biases.use_tensor_dimensions(_bias->info()->tensor_shape());
add_1D_tensor_argument(idx1, _bias, slice_biases);
}
// Run kernel
do
{
// Set arguments
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(window.slide_window_slice_3D(slice));
}
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