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/*
* Copyright (c) 2019-2020 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/NEON/kernels/NEBatchConcatenateLayerKernel.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/IAccessWindow.h"
#include "arm_compute/core/NEON/NEAsymm.h"
#include "arm_compute/core/NEON/wrapper/wrapper.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"
namespace arm_compute
{
namespace
{
template <typename T>
void batch_concat(const ITensor *in, ITensor *out, unsigned int batch_offset, const Window &window)
{
// Offset input
uint8_t *input_ptr = in->buffer() + in->info()->offset_first_element_in_bytes();
// Offset output
uint8_t *output_ptr = out->buffer() + out->info()->offset_first_element_in_bytes() + batch_offset * out->info()->strides_in_bytes()[3];
const auto window_start_x = static_cast<int>(window.x().start());
const auto window_end_x = static_cast<int>(window.x().end());
const int window_step_x = 16 / out->info()->element_size();
Window win{ window };
win.set(Window::DimX, Window::Dimension(0, 1, 1));
win.set(3, Window::Dimension(0, in->info()->tensor_shape()[3], 1));
Iterator input(in, win);
Iterator output(out, win);
const DataType dt = in->info()->data_type();
const UniformQuantizationInfo input_qinfo = in->info()->quantization_info().uniform();
const UniformQuantizationInfo output_qinfo = out->info()->quantization_info().uniform();
if(dt == DataType::QASYMM8 && input_qinfo != output_qinfo)
{
execute_window_loop(win, [&](const Coordinates &)
{
const auto in_ptr = reinterpret_cast<const uint8_t *>(input_ptr + input.offset());
const auto out_ptr = reinterpret_cast<uint8_t *>(output_ptr + output.offset());
int x = window_start_x;
for(; x <= (window_end_x - window_step_x); x += window_step_x)
{
wrapper::vstore(out_ptr, vquantize(vdequantize(wrapper::vloadq(in_ptr), input_qinfo), output_qinfo));
}
// Compute left-over elements
for(; x < window_end_x; ++x)
{
*(out_ptr + x) = quantize_qasymm8(dequantize_qasymm8(*(in_ptr + x), input_qinfo), output_qinfo);
}
},
input, output);
}
else if(dt == DataType::QASYMM8_SIGNED && input_qinfo != output_qinfo)
{
execute_window_loop(win, [&](const Coordinates &)
{
const auto in_ptr = reinterpret_cast<const int8_t *>(input_ptr + input.offset());
const auto out_ptr = reinterpret_cast<int8_t *>(output_ptr + output.offset());
int x = window_start_x;
for(; x <= (window_end_x - window_step_x); x += window_step_x)
{
wrapper::vstore(out_ptr, vquantize_signed(vdequantize(wrapper::vloadq(in_ptr), input_qinfo), output_qinfo));
}
// Compute left-over elements
for(; x < window_end_x; ++x)
{
*(out_ptr + x) = quantize_qasymm8_signed(dequantize_qasymm8_signed(*(in_ptr + x), input_qinfo), output_qinfo);
}
},
input, output);
}
else
{
execute_window_loop(win, [&](const Coordinates &)
{
const auto in_ptr = reinterpret_cast<const T *>(input_ptr + input.offset());
const auto out_ptr = reinterpret_cast<T *>(output_ptr + output.offset());
int x = window_start_x;
for(; x <= (window_end_x - window_step_x); x += window_step_x)
{
wrapper::vstore(out_ptr + x, wrapper::vloadq(in_ptr + x));
}
// Compute left-over elements
for(; x < window_end_x; ++x)
{
*(out_ptr + x) = *(in_ptr + x);
}
},
input, output);
}
}
Status validate_arguments(const ITensorInfo *input, unsigned int batch_offset, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
//Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input) is not needed here as this kernel doesn't use NEON FP16 instructions.
ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimX) != output->dimension(Window::DimX));
ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimY) != output->dimension(Window::DimY));
ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(Window::DimZ) != output->dimension(Window::DimZ));
ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(3) + batch_offset > output->dimension(3));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(4, input, output);
return Status{};
}
} // namespace
NEBatchConcatenateLayerKernel::NEBatchConcatenateLayerKernel()
: _func(nullptr), _input(nullptr), _output(nullptr), _batch_offset(0)
{
}
void NEBatchConcatenateLayerKernel::configure(const ITensor *input, unsigned int batch_offset, ITensor *output)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), batch_offset, output->info()));
_func = nullptr;
_input = input;
_output = output;
_batch_offset = batch_offset;
switch(input->info()->data_type())
{
case DataType::S8:
case DataType::U8:
case DataType::QASYMM8:
case DataType::QASYMM8_SIGNED:
_func = &batch_concat<uint8_t>;
break;
case DataType::S16:
case DataType::U16:
case DataType::F16:
_func = &batch_concat<uint16_t>;
break;
case DataType::S32:
case DataType::U32:
case DataType::F32:
_func = &batch_concat<uint32_t>;
break;
default:
ARM_COMPUTE_ERROR("Unsupported data type.");
}
// Configure kernel window
Window win = calculate_max_window(*output->info(), Steps());
Coordinates coord;
coord.set_num_dimensions(output->info()->num_dimensions());
output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape()));
INEKernel::configure(win);
}
Status NEBatchConcatenateLayerKernel::validate(const arm_compute::ITensorInfo *input,
unsigned int batch_offset,
const arm_compute::ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, batch_offset, output));
return Status{};
}
void NEBatchConcatenateLayerKernel::run(const Window &window, const ThreadInfo &info)
{
ARM_COMPUTE_UNUSED(info);
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window);
ARM_COMPUTE_ERROR_ON(_func == nullptr);
(*_func)(_input, _output, _batch_offset, window);
}
} // namespace arm_compute
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