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/*
* Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
* Copyright (c) 2016-2018 ARM Limited.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "arm_compute/core/CL/kernels/CLSpaceToBatchNDKernel.h"
#include "arm_compute/core/CL/CLHelpers.h"
#include "arm_compute/core/CL/CLKernelLibraryEx.h"
#include "arm_compute/core/CL/ICLTensor.h"
using namespace arm_compute;
namespace
{
constexpr unsigned int num_elems_processed_per_iteration = 16;
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *block_size,
const ITensorInfo *padding_size, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::QASYMM8,
DataType::S16, DataType::F16, DataType::S32,
DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(block_size, 1, DataType::S32);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(padding_size, 1, DataType::S32);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::QASYMM8,
DataType::S16, DataType::F16, DataType::S32,
DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_dimensions() != output->num_dimensions(),
"The number of dimensions of input should be equal to output");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->data_layout() != output->data_layout(),
"The input and output layouts are different!");
// TODO Support other cases
if (input->num_dimensions() == 4 && input->data_layout() == DataLayout::NCHW)
{
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->dimension(2) != output->dimension(2),
"Input Depth should be equal to Output Depth");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(block_size->dimension(0) != 2 ||
padding_size->dimension(1) != 2,
"Only 2-dimensional spatial block's size was wrong");
}
else if (input->num_dimensions() == 4 && input->data_layout() == DataLayout::NHWC)
{
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->dimension(0) != output->dimension(0),
"Input Depth should be equal to Output Depth");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(block_size->dimension(0) != 2 ||
padding_size->dimension(1) != 2,
"Only 2-dimensional spatial block's size was wrong");
}
else
{
ARM_COMPUTE_RETURN_ERROR_MSG("CLSpaceToBatchNDKernel supports only 4-dimensional input");
}
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_dimensions() < 2 && input->num_dimensions() > 4,
"CLSpaceToBatchNDKernel supports dimensions up to 4");
if (input->data_type() == DataType::QASYMM8)
{
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->quantization_info() != output->quantization_info(),
"The input and output quantization info are different!");
}
return Status{};
}
} // namespace
CLSpaceToBatchNDKernel::CLSpaceToBatchNDKernel()
{
// DO NOTHING
}
void CLSpaceToBatchNDKernel::configure(const ICLTensor *input, const ICLTensor *block_size,
const ICLTensor *padding_size, ICLTensor *output)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_ERROR_THROW_ON(
validate_arguments(input->info(), block_size->info(), padding_size->info(), output->info()));
_input = input;
_block_size = block_size;
_padding_size = padding_size;
_output = output;
// Set kernel build options
// TODO Support other cases
std::string kernel_name = "space_to_batch_4d";
std::set<std::string> build_opts;
Window win;
if (input->info()->data_layout() == DataLayout::NCHW)
{
kernel_name += "_nchw";
build_opts.emplace("-DDEPTH_OUT=" + support::cpp11::to_string(output->info()->dimension(2)));
build_opts.emplace("-DHEIGHT_IN=" + support::cpp11::to_string(input->info()->dimension(1)));
build_opts.emplace("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(0)));
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()));
}
else if (input->info()->data_layout() == DataLayout::NHWC)
{
kernel_name += "_nhwc";
build_opts.emplace("-DHEIGHT_OUT=" + support::cpp11::to_string(output->info()->dimension(2)));
build_opts.emplace("-DHEIGHT_IN=" + support::cpp11::to_string(input->info()->dimension(2)));
build_opts.emplace("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(1)));
build_opts.emplace("-DVEC_SIZE=" +
support::cpp11::to_string(num_elems_processed_per_iteration));
win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration));
AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration);
AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration);
bool window_changed = update_window_and_padding(win, input_access, output_access);
input_access.set_valid_region(win, output->info()->valid_region());
if (window_changed)
{
ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!");
}
}
else
{
ARM_COMPUTE_ERROR("Unsupported layout");
}
build_opts.emplace("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
build_opts.emplace("-DBATCH_IN=" + support::cpp11::to_string(input->info()->dimension(3)));
if (input->info()->data_type() == DataType::QASYMM8)
{
build_opts.emplace("-DZERO_VALUE=" +
support::cpp11::to_string(input->info()->quantization_info().offset));
}
else
{
build_opts.emplace("-DZERO_VALUE=" + support::cpp11::to_string(0));
}
// Create kernel
_kernel =
static_cast<cl::Kernel>(CLKernelLibraryEx::get().create_kernel(kernel_name, build_opts));
// Configure kernel window
ICLKernel::configure_internal(win);
}
void CLSpaceToBatchNDKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(ICLKernel::window(), window);
#if defined(ARM_COMPUTE_DEBUG_ENABLED)
const_cast<ICLTensor *>(_block_size)->map(queue);
const_cast<ICLTensor *>(_padding_size)->map(queue);
const size_t num_dimensions = _input->info()->num_dimensions();
const size_t num_spacial_dimensions = _block_size->info()->dimension(0);
uint32_t batch_size = _input->info()->dimension(num_dimensions - 1);
for (size_t i = 0; i < num_spacial_dimensions; ++i)
{
const int32_t block_size = *reinterpret_cast<int32_t *>(_block_size->ptr_to_element({i}));
const int32_t padding_size_pre =
*reinterpret_cast<int32_t *>(_padding_size->ptr_to_element({0, i}));
const int32_t padding_size_post =
*reinterpret_cast<int32_t *>(_padding_size->ptr_to_element({1, i}));
ARM_COMPUTE_ERROR_ON_MSG(block_size < 1, "Block size should be greater than or equal to 1");
ARM_COMPUTE_ERROR_ON_MSG(padding_size_pre < 0 && padding_size_post < 0,
"Padding size should be greater than or equal to 0");
if (num_dimensions == 4 && _input->info()->data_layout() == DataLayout::NCHW)
{
ARM_COMPUTE_ERROR_ON_MSG(
_output->info()->dimension(i) !=
(_input->info()->dimension(i) + padding_size_pre + padding_size_post) / block_size,
"Dimension value of spatial block does not match output's dimension value");
}
else
{
ARM_COMPUTE_ERROR_ON_MSG(
_output->info()->dimension(num_dimensions - num_spacial_dimensions - 1 + i) !=
(_input->info()->dimension(num_dimensions - num_spacial_dimensions - 1 + i) +
padding_size_pre + padding_size_post) /
block_size,
"Dimension value of spatial block does not match output's dimension value");
}
batch_size *= block_size;
}
ARM_COMPUTE_ERROR_ON_MSG(
_output->info()->dimension(num_dimensions - 1) != batch_size,
"Output batch size should be equal to input batch size * (multiplication of all block size)");
const_cast<ICLTensor *>(_block_size)->unmap(queue);
const_cast<ICLTensor *>(_padding_size)->unmap(queue);
#endif // defined(ARM_COMPUTE_DEBUG_ENABLED)
Window slice_out = window.first_slice_window_4D().collapse(ICLKernel::window(), 2, 4);
// Setup output slice
Window slice_in(slice_out);
slice_in.set(Window::DimX, Window::Dimension(0, 0, 0));
slice_in.set(Window::DimY, Window::Dimension(0, 0, 0));
slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
slice_in.set(3, Window::Dimension(0, 0, 0));
// Set block size window
Window win_block = calculate_max_window(*_block_size->info(), Steps());
// Set padding size window
Window win_padding = calculate_max_window(*_padding_size->info(), Steps());
do
{
unsigned int idx = 0;
add_4D_tensor_argument(idx, _input, slice_in);
add_4D_tensor_argument(idx, _output, slice_out);
add_1D_tensor_argument(idx, _block_size, win_block);
add_2D_tensor_argument(idx, _padding_size, win_padding);
enqueue(queue, *this, slice_out);
} while (window.slide_window_slice_4D(slice_out) && window.slide_window_slice_4D(slice_in));
}
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