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/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
*
* 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.
*/
/*
* Copyright (c) 2017 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/runtime/CL/functions/CLSplitVEx.h"
#include "support/ToolchainSupport.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
#include <cassert>
using namespace arm_compute;
namespace
{
Status validate_arguments(const ICLTensor *size_splits, const std::vector<ICLTensor *> &outputs,
unsigned int num_splits)
{
ARM_COMPUTE_RETURN_ERROR_ON_MSG(size_splits->info()->num_dimensions() != 1,
"size_splits must be a 1-D tensor.");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(num_splits != outputs.size(),
"Number of output tensors does not match number of splits.");
return Status{};
}
Status validate_slices(const ITensorInfo *input, const std::vector<ITensorInfo *> &outputs,
uint32_t split_dim)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
ARM_COMPUTE_RETURN_ERROR_ON(split_dim >= input->num_dimensions());
ARM_COMPUTE_RETURN_ERROR_ON(outputs.size() < 2);
// Start/End coordinates
Coordinates start_coords;
Coordinates end_coords;
for (unsigned int d = 0; d < input->num_dimensions(); ++d)
{
end_coords.set(d, -1);
}
unsigned int axis_offset = 0;
// Validate output tensors
for (const auto &output : outputs)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
// Get output shape
const TensorShape output_shape = output->tensor_shape();
ARM_COMPUTE_RETURN_ERROR_ON(output_shape.total_size() == 0);
const size_t axis_split_step = output_shape[split_dim];
// Output auto inizialitation if not yet initialized
TensorInfo tmp_output_info = *output->clone();
auto_init_if_empty(tmp_output_info,
input->clone()->set_is_resizable(true).set_tensor_shape(output_shape));
// Update coordinate on axis
start_coords.set(split_dim, axis_offset);
end_coords.set(split_dim, axis_offset + axis_split_step);
ARM_COMPUTE_RETURN_ON_ERROR(CLSlice::validate(input, output, start_coords, end_coords));
axis_offset += axis_split_step;
}
return Status{};
}
void configure_slices(const ICLTensor *input, const std::vector<ICLTensor *> &outputs,
std::vector<CLSlice> &_slice_functions, uint32_t split_dim)
{
unsigned int axis_offset = 0;
// Start/End coordinates
Coordinates start_coords;
Coordinates end_coords;
for (unsigned int d = 0; d < input->info()->num_dimensions(); ++d)
{
end_coords.set(d, -1);
}
int out_iter = 0;
for (const auto &output : outputs)
{
const TensorShape output_shape = output->info()->tensor_shape();
auto op_size = output_shape.total_size();
if (!op_size)
{
continue;
}
assert(op_size != 0);
assert(split_dim <= output_shape.num_dimensions());
const size_t axis_split_step = output_shape[split_dim];
// Output auto inizialitation if not yet initialized
TensorInfo tmp_output_info = *output->info()->clone();
auto_init_if_empty(
tmp_output_info,
input->info()->clone()->set_is_resizable(true).set_tensor_shape(output_shape));
// Update coordinate on axis
start_coords.set(split_dim, axis_offset);
end_coords.set(split_dim, axis_offset + axis_split_step);
// Configure slice function
_slice_functions[out_iter].configure(input, output, start_coords, end_coords);
// Set valid region from shape
outputs[out_iter++]->info()->set_valid_region(ValidRegion(Coordinates(), output_shape));
axis_offset += axis_split_step;
}
}
} // namespace
CLSplitVEx::CLSplitVEx()
: _input(nullptr), _size_splits(nullptr), _outputs(), _num_splits(0), _slice_functions()
{
}
void CLSplitVEx::configure(const ICLTensor *input, const ICLTensor *size_splits, uint32_t split_dim,
const std::vector<ICLTensor *> &outputs, unsigned int num_splits)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, size_splits);
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(size_splits, outputs, num_splits));
_input = input;
_size_splits = size_splits;
_outputs = outputs;
_num_splits = num_splits;
// Create tensor slices
_slice_functions.resize(_num_splits);
// Extract output tensor info
std::vector<ITensorInfo *> outputs_info;
for (auto &output : _outputs)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(output);
outputs_info.emplace_back(output->info());
}
// Validate slices
ARM_COMPUTE_ERROR_THROW_ON(validate_slices(_input->info(), outputs_info, split_dim));
// Configure slices
configure_slices(_input, _outputs, _slice_functions, split_dim);
}
void CLSplitVEx::run()
{
// execute the slices
for (unsigned i = 0; i < _outputs.size(); ++i)
{
_slice_functions[i].run();
}
}
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