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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.
*/
#include "DepthToSpace.h"
#include "Utils.h"
#include <tensorflow/lite/kernels/internal/optimized/optimized_ops.h>
namespace luci_interpreter
{
namespace kernels
{
DepthToSpace::DepthToSpace(const Tensor *input, Tensor *output, const DepthToSpaceParams ¶ms)
: KernelWithParams<DepthToSpaceParams>({input}, {output}, params)
{
}
void DepthToSpace::configure()
{
if (input()->shape().num_dims() != 4)
{
throw std::runtime_error("Invalid input num_dims.");
}
if (output()->element_type() != DataType::FLOAT32 && output()->element_type() != DataType::U8 &&
output()->element_type() != DataType::S8 && output()->element_type() != DataType::S32 &&
output()->element_type() != DataType::S64)
{
throw std::runtime_error("Invalid output type");
}
if (input()->element_type() != output()->element_type())
{
throw std::runtime_error("Type mismatch on input and output.");
}
const int block_size = params().block_size;
const int32_t input_height = input()->shape().dim(1);
const int32_t input_width = input()->shape().dim(2);
const int32_t input_channels = input()->shape().dim(3);
int32_t output_height = input_height * block_size;
int32_t output_width = input_width * block_size;
int32_t output_channels = input_channels / block_size / block_size;
assert(input_height == output_height / block_size);
assert(input_width == output_width / block_size);
assert(input_channels == output_channels * block_size * block_size);
Shape output_shape(4);
output_shape.dim(0) = input()->shape().dim(0);
output_shape.dim(1) = output_height;
output_shape.dim(2) = output_width;
output_shape.dim(3) = output_channels;
output()->resize(output_shape);
}
void DepthToSpace::execute() const
{
tflite::DepthToSpaceParams op_params;
op_params.block_size = params().block_size;
switch (input()->element_type())
{
case DataType::FLOAT32:
tflite::optimized_ops::DepthToSpace(op_params, getTensorShape(input()),
getTensorData<float>(input()), getTensorShape(output()),
getTensorData<float>(output()));
break;
case DataType::U8:
tflite::optimized_ops::DepthToSpace(op_params, getTensorShape(input()),
getTensorData<uint8_t>(input()), getTensorShape(output()),
getTensorData<uint8_t>(output()));
break;
default:
throw std::runtime_error("Unsupported Type.");
}
}
} // namespace kernels
} // namespace luci_interpreter
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