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/*
* Copyright (c) 2021 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 "Builders.h"
#include "kernels/TransposeConv.h"
namespace luci_interpreter
{
std::unique_ptr<Kernel> build_kernel_CircleTransposeConv(const luci::CircleNode *circle_node,
KernelBuilderHelper &helper)
{
const auto *node = loco::must_cast<const luci::CircleTransposeConv *>(circle_node);
assert(node->arity() == 4);
const Tensor *input_sizes = helper.getInputTensor(node->inputSizes());
const Tensor *filter = helper.getInputTensor(node->filter());
const Tensor *out_backprop = helper.getInputTensor(node->outBackprop());
const Tensor *bias = helper.getOptionalInputTensor(node->bias());
Tensor *output = helper.getOutputTensor(node);
DataType scratch_data_type =
helper.getInputTensor(node)->element_type() == DataType::S16 ? DataType::S64 : DataType::S32;
auto scratch_tensor =
std::make_unique<Tensor>(scratch_data_type, Shape({}), AffineQuantization{}, "");
scratch_tensor->set_observable(false);
scratch_tensor->set_data_buffer(nullptr);
Tensor *tmp = helper.getRuntimeGraph(node->graph())->addTensor(std::move(scratch_tensor));
TransposeConvParams params{};
params.padding = node->padding();
params.stride_height = node->stride()->h();
params.stride_width = node->stride()->w();
params.activation = node->fusedActivationFunction();
// TODO support activation
if (params.activation != luci::FusedActFunc::NONE)
{
throw std::runtime_error("Unsupported activation of TransposeConv");
}
return std::make_unique<kernels::TransposeConv>(input_sizes, filter, out_backprop, bias, output,
tmp, params);
}
} // namespace luci_interpreter
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