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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 "luci/Import/Nodes/CircleCustom.h"
#include <loco.h>
namespace luci
{
bool CircleCustomGraphBuilder::validate(const ValidateArgs &) const
{
// DO NOTHING
return true;
}
void CircleCustomGraphBuilder::build(const circle::OperatorT &op,
GraphBuilderContext *context) const
{
assert(context != nullptr);
auto graph = context->graph();
const std::vector<int32_t> &inputs = op.inputs;
const std::vector<int32_t> &outputs = op.outputs;
const auto &tensors = context->reader()->tensors();
auto tensors_ptr = context->reader()->tensors_ptr();
assert(tensors_ptr != nullptr);
// Create CircleCustom
const auto &opcodes = context->reader()->opcodes();
const uint32_t opcode_index = op.opcode_index;
const circle::OperatorCodeT &opcode = *opcodes[opcode_index];
auto *node = graph->nodes()->create<CircleCustom>(inputs.size());
uint32_t input_idx = 0;
for (const int32_t input_tensor_index : inputs)
{
node->inputs(input_idx++, context->nodefinder()->node(input_tensor_index));
}
node->custom_options(std::vector<uint8_t>{op.custom_options.begin(), op.custom_options.end()});
node->custom_code(opcode.custom_code);
// Operator version of custom is always 1, so do nothing
uint32_t output_count = outputs.size();
assert(output_count > 0);
{
// Let's use attributes from output 0 for this node
const circle::TensorT &output_tensor = *tensors[outputs[0]];
node->name(tensor_name(output_tensor));
node->dtype(luci_datatype(output_tensor.type));
}
// Create virtual outputs of Custom
for (uint32_t n = 0; n < output_count; ++n)
{
const circle::TensorT &output_tensor = *tensors[outputs[n]];
auto *nodeout = graph->nodes()->create<CircleCustomOut>();
copy_tensor_attributes(output_tensor, nodeout);
// mark shape_status
if (tensors_ptr->Get(outputs[n])->shape() == nullptr)
nodeout->shape_status(ShapeStatus::NOSHAPE);
else
nodeout->shape_status(ShapeStatus::VALID);
nodeout->input(node);
nodeout->index(n);
context->nodefinder()->enroll(outputs[n], nodeout);
}
}
} // namespace luci
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