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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/CircleWhile.h"
#include <luci/IR/Nodes/CircleWhile.h>
#include <luci/IR/Nodes/CircleWhileOut.h>
#include <loco.h>
#include <oops/UserExn.h>
namespace luci
{
bool CircleWhileGraphBuilder::validate(const ValidateArgs &args) const
{
const auto &inputs = args.op.inputs;
const auto *options = args.op.builtin_options.AsWhileOptions();
if (inputs.size() != args.op.outputs.size())
return false;
auto num_graphs = static_cast<int32_t>(args.reader.num_subgraph());
if (options->cond_subgraph_index >= num_graphs)
return false;
if (options->body_subgraph_index >= num_graphs)
return false;
return true;
}
/**
* @brief While Node builder
*
* @note Current loco does not provide multiple outputs
* We will create multiple CircleWhileOut nodes to emulate this
* For two outputs that may look like this
*
* --- CircleWhile --- Node ---
* \- Node ---
*
* will be created like this
*
* --- CircleWhile --- CircleWhileOut --- Node ---
* \- CircleWhileOut --- Node ---
*/
void CircleWhileGraphBuilder::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();
const auto &opcodes = context->reader()->opcodes();
std::vector<CircleNode *> input_nodes;
for (const int32_t input_tensor_index : inputs)
{
auto input_node = context->nodefinder()->node(input_tensor_index);
assert(input_node != nullptr);
input_nodes.push_back(input_node);
}
uint32_t input_count = inputs.size();
uint32_t output_count = outputs.size();
// Create CircleWhile
CircleWhile *node = graph->nodes()->create<CircleWhile>(input_count, output_count);
for (uint32_t idx = 0; idx < input_count; ++idx)
{
node->input(idx, input_nodes[idx]);
}
const auto *options = op.builtin_options.AsWhileOptions();
node->cond_branch(options->cond_subgraph_index);
node->body_branch(options->body_subgraph_index);
assert(outputs.size() > 0);
{
// Lets use name of output 0 as While name
const circle::TensorT &output_tensor = *tensors[outputs[0]];
node->name(tensor_name(output_tensor));
node->op_version(opcodes[op.opcode_index].get()->version);
// NOTE We don't set quantization for While itself but to virtual outputs
}
// Create virtual outputs of While
for (uint32_t n = 0; n < output_count; ++n)
{
const circle::TensorT &output_tensor = *tensors[outputs[n]];
auto *nodeout = graph->nodes()->create<CircleWhileOut>();
nodeout->input(node);
nodeout->index(n);
copy_tensor_attributes(output_tensor, nodeout);
// Note: leave shape_status to UNKNOWN to run shape inference
context->nodefinder()->enroll(outputs[n], nodeout);
}
}
} // namespace luci
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