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/*
* Copyright (c) 2019 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 "moco/Import/Nodes/FakeQuantWithMinMaxVars.h"
#include <moco/IR/Nodes/TFFakeQuantWithMinMaxVars.h>
#include <moco/Names.h>
#include "Convert.h"
#include <plier/tf/Convert.h>
#include <loco/IR/PermutingCodec.h>
#include <memory>
#include <cassert>
using namespace plier::tf;
namespace
{
using namespace moco;
class TFFakeQuantWithMinMaxVarsGraphUpdate final : public GraphUpdate
{
public:
TFFakeQuantWithMinMaxVarsGraphUpdate(TFFakeQuantWithMinMaxVars *node,
std::vector<TensorName> names)
: _node(node), _names(names)
{
}
void input(const SymbolTable *) const override;
private:
TFFakeQuantWithMinMaxVars *_node;
std::vector<TensorName> _names;
};
void TFFakeQuantWithMinMaxVarsGraphUpdate::input(const SymbolTable *node_table) const
{
assert(_names.size() == 3);
auto inputs_node = node_table->node(_names[0]);
auto min_node = node_table->node(_names[1]);
auto max_node = node_table->node(_names[2]);
assert(inputs_node != nullptr);
assert(min_node != nullptr);
assert(max_node != nullptr);
_node->inputs(inputs_node);
_node->min(min_node);
_node->max(max_node);
}
} // namespace
namespace moco
{
bool FakeQuantWithMinMaxVarsGraphBuilder::validate(const tensorflow::NodeDef &node) const
{
if (node.input_size() != 3)
return false;
// attrs "narrow_range", "num_bits" are optional
return true;
}
void FakeQuantWithMinMaxVarsGraphBuilder::build(const tensorflow::NodeDef &node,
GraphBuilderContext *context) const
{
assert(context != nullptr);
loco::Graph *graph = context->graph();
SymbolTable *tensor_names = context->tensor_names();
UpdateQueue *updates = context->updates();
auto fakequant_node = graph->nodes()->create<TFFakeQuantWithMinMaxVars>();
fakequant_node->name(node.name());
// read optional attributes
if (has_attr(node, "num_bits"))
{
auto num_bits = get_int_attr(node, "num_bits");
fakequant_node->num_bits(num_bits);
}
if (has_attr(node, "narrow_range"))
{
auto narrow_range = get_bool_attr(node, "narrow_range");
fakequant_node->narrow_range(narrow_range);
}
// save the name for graph link updates
TensorName output_name(node.name(), 0);
tensor_names->enroll(output_name, fakequant_node);
std::vector<TensorName> input_names;
input_names.push_back(TensorName(node.input(0))); // inputs
input_names.push_back(TensorName(node.input(1))); // min
input_names.push_back(TensorName(node.input(2))); // max
// Record ifm inputs to featureEncode_node
auto tffakequant_update =
std::make_unique<TFFakeQuantWithMinMaxVarsGraphUpdate>(fakequant_node, input_names);
updates->enroll(std::move(tffakequant_update));
}
} // namespace moco
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