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67 lines
2.1 KiB
67 lines
2.1 KiB
// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <memory>
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#include <string>
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#include <unordered_map>
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#include <utility>
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#include "paddle/fluid/framework/ir/fuse_pass_base.h"
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#include "paddle/fluid/framework/ir/graph.h"
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#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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/*
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* Map variable name to tensor of scaling factors scaling it to MAX=1.0.
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* bool denotes whether quantization of the variable should be done to unsigned
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* type.
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*/
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using VarQuantScale =
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std::unordered_map<std::string, std::pair<bool, LoDTensor>>;
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/*
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* Quantize all supported operators.
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*/
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class CPUQuantizePass : public FusePassBase {
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public:
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virtual ~CPUQuantizePass() {}
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protected:
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std::unique_ptr<ir::Graph> ApplyImpl(
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std::unique_ptr<ir::Graph> graph) const override;
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void QuantizeConv(Graph* graph, bool with_residual_data = false) const;
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void QuantizePool(Graph* graph) const;
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void QuantizeInput(Graph* g, Node* op, Node* input, std::string input_name,
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double scale_to_one, bool is_unsigned,
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std::string scale_attr_name = "") const;
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void DequantizeOutput(Graph* g, Node* op, Node* output,
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std::string output_name, double scale_to_one,
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bool is_unsigned,
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std::string scale_attr_name = "") const;
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const std::string name_scope_{"quantize"};
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};
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} // namespace ir
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} // namespace framework
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} // namespace paddle
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