test=developrevert-15296-async_double_buffered_py_reader
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// 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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#include "paddle/fluid/framework/ir/identity_scale_op_clean_pass.h"
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#include <string>
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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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std::unique_ptr<ir::Graph> IdentityScaleOpCleanPass::ApplyImpl(
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std::unique_ptr<ir::Graph> graph) const {
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FusePassBase::Init("identity_scale_op_clean", graph.get());
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// pre_op -> scale_in -> scale_op -> scale_out
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// ->
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// pre_op -> scale_out
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GraphPatternDetector detector;
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auto pre_op = detector.mutable_pattern()->NewNode("pre_op")->assert_is_op();
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auto scale_in = detector.mutable_pattern()
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->NewNode("scale_in")
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->assert_is_op_input("scale")
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->AsIntermediate();
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auto scale_op = detector.mutable_pattern()
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->NewNode("scale_fuse")
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->assert_is_op("scale")
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->assert_op_attr<float>("scale", 1.)
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->assert_op_attr<float>("bias", 0.);
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auto scale_out = detector.mutable_pattern()
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->NewNode("scale_out")
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->assert_is_op_output("scale");
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pre_op->LinksTo({scale_in});
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scale_op->LinksFrom({scale_in}).LinksTo({scale_out});
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GraphPatternDetector::handle_t handler = [&](
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const GraphPatternDetector::subgraph_t& subgraph, Graph* graph) {
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Node* scale_op_var = subgraph.at(scale_op);
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Node* scale_in_var = subgraph.at(scale_in);
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Node* scale_out_var = subgraph.at(scale_out);
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Node* pre_op_var = subgraph.at(pre_op);
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// Link pre_op directly to scale_out
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const std::string scale_in_name = scale_in_var->Name();
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const std::string scale_out_name = scale_out_var->Name();
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// Remove links in graph
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GraphSafeRemoveNodes(graph, {scale_in_var, scale_op_var});
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// Modify proto message
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auto* pre_op_desc = pre_op_var->Op();
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for (auto& parameter : *pre_op_desc->Proto()->mutable_outputs()) {
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auto* arguments = parameter.mutable_arguments();
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auto it = std::find(arguments->begin(), arguments->end(), scale_in_name);
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PADDLE_ENFORCE(it != arguments->end());
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*it = scale_out_name;
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}
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IR_NODE_LINK_TO(pre_op_var, scale_out_var);
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};
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detector(graph.get(), handler);
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return graph;
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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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REGISTER_PASS(identity_scale_op_clean_pass,
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paddle::framework::ir::IdentityScaleOpCleanPass);
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@ -0,0 +1,33 @@
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// 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 "paddle/fluid/framework/ir/fuse_pass_base.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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class IdentityScaleOpCleanPass : public FusePassBase {
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protected:
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std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
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private:
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virtual ~IdentityScaleOpCleanPass() = default;
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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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