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Paddle/paddle/fluid/framework/ir/shuffle_channel_detect_pass.cc

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3.4 KiB

// Copyright (c) 2018 PaddlePaddle Authors. 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 <string>
#include "paddle/fluid/framework/ir/shuffle_channel_detect_pass.h"
#include "paddle/fluid/framework/op_version_registry.h"
namespace paddle {
namespace framework {
namespace ir {
#define GET_IR_NODE(node__) GET_IR_NODE_FROM_SUBGRAPH(node__, node__, pattern);
#define GET_NODES \
GET_IR_NODE(reshape1_op); \
GET_IR_NODE(reshape1_out); \
GET_IR_NODE(transpose_op); \
GET_IR_NODE(transpose_out); \
GET_IR_NODE(reshape2_op); \
GET_IR_NODE(reshape2_out);
void ShuffleChannelDetectPass::ApplyImpl(ir::Graph* graph) const {
const std::string pattern_name = "shufflechannel_pattern";
FusePassBase::Init(pattern_name, graph);
GraphPatternDetector gpd;
auto* x = gpd.mutable_pattern()
->NewNode("x")
->assert_is_op_input("reshape2", "X")
->AsInput();
patterns::ShuffleChannelPattern pattern(gpd.mutable_pattern(), pattern_name);
pattern(x);
auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
Graph* g) {
GET_NODES;
PADDLE_ENFORCE_GT(
subgraph.count(x), 0,
platform::errors::NotFound("Detector did not find input X."));
auto* input_node = subgraph.at(x);
auto reshape1_desc = reshape1_op->Op();
auto reshape2_desc = reshape2_op->Op();
std::string input_name = input_node->Name();
std::string output_name = reshape2_out->Name();
auto reshape1_shape =
BOOST_GET_CONST(std::vector<int>, reshape1_desc->GetAttr("shape"));
auto reshape2_shape =
BOOST_GET_CONST(std::vector<int>, reshape2_desc->GetAttr("shape"));
int i_c = reshape1_shape[2];
int o_c = reshape2_shape[1];
int group = o_c / i_c;
framework::OpDesc new_op_desc;
new_op_desc.SetType("shuffle_channel");
new_op_desc.SetInput("X", {input_name});
new_op_desc.SetOutput("Out", {output_name});
new_op_desc.SetAttr("group", group);
new_op_desc.Flush();
// Create a new node for the fused op.
auto* new_op = graph->CreateOpNode(&new_op_desc);
IR_NODE_LINK_TO(input_node, new_op);
IR_NODE_LINK_TO(new_op, reshape2_out);
// Delete the unneeded nodes.
GraphSafeRemoveNodes(graph, {reshape1_op, reshape1_out, transpose_op,
transpose_out, reshape2_op});
LOG_FIRST_N(WARNING, 1)
<< "There is fluid.layers.shuffle_channel API already, maybe you can "
"use it instead of (reshape + transpose + reshape)";
};
gpd(graph, handler);
}
} // namespace ir
} // namespace framework
} // namespace paddle
REGISTER_PASS(shuffle_channel_detect_pass,
paddle::framework::ir::ShuffleChannelDetectPass);
REGISTER_PASS_CAPABILITY(shuffle_channel_detect_pass)
.AddCombination(
paddle::framework::compatible::OpVersionComparatorCombination()
.EQ("reshape2", 0)
.EQ("transpose2", 0));