Add generalized Conv+Activation MKLDNN fuse pass creation Part2 (#19237)
* Add generalized Conv+Activation MKLDNN fuse pass creation Part2 test=develop * Undefined behaviour of GetAttrIfExists<> FIX test=developpadding_in_crf
Adam
6 years ago
committed by
Tao Luo
parent
37428952c6
commit
97d1db1874
@ -1,71 +0,0 @@
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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/mkldnn/conv_brelu_mkldnn_fuse_pass.h"
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#include <string>
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#include <vector>
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#include "paddle/fluid/platform/enforce.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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void ConvBReLUFusePass::ApplyImpl(ir::Graph* graph) const {
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PADDLE_ENFORCE(graph);
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FusePassBase::Init("conv_bounded_relu_mkldnn_fuse", graph);
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GraphPatternDetector gpd;
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auto* conv_input = gpd.mutable_pattern()
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->NewNode("conv_bounded_relu_mkldnn_fuse/conv_input")
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->AsInput()
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->assert_is_op_input("conv2d", "Input");
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patterns::ConvBReLU conv_brelu_pattern(gpd.mutable_pattern(),
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"conv_bounded_relu_mkldnn_fuse");
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conv_brelu_pattern(conv_input);
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int found_conv_brelu_count = 0;
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auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
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Graph* g) {
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VLOG(4) << "handle ConvBoundedReLUFusePass fuse";
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GET_IR_NODE_FROM_SUBGRAPH(conv_weight, conv_weight,
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conv_brelu_pattern); // Filter
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GET_IR_NODE_FROM_SUBGRAPH(conv_out, conv_out, conv_brelu_pattern); // tmp
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GET_IR_NODE_FROM_SUBGRAPH(conv, conv, conv_brelu_pattern); // CONV op
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GET_IR_NODE_FROM_SUBGRAPH(brelu_out, brelu_out, conv_brelu_pattern); // Out
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GET_IR_NODE_FROM_SUBGRAPH(brelu, brelu, conv_brelu_pattern); // ReLU op
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// Transform Conv node into ConvBReLU node.
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OpDesc* desc = conv->Op();
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desc->SetOutput("Output", std::vector<std::string>({brelu_out->Name()}));
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desc->SetAttr("fuse_brelu", true);
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desc->SetAttr("fuse_brelu_threshold", brelu->Op()->GetAttr("threshold"));
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GraphSafeRemoveNodes(graph, {brelu, conv_out});
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PADDLE_ENFORCE(subgraph.count(conv_input));
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IR_NODE_LINK_TO(conv, brelu_out);
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found_conv_brelu_count++;
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};
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gpd(graph, handler);
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AddStatis(found_conv_brelu_count);
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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(conv_brelu_mkldnn_fuse_pass,
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paddle::framework::ir::ConvBReLUFusePass);
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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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#include "paddle/fluid/framework/ir/graph.h"
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#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
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#include "paddle/fluid/framework/ir/pass.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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* Fuse the CONV and ReLU6 to a ConvReLU6Op.
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*/
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class ConvBReLUFusePass : public FusePassBase {
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public:
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virtual ~ConvBReLUFusePass() {}
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protected:
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void ApplyImpl(ir::Graph* graph) const override;
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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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@ -1,135 +0,0 @@
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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/mkldnn/conv_brelu_mkldnn_fuse_pass.h"
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#include <gtest/gtest.h>
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#include "paddle/fluid/framework/op_proto_maker.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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void SetOp(ProgramDesc* prog, const std::string& type, const std::string& name,
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const std::vector<std::string>& inputs,
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const std::vector<std::string>& outputs, bool use_mkldnn = false) {
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auto* op = prog->MutableBlock(0)->AppendOp();
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op->SetType(type);
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if (type == "conv2d") {
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op->SetAttr("use_mkldnn", use_mkldnn);
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op->SetAttr("name", name);
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op->SetInput("Input", {inputs[0]});
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op->SetInput("Filter", {inputs[1]});
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op->SetInput("Bias", {inputs[2]});
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} else if (type == "relu6") {
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op->SetAttr("use_mkldnn", use_mkldnn);
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if (use_mkldnn) {
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op->SetAttr("threshold", 6.0f);
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}
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op->SetInput("X", inputs);
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}
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op->SetOutput("Out", outputs);
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op->SetAttr(OpProtoAndCheckerMaker::OpRoleAttrName(),
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static_cast<int>(OpRole::kForward));
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}
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// a->OP0->b
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// b->OP1->c
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// (c, weights, bias)->conv->f
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// (f)->brelu->g
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ProgramDesc BuildProgramDesc() {
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ProgramDesc prog;
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for (auto& v :
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std::vector<std::string>({"a", "b", "c", "weights", "bias", "f", "g",
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"h", "weights2", "bias2", "k", "l"})) {
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auto* var = prog.MutableBlock(0)->Var(v);
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var->SetType(proto::VarType::SELECTED_ROWS);
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if (v == "weights" || v == "bias") {
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var->SetPersistable(true);
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}
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}
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SetOp(&prog, "OP0", "op0", std::vector<std::string>({"a"}),
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std::vector<std::string>({"b"}));
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SetOp(&prog, "OP1", "op1", std::vector<std::string>({"b"}),
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std::vector<std::string>({"c"}));
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// conv+brelu, both with MKL-DNN
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SetOp(&prog, "conv2d", "conv1",
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std::vector<std::string>({"c", "weights", "bias"}),
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std::vector<std::string>({"f"}), true);
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SetOp(&prog, "relu6", "relu1", std::vector<std::string>({"f"}),
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std::vector<std::string>({"g"}), true);
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SetOp(&prog, "OP3", "op3", std::vector<std::string>({"g"}),
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std::vector<std::string>({"h"}));
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// conv+brelu, only one with MKL-DNN
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SetOp(&prog, "conv2d", "conv2",
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std::vector<std::string>({"h", "weights2", "bias2"}),
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std::vector<std::string>({"k"}), true);
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SetOp(&prog, "relu6", "relu2", std::vector<std::string>({"k"}),
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std::vector<std::string>({"l"}));
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return prog;
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}
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TEST(ConvBReLUFusePass, basic) {
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auto prog = BuildProgramDesc();
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std::unique_ptr<ir::Graph> graph(new ir::Graph(prog));
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auto pass = PassRegistry::Instance().Get("conv_brelu_mkldnn_fuse_pass");
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int original_nodes_num = graph->Nodes().size();
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graph.reset(pass->Apply(graph.release()));
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int current_nodes_num = graph->Nodes().size();
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// Remove 3 Nodes: CONV, BRELU, conv_out
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// Add 1 Node: ConvBReLU
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EXPECT_EQ(original_nodes_num - 2, current_nodes_num);
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// Assert conv_brelu op in newly generated graph
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int conv_brelu_count = 0;
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for (auto* node : graph->Nodes()) {
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if (node->IsOp() && node->Op()->Type() == "conv2d") {
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auto* op = node->Op();
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ASSERT_TRUE(op->HasAttr("use_mkldnn"));
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EXPECT_TRUE(boost::get<bool>(op->GetAttr("use_mkldnn")));
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// check if only "conv1" convolution is fused
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auto op_name = boost::get<std::string>(op->GetAttr("name"));
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if (op_name == "conv1") {
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ASSERT_TRUE(op->HasAttr("fuse_brelu"));
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ASSERT_TRUE(op->HasAttr("fuse_brelu_threshold"));
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bool fuse_brelu = boost::get<bool>(op->GetAttr("fuse_brelu"));
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if (fuse_brelu) {
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++conv_brelu_count;
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float fuse_brelu_threshold =
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boost::get<float>(op->GetAttr("fuse_brelu_threshold"));
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EXPECT_EQ(fuse_brelu_threshold, 6.0f);
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}
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} else if (op_name == "conv2") {
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ASSERT_FALSE(op->HasAttr("fuse_brelu"));
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}
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}
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}
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EXPECT_EQ(conv_brelu_count, 1);
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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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USE_PASS(conv_brelu_mkldnn_fuse_pass);
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@ -1,76 +0,0 @@
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// Copyright (c) 2018 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/mkldnn/conv_relu_mkldnn_fuse_pass.h"
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#include <string>
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#include <vector>
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#include "paddle/fluid/platform/enforce.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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void ConvReLUFusePass::ApplyImpl(ir::Graph* graph) const {
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PADDLE_ENFORCE(graph);
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FusePassBase::Init("conv_relu_mkldnn_fuse", graph);
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GraphPatternDetector gpd;
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auto* conv_input = gpd.mutable_pattern()
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->NewNode("conv_relu_mkldnn_fuse/conv_input")
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->AsInput()
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->assert_is_op_input("conv2d", "Input");
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patterns::ConvReLU conv_relu_pattern(gpd.mutable_pattern(),
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"conv_relu_mkldnn_fuse");
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conv_relu_pattern(conv_input);
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int found_conv_relu_count = 0;
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auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
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Graph* g) {
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VLOG(4) << "handle ConvReLU fuse";
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GET_IR_NODE_FROM_SUBGRAPH(conv_weight, conv_weight,
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conv_relu_pattern); // Filter
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GET_IR_NODE_FROM_SUBGRAPH(conv_out, conv_out, conv_relu_pattern); // tmp
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GET_IR_NODE_FROM_SUBGRAPH(conv, conv, conv_relu_pattern); // CONV op
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GET_IR_NODE_FROM_SUBGRAPH(relu_out, relu_out, conv_relu_pattern); // Out
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GET_IR_NODE_FROM_SUBGRAPH(relu, relu, conv_relu_pattern); // ReLU op
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FuseOptions fuse_option = FindFuseOption(*conv, *relu);
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if (fuse_option == DO_NOT_FUSE) {
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VLOG(3) << "do not perform conv+relu fuse";
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return;
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}
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// Transform Conv node into ConvReLU node.
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OpDesc* desc = conv->Op();
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desc->SetOutput("Output", std::vector<std::string>({relu_out->Name()}));
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desc->SetAttr("fuse_relu", true);
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GraphSafeRemoveNodes(graph, {relu, conv_out});
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PADDLE_ENFORCE(subgraph.count(conv_input));
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IR_NODE_LINK_TO(conv, relu_out);
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found_conv_relu_count++;
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};
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gpd(graph, handler);
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AddStatis(found_conv_relu_count);
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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(conv_relu_mkldnn_fuse_pass,
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paddle::framework::ir::ConvReLUFusePass);
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@ -1,39 +0,0 @@
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// Copyright (c) 2018 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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#include "paddle/fluid/framework/ir/graph.h"
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#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
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#include "paddle/fluid/framework/ir/pass.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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* Fuse the CONV and ReLU to a ConvReLUOp.
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*/
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class ConvReLUFusePass : public FusePassBase {
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public:
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virtual ~ConvReLUFusePass() {}
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protected:
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void ApplyImpl(ir::Graph* graph) const override;
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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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@ -1,127 +0,0 @@
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// Copyright (c) 2018 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/mkldnn/conv_relu_mkldnn_fuse_pass.h"
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#include <gtest/gtest.h>
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#include "paddle/fluid/framework/op_proto_maker.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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void SetOp(ProgramDesc* prog, const std::string& type, const std::string& name,
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const std::vector<std::string>& inputs,
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const std::vector<std::string>& outputs, bool use_mkldnn = false) {
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auto* op = prog->MutableBlock(0)->AppendOp();
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op->SetType(type);
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if (type == "conv2d") {
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op->SetAttr("use_mkldnn", use_mkldnn);
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op->SetAttr("name", name);
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op->SetInput("Input", {inputs[0]});
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op->SetInput("Filter", {inputs[1]});
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op->SetInput("Bias", {inputs[2]});
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} else if (type == "relu") {
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op->SetAttr("use_mkldnn", use_mkldnn);
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op->SetInput("X", inputs);
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}
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op->SetOutput("Out", outputs);
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op->SetAttr(OpProtoAndCheckerMaker::OpRoleAttrName(),
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static_cast<int>(OpRole::kForward));
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}
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// a->OP0->b
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// b->OP1->c
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// (c, weights, bias)->conv->f
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// (f)->relu->g
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ProgramDesc BuildProgramDesc() {
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ProgramDesc prog;
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for (auto& v :
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std::vector<std::string>({"a", "b", "c", "weights", "bias", "f", "g",
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"h", "weights2", "bias2", "k", "l"})) {
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auto* var = prog.MutableBlock(0)->Var(v);
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var->SetType(proto::VarType::SELECTED_ROWS);
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if (v == "weights" || v == "bias") {
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var->SetPersistable(true);
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}
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}
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SetOp(&prog, "OP0", "op0", std::vector<std::string>({"a"}),
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std::vector<std::string>({"b"}));
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SetOp(&prog, "OP1", "op1", std::vector<std::string>({"b"}),
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std::vector<std::string>({"c"}));
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// conv+relu, both with MKL-DNN
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SetOp(&prog, "conv2d", "conv1",
|
||||
std::vector<std::string>({"c", "weights", "bias"}),
|
||||
std::vector<std::string>({"f"}), true);
|
||||
SetOp(&prog, "relu", "relu1", std::vector<std::string>({"f"}),
|
||||
std::vector<std::string>({"g"}), true);
|
||||
SetOp(&prog, "OP3", "op3", std::vector<std::string>({"g"}),
|
||||
std::vector<std::string>({"h"}));
|
||||
// conv+relu, only one with MKL-DNN
|
||||
SetOp(&prog, "conv2d", "conv2",
|
||||
std::vector<std::string>({"h", "weights2", "bias2"}),
|
||||
std::vector<std::string>({"k"}), true);
|
||||
SetOp(&prog, "relu", "relu2", std::vector<std::string>({"k"}),
|
||||
std::vector<std::string>({"l"}));
|
||||
|
||||
return prog;
|
||||
}
|
||||
|
||||
TEST(ConvReLUFusePass, basic) {
|
||||
auto prog = BuildProgramDesc();
|
||||
|
||||
std::unique_ptr<ir::Graph> graph(new ir::Graph(prog));
|
||||
|
||||
auto pass = PassRegistry::Instance().Get("conv_relu_mkldnn_fuse_pass");
|
||||
|
||||
int original_nodes_num = graph->Nodes().size();
|
||||
|
||||
graph.reset(pass->Apply(graph.release()));
|
||||
|
||||
int current_nodes_num = graph->Nodes().size();
|
||||
|
||||
// Remove 3 Nodes: CONV, RELU, conv_out
|
||||
// Add 1 Node: ConvReLU
|
||||
EXPECT_EQ(original_nodes_num - 2, current_nodes_num);
|
||||
|
||||
// Assert conv_relu op in newly generated graph
|
||||
int conv_relu_count = 0;
|
||||
|
||||
for (auto* node : graph->Nodes()) {
|
||||
if (node->IsOp() && node->Op()->Type() == "conv2d") {
|
||||
auto* op = node->Op();
|
||||
ASSERT_TRUE(op->HasAttr("use_mkldnn"));
|
||||
EXPECT_TRUE(boost::get<bool>(op->GetAttr("use_mkldnn")));
|
||||
// check if only "conv1" convolution is fused
|
||||
auto op_name = boost::get<std::string>(op->GetAttr("name"));
|
||||
if (op_name == "conv1") {
|
||||
ASSERT_TRUE(op->HasAttr("fuse_relu"));
|
||||
bool fuse_relu = boost::get<bool>(op->GetAttr("fuse_relu"));
|
||||
if (fuse_relu) {
|
||||
++conv_relu_count;
|
||||
}
|
||||
} else if (op_name == "conv2") {
|
||||
ASSERT_FALSE(op->HasAttr("fuse_relu"));
|
||||
}
|
||||
}
|
||||
}
|
||||
EXPECT_EQ(conv_relu_count, 1);
|
||||
}
|
||||
|
||||
} // namespace ir
|
||||
} // namespace framework
|
||||
} // namespace paddle
|
||||
|
||||
USE_PASS(conv_relu_mkldnn_fuse_pass);
|
||||
Loading…
Reference in new issue