Michal Gallus
7 years ago
parent
91e8fbac2f
commit
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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/conv_bias_mkldnn_fuse_pass.h"
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#include <gtest/gtest.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,
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const std::vector<std::string>& inputs,
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const std::vector<std::string>& outputs) {
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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", true);
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op->SetInput("Input", {inputs[0]});
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op->SetInput("Filter", {inputs[1]});
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} else if (type == "elementwise_add") {
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op->SetInput("X", {inputs[0]});
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op->SetInput("Y", {inputs[1]});
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}
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op->SetOutput("Out", outputs);
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}
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// a->OP0->b
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// b->OP1->c
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// (c, weights)->conv->f
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// (f, bias)->elementwise_add->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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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", std::vector<std::string>({"a"}),
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std::vector<std::string>({"b"}));
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SetOp(&prog, "OP1", std::vector<std::string>({"b"}),
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std::vector<std::string>({"c"}));
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SetOp(&prog, "conv2d", std::vector<std::string>({"c", "weights"}),
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std::vector<std::string>({"f"}));
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SetOp(&prog, "elementwise_add", std::vector<std::string>({"f", "bias"}),
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std::vector<std::string>({"g"}));
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return prog;
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}
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TEST(ConvBiasFusePass, 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_bias_mkldnn_fuse_pass");
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int original_nodes_num = graph->Nodes().size();
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graph = pass->Apply(std::move(graph));
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int current_nodes_num = graph->Nodes().size();
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// Remove 3 Nodes: conv, elementwise_add, conv_out
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// Add 1 Node: ConvBias
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EXPECT_EQ(original_nodes_num - 2, current_nodes_num);
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// Assert conv_bias op in newly generated graph
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int conv_bias_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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if (node->Op()->HasAttr("use_mkldnn")) {
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bool use_mkldnn = boost::get<bool>(node->Op()->GetAttr("use_mkldnn"));
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if (use_mkldnn) {
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auto names = node->Op()->InputNames();
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if (std::find(names.begin(), names.end(), "Bias") != names.end()) {
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conv_bias_count++;
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}
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}
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}
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}
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}
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EXPECT_EQ(conv_bias_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_bias_mkldnn_fuse_pass);
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