未验证 提交 d5a888e1 编写于 作者: T Tao Luo 提交者: GitHub

Merge pull request #15943 from kbinias/kbinias/add-placement-pass-tester

MKL-DNN: Add placement pass tester
......@@ -105,4 +105,5 @@ if (WITH_MKLDNN)
cc_test(test_conv_bias_mkldnn_fuse_pass SRCS mkldnn/conv_bias_mkldnn_fuse_pass_tester.cc DEPS conv_bias_mkldnn_fuse_pass naive_executor)
cc_test(test_conv_relu_mkldnn_fuse_pass SRCS mkldnn/conv_relu_mkldnn_fuse_pass_tester.cc DEPS conv_relu_mkldnn_fuse_pass)
cc_test(test_conv_elementwise_add_mkldnn_fuse_pass SRCS mkldnn/conv_elementwise_add_mkldnn_fuse_pass_tester.cc DEPS conv_elementwise_add_mkldnn_fuse_pass)
cc_test(test_mkldnn_placement_pass SRCS mkldnn/mkldnn_placement_pass_tester.cc DEPS mkldnn_placement_pass)
endif ()
......@@ -21,7 +21,7 @@ namespace ir {
std::unique_ptr<ir::Graph> MKLDNNPlacementPass::ApplyImpl(
std::unique_ptr<ir::Graph> graph) const {
VLOG(3) << "Aplies MKL-DNN placement strategy.";
VLOG(3) << "Applies MKL-DNN placement strategy.";
const auto& op_types_list =
Get<std::unordered_set<std::string>>("mkldnn_enabled_op_types");
for (const Node* n : graph->Nodes()) {
......
// Copyright (c) 2019 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 "paddle/fluid/framework/ir/mkldnn/mkldnn_placement_pass.h"
#include <gtest/gtest.h>
#include <boost/logic/tribool.hpp>
namespace paddle {
namespace framework {
namespace ir {
void SetOp(ProgramDesc* prog, const std::string& type, const std::string& name,
const std::vector<std::string>& inputs,
const std::vector<std::string>& outputs, boost::tribool use_mkldnn) {
auto* op = prog->MutableBlock(0)->AppendOp();
op->SetType(type);
if (!boost::indeterminate(use_mkldnn)) op->SetAttr("use_mkldnn", use_mkldnn);
if (type == "conv2d") {
op->SetAttr("name", name);
op->SetInput("Input", {inputs[0]});
op->SetInput("Filter", {inputs[1]});
op->SetInput("Bias", {inputs[2]});
} else if (type == "relu") {
op->SetInput("X", inputs);
} else if (type == "concat") {
op->SetAttr("axis", 1);
op->SetInput("X", {inputs[0], inputs[1]});
} else if (type == "pool2d") {
op->SetInput("X", {inputs[0]});
} else {
FAIL() << "Unexpected operator type.";
}
op->SetOutput("Out", {outputs[0]});
}
// operator use_mkldnn
// ---------------------------------------
// (a,b)->concat->c none
// (c,weights,bias)->conv->f none
// f->relu->g false
// g->pool->h false
// (h,weights2,bias2)->conv->k true
// k->relu->l true
ProgramDesc BuildProgramDesc() {
ProgramDesc prog;
for (auto& v :
std::vector<std::string>({"a", "b", "c", "weights", "bias", "f", "g",
"h", "weights2", "bias2", "k", "l"})) {
auto* var = prog.MutableBlock(0)->Var(v);
var->SetType(proto::VarType::SELECTED_ROWS);
if (v == "weights" || v == "bias") {
var->SetPersistable(true);
}
}
SetOp(&prog, "concat", "concat1", std::vector<std::string>({"a", "b"}),
std::vector<std::string>({"c"}), boost::indeterminate);
SetOp(&prog, "conv2d", "conv1",
std::vector<std::string>({"c", "weights", "bias"}),
std::vector<std::string>({"f"}), boost::indeterminate);
SetOp(&prog, "relu", "relu1", std::vector<std::string>({"f"}),
std::vector<std::string>({"g"}), false);
SetOp(&prog, "pool2d", "pool1", std::vector<std::string>({"g"}),
std::vector<std::string>({"h"}), false);
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"}), true);
return prog;
}
void MainTest(std::initializer_list<std::string> mkldnn_enabled_op_types,
unsigned expected_use_mkldnn_true_count) {
auto prog = BuildProgramDesc();
std::unique_ptr<ir::Graph> graph(new ir::Graph(prog));
auto pass = PassRegistry::Instance().Get("mkldnn_placement_pass");
pass->Set("mkldnn_enabled_op_types",
new std::unordered_set<std::string>(mkldnn_enabled_op_types));
graph = pass->Apply(std::move(graph));
unsigned use_mkldnn_true_count = 0;
for (auto* node : graph->Nodes()) {
if (node->IsOp()) {
auto* op = node->Op();
if (op->HasAttr("use_mkldnn") &&
boost::get<bool>(op->GetAttr("use_mkldnn"))) {
++use_mkldnn_true_count;
}
}
}
EXPECT_EQ(use_mkldnn_true_count, expected_use_mkldnn_true_count);
}
TEST(MKLDNNPlacementPass, enable_conv_relu) {
// 1 conv (1 conv is always true) + 2 relu (1 relu is always true) + 0 pool
MainTest({"conv2d", "relu"}, 3);
}
TEST(MKLDNNPlacementPass, enable_relu_pool) {
// 1 conv (1 conv is always true) + 2 relu (1 relu is always true) + 1 pool
MainTest({"relu", "pool2d"}, 4);
}
TEST(MKLDNNPlacementPass, enable_all) {
// 1 conv (1 conv is always true) + 2 relu (1 relu is always true) + 1 pool
MainTest({}, 4);
}
} // namespace ir
} // namespace framework
} // namespace paddle
USE_PASS(mkldnn_placement_pass);
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册