Add the test_conv_brelu_mkldnn_fuse_pass case.

test=develop

Author: guomingz

paddle/fluid/framework/ir/CMakeLists.txt

@@ -111,6 +111,7 @@ if (WITH_MKLDNN)
     cc_test(test_depthwise_conv_mkldnn_pass SRCS mkldnn/depthwise_conv_mkldnn_pass_tester.cc DEPS depthwise_conv_mkldnn_pass)
     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_brelu_mkldnn_fuse_pass SRCS mkldnn/conv_brelu_mkldnn_fuse_pass_tester.cc DEPS conv_brelu_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)
     cc_test(test_cpu_quantize_placement_pass SRCS mkldnn/cpu_quantize_placement_pass_tester.cc DEPS cpu_quantize_placement_pass)

paddle/fluid/framework/ir/mkldnn/conv_brelu_mkldnn_fuse_pass_tester.cc

@@ -0,0 +1,135 @@
+// 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/conv_brelu_mkldnn_fuse_pass.h"
+
+#include <gtest/gtest.h>
+#include "paddle/fluid/framework/op_proto_maker.h"
+
+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, bool use_mkldnn = false) {
+  auto* op = prog->MutableBlock(0)->AppendOp();
+  op->SetType(type);
+  if (type == "conv2d") {
+    op->SetAttr("use_mkldnn", use_mkldnn);
+    op->SetAttr("name", name);
+    op->SetInput("Input", {inputs[0]});
+    op->SetInput("Filter", {inputs[1]});
+    op->SetInput("Bias", {inputs[2]});
+  } else if (type == "relu6") {
+    op->SetAttr("use_mkldnn", use_mkldnn);
+    if (use_mkldnn) {
+      op->SetAttr("threshold", 6.0f);
+    }
+    op->SetInput("X", inputs);
+  }
+  op->SetOutput("Out", outputs);
+  op->SetAttr(OpProtoAndCheckerMaker::OpRoleAttrName(),
+              static_cast<int>(OpRole::kForward));
+}
+
+// a->OP0->b
+// b->OP1->c
+// (c, weights, bias)->conv->f
+// (f)->brelu->g
+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, "OP0", "op0", std::vector<std::string>({"a"}),
+        std::vector<std::string>({"b"}));
+  SetOp(&prog, "OP1", "op1", std::vector<std::string>({"b"}),
+        std::vector<std::string>({"c"}));
+  // conv+brelu, both with MKL-DNN
+  SetOp(&prog, "conv2d", "conv1",
+        std::vector<std::string>({"c", "weights", "bias"}),
+        std::vector<std::string>({"f"}), true);
+  SetOp(&prog, "relu6", "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+brelu, only one with MKL-DNN
+  SetOp(&prog, "conv2d", "conv2",
+        std::vector<std::string>({"h", "weights2", "bias2"}),
+        std::vector<std::string>({"k"}), true);
+  SetOp(&prog, "relu6", "relu2", std::vector<std::string>({"k"}),
+        std::vector<std::string>({"l"}));
+
+  return prog;
+}
+
+TEST(ConvBReLUFusePass, basic) {
+  auto prog = BuildProgramDesc();
+
+  std::unique_ptr<ir::Graph> graph(new ir::Graph(prog));
+
+  auto pass = PassRegistry::Instance().Get("conv_brelu_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, BRELU, conv_out
+  // Add 1 Node: ConvBReLU
+  EXPECT_EQ(original_nodes_num - 2, current_nodes_num);
+
+  // Assert conv_brelu op in newly generated graph
+  int conv_brelu_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_brelu"));
+        ASSERT_TRUE(op->HasAttr("fuse_brelu_threshold"));
+
+        bool fuse_brelu = boost::get<bool>(op->GetAttr("fuse_brelu"));
+        if (fuse_brelu) {
+          ++conv_brelu_count;
+          float fuse_brelu_threshold =
+              boost::get<float>(op->GetAttr("fuse_brelu_threshold"));
+          EXPECT_EQ(fuse_brelu_threshold, 6.0f);
+        }
+      } else if (op_name == "conv2") {
+        ASSERT_FALSE(op->HasAttr("fuse_brelu"));
+      }
+    }
+  }
+  EXPECT_EQ(conv_brelu_count, 1);
+}
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle
+
+USE_PASS(conv_brelu_mkldnn_fuse_pass);