Merge pull request #14903 from NHZlX/add_conv_elementwise_pass

Add conv + elementwiseAdd pass

paddle/fluid/framework/ir/CMakeLists.txt

@@ -44,6 +44,7 @@ pass_library(seqconv_eltadd_relu_fuse_pass inference)
 pass_library(is_test_pass base)
 pass_library(conv_elementwise_add_act_fuse_pass inference)
 pass_library(conv_elementwise_add2_act_fuse_pass inference)
+pass_library(conv_elementwise_add_fuse_pass inference)
 if(WITH_MKLDNN)
     pass_library(mkldnn_placement_pass base)
     pass_library(depthwise_conv_mkldnn_pass base)

paddle/fluid/framework/ir/conv_elementwise_add_fuse_pass.cc

@@ -0,0 +1,91 @@
+// 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/conv_elementwise_add_fuse_pass.h"
+#include "paddle/fluid/framework/ir/graph_viz_pass.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(conv_op);              \
+  GET_IR_NODE(conv_out);             \
+  GET_IR_NODE(conv_filter);          \
+  GET_IR_NODE(elementwise_add_op);   \
+  GET_IR_NODE(elementwise_add_in_y); \
+  GET_IR_NODE(elementwise_add_out);
+
+std::unique_ptr<ir::Graph> ConvElementwiseAddFusePass::ApplyImpl(
+    std::unique_ptr<ir::Graph> graph) const {
+  const std::string pattern_name = "conv_elementwise_add_fuse";
+  FusePassBase::Init(pattern_name, graph.get());
+
+  GraphPatternDetector gpd;
+  auto* x = gpd.mutable_pattern()
+                ->NewNode("x")
+                ->assert_is_op_input("conv2d", "Input")
+                ->AsInput();
+
+  patterns::ConvElementwiseadd pattern(gpd.mutable_pattern(), pattern_name);
+  pattern(x);
+
+  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
+                     Graph* g) {
+    GET_NODES;
+
+    auto base_op_desc = *conv_op->Op()->Proto();
+    std::string bias_name = elementwise_add_in_y->Name();
+    std::string output_name = elementwise_add_out->Name();
+
+    std::string act_type = "identity";
+    framework::OpDesc new_op_desc(base_op_desc, nullptr);
+    new_op_desc.SetType("conv2d_fusion");
+    new_op_desc.SetInput("Bias", {bias_name});
+    new_op_desc.SetInput("ResidualData", {});
+    new_op_desc.SetAttr("activation", act_type);
+    new_op_desc.SetOutput("Output", {output_name});
+    new_op_desc.SetAttr("is_test", true);
+    new_op_desc.SetAttr("use_cudnn", false);
+    new_op_desc.Flush();
+
+    // Create a new node for the fused op.
+    auto* new_conv_op = graph->CreateOpNode(&new_op_desc);
+
+    // Link inputs and outputs.
+    PADDLE_ENFORCE(subgraph.count(x));
+    auto* conv_in_node = subgraph.at(x);
+
+    IR_NODE_LINK_TO(conv_in_node, new_conv_op);          // Input
+    IR_NODE_LINK_TO(conv_filter, new_conv_op);           // Filter
+    IR_NODE_LINK_TO(elementwise_add_in_y, new_conv_op);  // Bias
+    IR_NODE_LINK_TO(new_conv_op, elementwise_add_out);   // Output
+
+    // Delete the unneeded nodes.
+    GraphSafeRemoveNodes(graph.get(), {conv_op, conv_out, elementwise_add_op});
+  };
+
+  gpd(graph.get(), handler);
+  return graph;
+}
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle
+
+REGISTER_PASS(conv_elementwise_add_fuse_pass,
+              paddle::framework::ir::ConvElementwiseAddFusePass);

paddle/fluid/framework/ir/conv_elementwise_add_fuse_pass.h

@@ -0,0 +1,33 @@
+// 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.
+
+#pragma once
+#include "paddle/fluid/framework/ir/fuse_pass_base.h"
+#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
+
+namespace paddle {
+namespace framework {
+namespace ir {
+
+class ConvElementwiseAddFusePass : public FusePassBase {
+ public:
+  virtual ~ConvElementwiseAddFusePass() {}
+
+ protected:
+  std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
+};
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle

paddle/fluid/framework/ir/graph_pattern_detector.cc

@@ -17,7 +17,6 @@
 #include <string>
 #include <vector>
 
-#include "graph_pattern_detector.h"
 #include "paddle/fluid/framework/ir/graph_helper.h"
 #include "paddle/fluid/framework/ir/graph_pattern_detector.h"
 #include "paddle/fluid/framework/ir/graph_traits.h"
@@ -1210,6 +1209,33 @@ PDNode *patterns::ConvElementwiseadd2Act::operator()(PDNode *conv_in) {
   return act_out;
 }
 
+PDNode *patterns::ConvElementwiseadd::operator()(PDNode *conv_in) {
+  conv_in->AsInput();
+  auto conv_op = pattern->NewNode(conv_op_repr())->assert_is_op("conv2d");
+  auto conv_out = pattern->NewNode(conv_out_repr())
+                      ->assert_is_op_output("conv2d")
+                      ->assert_is_op_input("elementwise_add", "X")
+                      ->AsIntermediate();
+  auto conv_filter = pattern->NewNode(conv_filter_repr())
+                         ->assert_is_op_input("conv2d", "Filter")
+                         ->AsInput();
+  auto elementwise_add_op = pattern->NewNode(elementwise_add_op_repr())
+                                ->assert_is_op("elementwise_add");
+  auto elementwise_add_in_y = pattern->NewNode(elementwise_add_in_y_repr())
+                                  ->assert_is_op_input("elementwise_add", "Y")
+                                  ->AsInput();
+  auto elementwise_add_out = pattern->NewNode(elementwise_add_out_repr())
+                                 ->assert_is_op_output("elementwise_add")
+                                 ->AsOutput();
+
+  conv_op->LinksFrom({conv_in, conv_filter});
+  conv_out->LinksFrom({conv_op});
+  elementwise_add_op->LinksFrom({conv_out, elementwise_add_in_y})
+      .LinksTo({elementwise_add_out});
+
+  return elementwise_add_out;
+}
+
 }  // namespace ir
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/ir/graph_pattern_detector.h

@@ -716,6 +716,24 @@ struct ConvElementwiseadd2Act : public PatternBase {
   PATTERN_DECL_NODE(act_out);
 };
 
+// Conv + ElementwiseAdd
+// This pattern should be used after ConvElementwiseadd2Act or
+// ConvElementwiseadd pass
+struct ConvElementwiseadd : public PatternBase {
+  ConvElementwiseadd(PDPattern* pattern, const std::string& name_scope)
+      : PatternBase(pattern, name_scope, "conv_elementwiseadd") {}
+
+  PDNode* operator()(PDNode* conv_in);
+
+  PATTERN_DECL_NODE(conv_op);
+  PATTERN_DECL_NODE(conv_out);
+  PATTERN_DECL_NODE(conv_filter);
+
+  PATTERN_DECL_NODE(elementwise_add_op);
+  PATTERN_DECL_NODE(elementwise_add_in_y);
+  PATTERN_DECL_NODE(elementwise_add_out);
+};
+
 }  // namespace patterns
 
 // Link two ir::Nodes from each other.

paddle/fluid/inference/analysis/ir_passes/tensorrt_subgraph_pass.cc

@@ -63,7 +63,6 @@ std::unique_ptr<framework::ir::Graph> analysis::TensorRtSubgraphPass::ApplyImpl(
 void TensorRtSubgraphPass::CreateTensorRTOp(framework::ir::Node *node,
                                             Graph *graph) const {
   auto *op_desc = node->Op();
-  static int counter{0};
   auto &subgraph = *Agent(node).subgraph();
   PADDLE_ENFORCE(!subgraph.empty());
 
@@ -192,8 +191,6 @@ void TensorRtSubgraphPass::CreateTensorRTOp(framework::ir::Node *node,
           block_desc.Proto()->SerializeAsString());
   SetAttr(op_desc->Proto(), "max_batch_size", Get<int>("max_batch_size"));
   SetAttr(op_desc->Proto(), "workspace_size", Get<int>("workspace_size"));
-  SetAttr(op_desc->Proto(), "engine_uniq_key",
-          "trt-" + std::to_string(counter++));
   SetAttr(op_desc->Proto(), "parameters", ExtractParameters(graph->Nodes()));
   SetAttr(op_desc->Proto(), "output_name_mapping", output_mapping);
 }

paddle/fluid/inference/api/paddle_pass_builder.h

@@ -122,6 +122,7 @@ class GpuPassStrategy : public PassStrategy {
         "conv_bn_fuse_pass",                    //
         "conv_elementwise_add_act_fuse_pass",   //
         "conv_elementwise_add2_act_fuse_pass",  //
+        "conv_elementwise_add_fuse_pass",       //
     });
   }
 

paddle/fluid/inference/tensorrt/convert/op_converter.h

@@ -103,6 +103,7 @@ class OpConverter {
   void ConvertBlock(const framework::proto::BlockDesc& block,
                     const std::unordered_set<std::string>& parameters,
                     const framework::Scope& scope, TensorRTEngine* engine) {
+    std::unique_lock<std::mutex> lk(mut_);
     for (int i = 0; i < block.ops_size(); i++) {
       const auto& op = block.ops(i);
       ConvertOp(op, parameters, scope, engine);
@@ -125,6 +126,7 @@ class OpConverter {
   std::unordered_map<std::string, OpConverter*> converters_;
   // fluid inference scope
   framework::Scope* scope_{nullptr};
+  std::mutex mut_;
 };
 
 }  // namespace tensorrt

paddle/fluid/operators/tensorrt/CMakeLists.txt

@@ -1,5 +1,5 @@
 op_library(tensorrt_engine_op DEPS tensorrt_engine tensorrt_converter)
-file(APPEND ${pybind_file} "USE_CUDA_ONLY_OP(tensorrt_engine);\n")
+file(APPEND ${pybind_file} "USE_NO_KERNEL_OP(tensorrt_engine);\n")
 nv_test(test_tensorrt_engine_op SRCS tensorrt_engine_op_test.cc
   DEPS tensorrt_engine_op
   analysis)

paddle/fluid/operators/tensorrt/tensorrt_engine_op.cc

@@ -21,8 +21,6 @@
 
 namespace paddle {
 
-DEFINE_int32(tensorrt_engine_batch_size, 1, "the batch_size of TensorRT");
-
 namespace operators {
 
 class TensorRTEngineOpMaker : public framework::OpProtoAndCheckerMaker {
@@ -31,7 +29,6 @@ class TensorRTEngineOpMaker : public framework::OpProtoAndCheckerMaker {
     AddInput("Xs", "A list of inputs.").AsDuplicable();
     AddOutput("Ys", "A list of outputs").AsDuplicable();
     AddAttr<std::string>("subgraph", "the subgraph.");
-    AddAttr<std::string>("engine_uniq_key", "unique key for the TRT engine.");
     AddAttr<int>("max_batch_size", "the maximum batch size.");
     AddAttr<int>("workspace_size", "the workspace size.");
     AddComment("TensorRT engine operator.");
@@ -50,6 +47,6 @@ class TensorRTEngineInferVarType : public framework::VarTypeInference {
 namespace ops = paddle::operators;
 
 REGISTER_OPERATOR(tensorrt_engine, ops::TensorRTEngineOp,
-                  ops::TensorRTEngineOpMaker, ops::TensorRTEngineOpMaker);
+                  ops::TensorRTEngineOpMaker);
 
 #endif  // PADDLE_WITH_CUDA

paddle/fluid/operators/tensorrt/tensorrt_engine_op.cu.cc

@@ -1,24 +0,0 @@
-/* Copyright (c) 2016 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/operators/tensorrt/tensorrt_engine_op.h"
-
-namespace ops = paddle::operators;
-
-REGISTER_OP_CUDA_KERNEL(
-    tensorrt_engine,
-    ops::TensorRTEngineKernel<paddle::platform::CUDADeviceContext, float>,
-    ops::TensorRTEngineKernel<paddle::platform::CUDADeviceContext, double>,
-    ops::TensorRTEngineKernel<paddle::platform::CUDADeviceContext, int>,
-    ops::TensorRTEngineKernel<paddle::platform::CUDADeviceContext, int64_t>);

paddle/fluid/operators/tensorrt/tensorrt_engine_op_test.cc

@@ -24,8 +24,7 @@ limitations under the License. */
 #include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
 #include "paddle/fluid/inference/tensorrt/convert/ut_helper.h"
 
-USE_CUDA_ONLY_OP(tensorrt_engine);
-
+USE_NO_KERNEL_OP(tensorrt_engine);
 namespace paddle {
 namespace operators {