paddle-anakin: concat, split, pool2d converter#16003

paddle/fluid/inference/anakin/CMakeLists.txt

 cc_library(anakin_engine SRCS engine.cc)
+nv_library(anakin_op_teller SRCS op_teller.cc DEPS framework_proto)
 target_link_libraries(anakin_engine anakin anakin_saber_common)
 cc_test(test_anakin_engine SRCS test_anakin_engine.cc DEPS anakin_engine)
 add_subdirectory(convert)

paddle/fluid/inference/anakin/convert/CMakeLists.txt

-cc_library(anakin_op_converter SRCS fc.cc conv2d.cc activation.cc DEPS anakin_engine framework_proto scope operator op_registry)
-cc_test(test_anakin_fc SRCS test_fc_op.cc DEPS anakin_op_converter mul_op)
+cc_library(anakin_op_converter SRCS fc.cc conv2d.cc activation.cc pool2d.cc concat.cc split.cc DEPS anakin_engine framework_proto scope op_registry)
+cc_test(test_anakin_fc SRCS test_fc_op.cc DEPS  ${FLUID_CORE_MODULES} ${GLOB_OPERATOR_DEPS}  anakin_op_converter mul_op)
 cc_test(test_anakin_conv2d SRCS test_conv2d_op.cc DEPS ${FLUID_CORE_MODULES} ${GLOB_OPERATOR_DEPS} anakin_op_converter conv_op im2col vol2col depthwise_conv SERIAL)
-cc_test(test_anakin_activation SRCS test_activation_op.cc DEPS ${FLUID_CORE_MODULES} ${GLOB_OPERATOR_DEPS} activation_op anakin_op_converter SERIAL)
+cc_test(test_anakin_activation SRCS test_activation_op.cc DEPS ${FLUID_CORE_MODULES} ${GLOB_OPERATOR_DEPS} activation_op anakin_op_converter
+ SERIAL)
+cc_test(test_anakin_pool2d SRCS test_pool2d_op.cc DEPS  ${FLUID_CORE_MODULES} ${GLOB_OPERATOR_DEPS} anakin_op_converter pool_op pooling)
+cc_test(test_anakin_concat SRCS test_concat_op.cc DEPS  ${FLUID_CORE_MODULES} ${GLOB_OPERATOR_DEPS} anakin_op_converter concat_op concat_and_split)
+cc_test(test_anakin_split SRCS test_split_op.cc DEPS  ${FLUID_CORE_MODULES} ${GLOB_OPERATOR_DEPS} anakin_op_converter split_op concat_and_split)

paddle/fluid/inference/anakin/convert/concat.cc

+// 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 "paddle/fluid/inference/anakin/convert/concat.h"
+#include <algorithm>
+
+using anakin::graph::GraphGlobalMem;
+using anakin::AK_FLOAT;
+using anakin::Precision;
+using anakin::saber::NV;
+using anakin::saber::X86;
+using anakin::saber::Shape;
+using anakin::PBlock;
+using anakin::PTuple;
+
+namespace paddle {
+namespace inference {
+namespace anakin {
+
+void ConcatOpConverter::operator()(const framework::proto::OpDesc &op,
+                                   const framework::Scope &scope,
+                                   bool test_mode) {
+  framework::OpDesc op_desc(op, nullptr);
+  auto input_names = op_desc.Input("X");
+  int axis = boost::get<int>(op_desc.GetAttr("axis"));
+  PADDLE_ENFORCE(axis > 0,
+                 "The axis attr of Concat op should be large than 0 for trt");
+
+  auto y_name = op_desc.Output("Out").front();
+  auto op_name = op_desc.Type() + ":" + op_desc.Output("Out").front();
+
+  engine_->AddOp(op_name, "Concat", input_names, {y_name});
+  engine_->AddOpAttr(op_name, "axis", axis);
+}
+
+}  // namespace anakin
+}  // namespace inference
+}  // namespace paddle
+
+REGISTER_ANAKIN_OP_CONVERTER(concat, ConcatOpConverter);

paddle/fluid/inference/anakin/convert/concat.h

+// 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/inference/anakin/convert/op_converter.h"
+
+namespace paddle {
+namespace inference {
+namespace anakin {
+
+class ConcatOpConverter : public AnakinOpConverter {
+ public:
+  ConcatOpConverter() = default;
+
+  virtual void operator()(const framework::proto::OpDesc &op,
+                          const framework::Scope &scope,
+                          bool test_mode) override;
+  virtual ~ConcatOpConverter() {}
+
+ private:
+};
+
+}  // namespace anakin
+}  // namespace inference
+}  // namespace paddle

paddle/fluid/inference/anakin/convert/conv2d.cc

@@ -48,7 +48,6 @@ void Conv2dOpConverter::operator()(const framework::proto::OpDesc &op,
   weight_tensor->Resize(filter_t->dims());
   TensorCopySync((*filter_t), platform::CPUPlace(), weight_tensor.get());
 
-  auto *weight_data = weight_tensor->mutable_data<float>(platform::CPUPlace());
   PADDLE_ENFORCE_EQ(weight_tensor->dims().size(), 4UL);
 
   // const int n_output = weight_tensor->dims()[0];

paddle/fluid/inference/anakin/convert/pool2d.cc

+// 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 "paddle/fluid/inference/anakin/convert/pool2d.h"
+#include <algorithm>
+#include <string>
+#include <vector>
+
+using anakin::graph::GraphGlobalMem;
+using anakin::AK_FLOAT;
+using anakin::Precision;
+using anakin::saber::NV;
+using anakin::saber::X86;
+using anakin::saber::Shape;
+using anakin::PBlock;
+using anakin::PTuple;
+
+namespace paddle {
+namespace inference {
+namespace anakin {
+
+void Pool2dOpConverter::operator()(const framework::proto::OpDesc &op,
+                                   const framework::Scope &scope,
+                                   bool test_mode) {
+  framework::OpDesc op_desc(op, nullptr);
+  PADDLE_ENFORCE_EQ(op_desc.Input("X").size(), 1);
+  PADDLE_ENFORCE_EQ(op_desc.Output("Out").size(), 1);
+
+  auto x_name = op_desc.Input("X").front();
+  auto y_name = op_desc.Output("Out").front();
+  auto op_name = op_desc.Type() + ":" + op_desc.Output("Out").front();
+
+  bool global_pooling = boost::get<bool>(op_desc.GetAttr("global_pooling"));
+  std::string pool_type =
+      boost::get<std::string>(op_desc.GetAttr("pooling_type"));
+  std::vector<int> ksize =
+      boost::get<std::vector<int>>(op_desc.GetAttr("ksize"));
+  std::vector<int> strides =
+      boost::get<std::vector<int>>(op_desc.GetAttr("strides"));
+  std::vector<int> paddings =
+      boost::get<std::vector<int>>(op_desc.GetAttr("paddings"));
+  bool ceil_mode = boost::get<bool>(op_desc.GetAttr("ceil_mode"));
+  std::string anakin_pool_type;
+  if (pool_type == "max") {
+    anakin_pool_type = "MAX";
+  } else if (pool_type == "avg") {
+    anakin_pool_type = "AVG";
+  } else {
+    PADDLE_THROW("TensorRT unsupported pooling type!");
+  }
+
+  engine_->AddOp(op_name, "Pooling", {x_name}, {y_name});
+  engine_->AddOpAttr<PTuple<int>>(op_name, "pool_size", ksize);
+  engine_->AddOpAttr<PTuple<int>>(op_name, "strides", strides);
+  engine_->AddOpAttr<PTuple<int>>(op_name, "padding", paddings);
+  engine_->AddOpAttr(op_name, "method", anakin_pool_type);
+  engine_->AddOpAttr(op_name, "global_pooling", global_pooling);
+  engine_->AddOpAttr(op_name, "cmp_out_shape_floor_as_conv", !ceil_mode);
+}
+
+}  // namespace anakin
+}  // namespace inference
+}  // namespace paddle
+
+REGISTER_ANAKIN_OP_CONVERTER(pool2d, Pool2dOpConverter);

paddle/fluid/inference/anakin/convert/pool2d.h

+// 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/inference/anakin/convert/op_converter.h"
+
+namespace paddle {
+namespace inference {
+namespace anakin {
+
+class Pool2dOpConverter : public AnakinOpConverter {
+ public:
+  Pool2dOpConverter() = default;
+
+  virtual void operator()(const framework::proto::OpDesc &op,
+                          const framework::Scope &scope,
+                          bool test_mode) override;
+  virtual ~Pool2dOpConverter() {}
+
+ private:
+};
+
+}  // namespace anakin
+}  // namespace inference
+}  // namespace paddle

paddle/fluid/inference/anakin/convert/split.cc

+// 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 "paddle/fluid/inference/anakin/convert/split.h"
+#include <algorithm>
+#include <vector>
+
+using anakin::graph::GraphGlobalMem;
+using anakin::AK_FLOAT;
+using anakin::Precision;
+using anakin::saber::NV;
+using anakin::saber::X86;
+using anakin::saber::Shape;
+using anakin::PBlock;
+using anakin::PTuple;
+
+namespace paddle {
+namespace inference {
+namespace anakin {
+
+void SplitOpConverter::operator()(const framework::proto::OpDesc &op,
+                                  const framework::Scope &scope,
+                                  bool test_mode) {
+  framework::OpDesc op_desc(op, nullptr);
+  auto input_name = op_desc.Input("X").front();
+  auto y_names = op_desc.Output("Out");
+  auto op_name = op_desc.Type() + ":" + op_desc.Output("Out").front();
+  int axis = boost::get<int>(op_desc.GetAttr("axis"));
+
+  std::vector<int> output_lengths =
+      boost::get<std::vector<int>>(op_desc.GetAttr("sections"));
+
+  int split_num = output_lengths.size();
+  PADDLE_ENFORCE(split_num > 1,
+                 "anakin split op converter: the split num should > 1");
+  int num_sum = 0;
+  std::vector<int> slice_point;
+  for (int i = 0; i < split_num - 1; i++) {
+    num_sum += output_lengths[i];
+    slice_point.push_back(num_sum);
+  }
+  engine_->AddOp(op_name, "Slice", {input_name}, y_names);
+  engine_->AddOpAttr(op_name, "axis", axis);
+  engine_->AddOpAttr<PTuple<int>>(op_name, "slice_point", slice_point);
+  // slice_dim is useless in anakin
+  engine_->AddOpAttr(op_name, "slice_dim", 4);
+}
+
+}  // namespace anakin
+}  // namespace inference
+}  // namespace paddle
+REGISTER_ANAKIN_OP_CONVERTER(split, SplitOpConverter);

paddle/fluid/inference/anakin/convert/split.h

+// 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/inference/anakin/convert/op_converter.h"
+
+namespace paddle {
+namespace inference {
+namespace anakin {
+
+class SplitOpConverter : public AnakinOpConverter {
+ public:
+  SplitOpConverter() = default;
+
+  virtual void operator()(const framework::proto::OpDesc &op,
+                          const framework::Scope &scope,
+                          bool test_mode) override;
+  virtual ~SplitOpConverter() {}
+
+ private:
+};
+
+}  // namespace anakin
+}  // namespace inference
+}  // namespace paddle

paddle/fluid/inference/anakin/convert/test_concat_op.cc

+/* 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 <gtest/gtest.h>
+#include "paddle/fluid/inference/anakin/convert/concat.h"
+#include "paddle/fluid/inference/anakin/convert/op_converter.h"
+#include "paddle/fluid/inference/anakin/convert/ut_helper.h"
+
+namespace paddle {
+namespace inference {
+namespace anakin {
+
+TEST(concat_op, test) {
+  std::unordered_set<std::string> parameters({""});
+  framework::Scope scope;
+  AnakinConvertValidation validator(parameters, scope);
+  validator.DeclInputVar("concat_x1", {1, 10, 3, 1});
+  validator.DeclInputVar("concat_x2", {1, 3, 3, 1});
+  validator.DeclInputVar("concat_x3", {1, 7, 3, 1});
+  validator.DeclOutputVar("concat_out", {1, 20, 3, 1});
+
+  // Prepare Op description
+  framework::OpDesc desc;
+  desc.SetType("concat");
+  desc.SetInput("X", {"concat_x1", "concat_x2", "concat_x3"});
+  desc.SetOutput("Out", {"concat_out"});
+
+  int axis = 1;
+  desc.SetAttr("axis", axis);
+
+  validator.SetOp(*desc.Proto());
+
+  validator.Execute(1);
+}
+
+}  // namespace anakin
+}  // namespace inference
+}  // namespace paddle
+USE_OP(concat);
+USE_ANAKIN_CONVERTER(concat);

paddle/fluid/inference/anakin/convert/test_pool2d_op.cc

+/* 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 <gtest/gtest.h>
+#include "paddle/fluid/inference/anakin/convert/op_converter.h"
+#include "paddle/fluid/inference/anakin/convert/ut_helper.h"
+
+namespace paddle {
+namespace inference {
+namespace anakin {
+
+void test_pool2d(bool global_pooling, bool ceil_mode,
+                 std::string pool_type = "max") {
+  auto* pool2d_converter =
+      Registry<AnakinOpConverter>::Global().Lookup("pool2d");
+  ASSERT_TRUE(pool2d_converter);
+
+  framework::Scope scope;
+  std::unordered_set<std::string> parameters;
+  AnakinConvertValidation validator(parameters, scope);
+
+  // The ITensor's Dims should not contain the batch size.
+  // So, the ITensor's Dims of input and output should be C * H * W.
+  validator.DeclInputVar("pool2d_x", {1, 3, 6, 7});
+  if (global_pooling)
+    validator.DeclOutputVar("pool2d_out", {1, 3, 1, 1});
+  else if (ceil_mode)
+    validator.DeclOutputVar("pool2d_out", {1, 3, 3, 4});
+  else
+    validator.DeclOutputVar("pool2d_out", {1, 3, 3, 3});
+
+  // Prepare Op description
+  framework::OpDesc desc;
+  desc.SetType("pool2d");
+  desc.SetInput("X", {"pool2d_x"});
+  desc.SetOutput("Out", {"pool2d_out"});
+
+  std::vector<int> ksize({2, 2});
+  std::vector<int> strides({2, 2});
+  std::vector<int> paddings({0, 0});
+  std::string pooling_t = pool_type;
+
+  desc.SetAttr("pooling_type", pooling_t);
+  desc.SetAttr("ksize", ksize);
+  desc.SetAttr("strides", strides);
+  desc.SetAttr("paddings", paddings);
+  desc.SetAttr("global_pooling", global_pooling);
+  desc.SetAttr("ceil_mode", ceil_mode);
+
+  LOG(INFO) << "set OP";
+  validator.SetOp(*desc.Proto());
+  LOG(INFO) << "execute";
+
+  validator.Execute(1);
+}
+
+TEST(Pool2dOpConverter, normal) { test_pool2d(false, false); }
+TEST(Pool2dOpConverter, test_global_pooling) { test_pool2d(true, false); }
+
+TEST(Pool2dOpConverter, max_ceil_test) { test_pool2d(false, true); }
+TEST(Pool2dOpConverter, avg_ceil_test) { test_pool2d(false, true, "avg"); }
+
+}  // namespace anakin
+}  // namespace inference
+}  // namespace paddle
+
+USE_OP(pool2d);
+USE_ANAKIN_CONVERTER(pool2d);

paddle/fluid/inference/anakin/convert/test_split_op.cc

+/* 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 <gtest/gtest.h>
+#include "paddle/fluid/inference/anakin/convert/op_converter.h"
+#include "paddle/fluid/inference/anakin/convert/split.h"
+#include "paddle/fluid/inference/anakin/convert/ut_helper.h"
+
+namespace paddle {
+namespace inference {
+namespace anakin {
+
+template <int Axis>
+void AnakinSliceTest(const std::vector<int> &in_shape,
+                     const std::vector<int> &sections) {
+  std::unordered_set<std::string> parameters({""});
+  framework::Scope scope;
+  AnakinConvertValidation validator(parameters, scope);
+
+  validator.DeclInputVar("split_input", in_shape);
+  std::vector<std::string> output_vars;
+  for (size_t i = 0; i < sections.size(); ++i) {
+    auto out_shape = in_shape;
+    out_shape[Axis] = sections[i];
+    std::string output_name = "split_out" + std::to_string(i);
+    validator.DeclOutputVar(output_name, out_shape);
+    output_vars.push_back(output_name);
+  }
+
+  // Prepare Op description
+  framework::OpDesc desc;
+  desc.SetType("split");
+  desc.SetInput("X", {"split_input"});
+  desc.SetOutput("Out", output_vars);
+
+  desc.SetAttr("axis", Axis);
+  desc.SetAttr("num", 0);
+  desc.SetAttr("sections", sections);
+
+  validator.SetOp(*desc.Proto());
+
+  validator.Execute(1);
+}
+
+// batch = 0, axis = 1, same shape
+TEST(split_op, test_same_shape_axis1_batch1) {
+  AnakinSliceTest<1>({1, 4, 2, 2}, {2, 2});
+}
+// batch = 0, axis = 1, different shape
+TEST(split_op, test_different_shape_axis1_batch1) {
+  AnakinSliceTest<1>({1, 3, 2, 2}, {2, 1});
+}
+// batch = 10, axis = 1, same shape
+TEST(split_op, test_same_shape_axis1_batch10) {
+  AnakinSliceTest<1>({1, 4, 2, 2}, {2, 2});
+}
+// batch = 10, axis = 1, different shape
+TEST(split_op, test_different_shape_axis1_batch10) {
+  AnakinSliceTest<1>({1, 3, 2, 2}, {2, 1});
+}
+// batch = 0, axis = 2, same shape
+TEST(split_op, test_same_shape_axis2_batch1) {
+  AnakinSliceTest<2>({1, 3, 4, 2}, {2, 2});
+}
+// batch = 0, axis = 2, different shape
+TEST(split_op, test_different_shape_axis2_batch1) {
+  AnakinSliceTest<2>({1, 3, 3, 2}, {2, 1});
+}
+// batch = 10, axis = 2, same shape
+TEST(split_op, test_same_shape_axis2_batch10) {
+  AnakinSliceTest<2>({1, 3, 4, 2}, {2, 2});
+}
+// batch = 10, axis = 2, different shape
+TEST(split_op, test_different_shape_axis2_batch10) {
+  AnakinSliceTest<2>({1, 3, 3, 2}, {2, 1});
+}
+// batch = 0, axis = 3, same shape
+TEST(split_op, test_same_shape_axis3_batch1) {
+  AnakinSliceTest<3>({1, 3, 2, 4}, {2, 2});
+}
+// batch = 0, axis = 3, different shape
+TEST(split_op, test_different_shape_axis3_batch1) {
+  AnakinSliceTest<3>({1, 3, 2, 3}, {2, 1});
+}
+// batch = 10, axis = 3, same shape
+TEST(split_op, test_same_shape_axis3_batch10) {
+  AnakinSliceTest<3>({1, 3, 2, 4}, {2, 2});
+}
+// batch = 10, axis = 3, different shape
+TEST(split_op, test_different_shape_axis3_batch10) {
+  AnakinSliceTest<3>({1, 3, 2, 3}, {2, 1});
+}
+
+}  // namespace anakin
+}  // namespace inference
+}  // namespace paddle
+
+USE_OP(split);
+USE_ANAKIN_CONVERTER(split);

paddle/fluid/inference/anakin/op_teller.cc

+// 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/inference/anakin/op_teller.h"
+
+namespace paddle {
+namespace inference {
+namespace anakin {
+
+// Just tell by the op_types.
+struct SimpleOpTypeSetTeller : public Teller {
+  SimpleOpTypeSetTeller() {}
+
+  bool operator()(const std::string& op_type,
+                  const framework::OpDesc& desc) override {
+    return teller_set.count(op_type);
+  }
+
+ private:
+  std::unordered_set<std::string> teller_set{{"mul"}};
+};
+
+bool OpTeller::Tell(const std::string& op_type, const framework::OpDesc& desc) {
+  for (auto& teller : tellers_) {
+    if ((*teller)(op_type, desc)) return true;
+  }
+  return false;
+}
+
+OpTeller::OpTeller() { tellers_.emplace_back(new SimpleOpTypeSetTeller); }
+
+}  // namespace anakin
+}  // namespace inference
+}  // namespace paddle

paddle/fluid/inference/anakin/op_teller.h

+// 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.
+
+#pragma once
+#include <memory>
+#include <string>
+#include <unordered_set>
+#include <vector>
+#include "paddle/fluid/framework/op_desc.h"
+
+namespace paddle {
+namespace inference {
+namespace anakin {
+
+/*
+ * Single Op teller definition.
+ * One can override this and define a more complex tell logic, considerring more
+ * issues such as op_desc.
+ */
+struct Teller {
+  virtual bool operator()(const std::string& op_type,
+                          const framework::OpDesc& desc) = 0;
+
+  virtual ~Teller() = default;
+};
+/*
+ * A real example:
+ *
+ * struct SomeTeller : public Teller {
+ * bool operator()(const std::string& op_type,
+ *                const framework::OpDesc& desc) override {
+ *  return op_type == "fc" && desc.Inputs().size() == 2;
+ * }
+ *};
+ */
+
+/*
+ * class OpTeller helps to tell whether a fluid
+ * operator can be transformed to a TensorRT layer.
+ */
+class OpTeller {
+ public:
+  static OpTeller& Global() {
+    static std::unique_ptr<OpTeller> x(new OpTeller);
+    return *x;
+  }
+
+  bool Tell(const std::string& op_type, const framework::OpDesc& desc);
+
+ private:
+  OpTeller();
+
+ private:
+  std::vector<std::unique_ptr<Teller>> tellers_;
+};
+
+}  // namespace anakin
+}  // namespace inference
+}  // namespace paddle

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

@@ -45,7 +45,7 @@ class EngineIOConverter {
   static void ConvertInput(const std::string& op_type, const LoDTensor& in,
                            void* out, size_t max_size, cudaStream_t* stream) {
     PADDLE_ENFORCE(stream != nullptr);
-    auto* converter = Registry<EngineIOConverter>::Lookup(
+    auto* converter = Registry<EngineIOConverter>::Global().Lookup(
         op_type, "default" /* default_type */);
     PADDLE_ENFORCE_NOT_NULL(converter);
     converter->SetStream(stream);
@@ -56,7 +56,7 @@ class EngineIOConverter {
                             LoDTensor* out, size_t max_size,
                             cudaStream_t* stream) {
     PADDLE_ENFORCE(stream != nullptr);
-    auto* converter = Registry<EngineIOConverter>::Lookup(
+    auto* converter = Registry<EngineIOConverter>::Global().Lookup(
         op_type, "default" /* default_type */);
     PADDLE_ENFORCE_NOT_NULL(converter);
     converter->SetStream(stream);
@@ -72,7 +72,7 @@ class EngineIOConverter {
 #define REGISTER_TENSORRT_IO_CONVERTER(op_type__, Converter__)                 \
   struct trt_io_##op_type__##_converter {                                      \
     trt_io_##op_type__##_converter() {                                         \
-      Registry<EngineIOConverter>::Register<Converter__>(#op_type__); \
+      Registry<EngineIOConverter>::Global().Register<Converter__>(#op_type__); \
     }                                                                          \
   };                                                                           \
   trt_io_##op_type__##_converter trt_io_##op_type__##_converter__;

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

@@ -86,7 +86,7 @@ class OpConverter {
       PADDLE_ENFORCE_EQ(op_desc.Input("Y").size(), 1UL);
       std::string Y = op_desc.Input("Y")[0];
       if (parameters.count(Y)) {
-        it = Registry<OpConverter>::Lookup("fc");
+        it = Registry<OpConverter>::Global().Lookup("fc");
       }
     }
     if (op_desc.Type().find("elementwise") != std::string::npos) {
@@ -103,28 +103,28 @@ class OpConverter {
       if (parameters.count(Y)) {
         PADDLE_ENFORCE(add_weight_op_set.count(op_type) > 0,
                        "Unsupported elementwise type" + op_type);
-        it =
-            Registry<OpConverter>::Lookup("elementwise_" + op_type + "_weight");
+        it = Registry<OpConverter>::Global().Lookup("elementwise_" + op_type +
+                                                    "_weight");
         PADDLE_ENFORCE_NOT_NULL(it, "no OpConverter for optype [%s]",
                                 op_desc.Type());
       } else {
         PADDLE_ENFORCE(add_tensor_op_set.count(op_type) > 0,
                        "Unsupported elementwise type" + op_type);
-        it =
-            Registry<OpConverter>::Lookup("elementwise_" + op_type + "_tensor");
+        it = Registry<OpConverter>::Global().Lookup("elementwise_" + op_type +
+                                                    "_tensor");
       }
       PADDLE_ENFORCE_NOT_NULL(it, "no OpConverter for optype [%s]",
                               op_desc.Type());
     }
 
     if (op_desc.Type() == "depthwise_conv2d") {
-      it = Registry<OpConverter>::Lookup("conv2d");
+      it = Registry<OpConverter>::Global().Lookup("conv2d");
       PADDLE_ENFORCE_NOT_NULL(it, "no OpConverter for optype [%s]",
                               op_desc.Type());
     }
 
     if (!it) {
-      it = Registry<OpConverter>::Lookup(op_desc.Type());
+      it = Registry<OpConverter>::Global().Lookup(op_desc.Type());
     }
     PADDLE_ENFORCE_NOT_NULL(it, "no OpConverter for optype [%s]",
                             op_desc.Type());