add feed operator

paddle/framework/scope.cc

@@ -13,6 +13,8 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include "paddle/framework/scope.h"
+#include <memory>  // for unique_ptr
+#include <mutex>   // for call_once
 #include "paddle/string/printf.h"
 
 namespace paddle {
@@ -62,5 +64,19 @@ void Scope::DropKids() {
   kids_.clear();
 }
 
+std::once_flag feed_variable_flag;
+
+template <typename T, typename... Args>
+std::unique_ptr<T> make_unique(Args&&... args) {
+  return std::unique_ptr<T>(new T(std::forward<Args>(args)...));
+}
+
+framework::Scope* GetScope() {
+  static std::unique_ptr<framework::Scope> g_scope =
+      make_unique<framework::Scope>();
+  std::call_once(feed_variable_flag, [&]() { g_scope->NewVar("feed_value"); });
+  return g_scope.get();
+}
+
 }  // namespace framework
 }  // namespace paddle

paddle/framework/scope.h

@@ -73,5 +73,7 @@ class Scope {
   DISABLE_COPY_AND_ASSIGN(Scope);
 };
 
+framework::Scope* GetScope();
+
 }  // namespace framework
 }  // namespace paddle

paddle/operators/activation_op.cu

 /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
 
-   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
+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
+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. */
+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. */
 
 #define EIGEN_USE_GPU
 #include "paddle/operators/activation_op.h"

paddle/operators/feed_op.cc

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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/operators/feed_op.h"
+
+namespace paddle {
+namespace operators {
+
+class FeedOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+ protected:
+  void InferShape(framework::InferShapeContextBase* ctx) const override {
+    typedef std::vector<framework::Tensor> FeedInputs;
+    PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output should be not null.");
+    int col = ctx->Attrs().Get<int>("col");
+    framework::Variable* g_feed_variable =
+        framework::GetScope()->FindVar("feed_value");
+    FeedInputs tensors = g_feed_variable->Get<FeedInputs>();
+    auto in_dim = tensors[col].dims();
+    ctx->SetOutputDim("Y", in_dim);
+    // need to handle LodTensor later
+  }
+};
+
+class FeedOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  FeedOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+      : OpProtoAndCheckerMaker(proto, op_checker) {
+    AddAttr<int>("col", "The col in Global Feed Variable");
+    AddOutput("Out", "The output of dropout op.");
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OP_WITHOUT_GRADIENT(feed, ops::FeedOp, ops::FeedOpMaker);
+REGISTER_OP_CPU_KERNEL(feed, ops::FeedKernel<float>);

paddle/operators/feed_op.cu

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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/operators/feed_op.h"
+
+namespace ops = paddle::operators;
+REGISTER_OP_GPU_KERNEL(feed, ops::FeedKernel<float>);

paddle/operators/feed_op.h

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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/framework/eigen.h"
+#include "paddle/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+using Tensor = framework::Tensor;
+
+template <typename T>
+class FeedKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    typedef std::vector<framework::Tensor> FeedInputs;
+    Tensor* out = ctx.Output<Tensor>("Out");
+    out->mutable_data<T>(ctx.GetPlace());
+    framework::Variable* g_feed_variable =
+        framework::GetScope()->FindVar("feed_value");
+    int col = ctx.template Attr<int>("col");
+    FeedInputs tensors = g_feed_variable->Get<FeedInputs>();
+    out->CopyFrom<T>(tensors[col], ctx.GetPlace());
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle