Merge remote-tracking branch 'baidu/develop' into executor_impl

paddle/framework/type_defs.h

@@ -15,6 +15,7 @@
 #pragma once
 #include <functional>
 #include <map>
+#include <memory>
 #include "paddle/platform/variant.h"
 
 namespace paddle {

paddle/operators/fill_constant_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/fill_constant_op.h"
+
+namespace paddle {
+namespace operators {
+
+class FillConstantOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+ protected:
+  void InferShape(framework::InferShapeContext *ctx) const override {
+    PADDLE_ENFORCE(ctx->HasOutput("Out"),
+                   "Output(Out) of FillConstantOp should not be null.");
+    auto &shape = ctx->Attrs().Get<std::vector<int>>("shape");
+    std::vector<int64_t> shape_int64(shape.size(), 0);
+    std::transform(shape.begin(), shape.end(), shape_int64.begin(),
+                   [](int a) { return static_cast<int64_t>(a); });
+    auto dims = framework::make_ddim(shape_int64);
+    ctx->SetOutputDim("Out", dims);
+  }
+
+  framework::DataType IndicateDataType(
+      const framework::ExecutionContext &ctx) const override {
+    return static_cast<framework::DataType>(ctx.Attr<int>("dataType"));
+  }
+};
+
+class FillConstantOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  FillConstantOpMaker(framework::OpProto *proto,
+                      framework::OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+    AddAttr<int>("dataType",
+                 "(int, default 5 (FP32)) "
+                 "Output data type")
+        .SetDefault(framework::DataType::FP32);
+    AddAttr<std::vector<int>>("shape", "(vector<int>) The shape of the output");
+    AddAttr<float>("value", "(float, default 0) The value to be filled")
+        .SetDefault(0.0f);
+    AddOutput("Out",
+              "(Tensor) Tensor of specified shape will be filled "
+              "with the specified value");
+    AddComment(R"DOC(Fill up a variable with specified constant value.)DOC");
+  }
+};
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OP_WITHOUT_GRADIENT(fill_constant, ops::FillConstantOp,
+                             ops::FillConstantOpMaker);
+REGISTER_OP_CPU_KERNEL(
+    fill_constant,
+    ops::FillConstantOpKernel<paddle::platform::CPUPlace, float>);

paddle/operators/fill_constant_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. */
+
+#define EIGEN_USE_GPU
+#include "paddle/framework/op_registry.h"
+#include "paddle/operators/fill_constant_op.h"
+
+namespace ops = paddle::operators;
+REGISTER_OP_GPU_KERNEL(
+    fill_constant,
+    ops::FillConstantOpKernel<paddle::platform::GPUPlace, float>);

paddle/operators/fill_constant_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 {
+
+template <typename Place, typename T>
+class FillConstantOpKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    auto* out = ctx.Output<framework::Tensor>("Out");
+    out->mutable_data<T>(ctx.GetPlace());
+    auto value = ctx.Attr<T>("value");
+
+    auto out_eigen = framework::EigenVector<T>::Flatten(*out);
+    auto place = ctx.GetEigenDevice<Place>();
+    out_eigen.device(place) = out_eigen.constant(static_cast<T>(value));
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

paddle/operators/interp_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/framework/op_registry.h"
+#include "paddle/operators/net_op.h"
+
+namespace paddle {
+namespace operators {
+
+class InterpOp : public NetOp {
+ public:
+  InterpOp(const std::string &type, const framework::VariableNameMap &inputs,
+           const framework::VariableNameMap &outputs,
+           const framework::AttributeMap &attrs)
+      : NetOp(type, inputs, outputs, attrs) {
+    PADDLE_ENFORCE_NE(Input("X"), framework::kEmptyVarName,
+                      "Input(X) of InterpOp should not be null.");
+    PADDLE_ENFORCE_NE(Input("Y"), framework::kEmptyVarName,
+                      "Input(Y) of InterpOp should not be null.");
+    PADDLE_ENFORCE_NE(Input("W"), framework::kEmptyVarName,
+                      "Input(W) of InterpOp should not be null.");
+    PADDLE_ENFORCE_NE(Output("SubOut"), framework::kEmptyVarName,
+                      "Output(SubOut) of InterpOp should not be null.");
+    PADDLE_ENFORCE_NE(Output("MulOut"), framework::kEmptyVarName,
+                      "Output(MulOut) of InterpOp should not be null.");
+    PADDLE_ENFORCE_NE(Output("Out"), framework::kEmptyVarName,
+                      "Output(Out) of InterpOp should not be null.");
+
+    // SubOut = X - Y
+    auto x = Input("X");
+    auto y = Input("Y");
+    auto sub_out = Output("SubOut");
+    AppendOp(framework::OpRegistry::CreateOp(
+        "elementwise_sub", {{"X", {x}}, {"Y", {y}}}, {{"Out", {sub_out}}}, {}));
+
+    // MulOut = SubOut * W = (X - Y) * W
+    auto w = Input("W");
+    auto mul_out = Output("MulOut");
+    AppendOp(framework::OpRegistry::CreateOp(
+        "elementwise_mul", {{"X", {sub_out}}, {"Y", {w}}}, {{"Out", {mul_out}}},
+        {{"axis", 0}}));
+
+    // Out = MulOut + Y = (X - Y) * W + Y = X * W + Y * (1 - W)
+    AppendOp(framework::OpRegistry::CreateOp("elementwise_add",
+                                             {{"X", {mul_out}}, {"Y", {y}}},
+                                             {{"Out", {Output("Out")}}}, {}));
+
+    CompleteAddOp(false);
+  }
+};
+
+class InterpOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  InterpOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+      : OpProtoAndCheckerMaker(proto, op_checker) {
+    AddInput("X",
+             "(Tensor), 2-D Matrix of shape [batch_size, data_dim]"
+             "containing data samples, the first input of interp_op");
+    AddInput("Y",
+             "(Tensor), 2-D Matrix of shape `[batch_size, data_dim]`"
+             "containing data samples, the second input of interp_op");
+    AddInput("W",
+             "(Tensor), 1-D Vector of shape [batch_size],"
+             "the interpolated values in the half-open interval [0.0, 1.0)");
+    AddOutput("SubOut",
+              "(Tensor), the intermediate subtraction outputs, saving X - Y.")
+        .AsIntermediate();
+    AddOutput("MulOut",
+              "(Tensor), the intermediate multiplication outputs,"
+              "saving the elementwise multiplication of (X - Y) and W.")
+        .AsIntermediate();
+    AddOutput("Out",
+              "(Tensor), the output of interp_op, same shape with X,"
+              "returns the first-dimensional piecewise linear interpolant "
+              "between X and Y");
+    AddComment(R"DOC(
+    Linear Interpolation with two inputs, used in NEURAL TURING MACHINE.
+
+    Equation:
+      Out.row[i] = X.row[i] * W[i] + Y.row[i] * (1 - W[i])
+                 = (X.row[i] - Y.row[i]) * W[i] + Y.row[i]
+
+    Example:
+      X = [[1,2],[3,4]],
+      Y = [[2,1],[4,3]],
+      W = [0.3, 0.4]
+
+      Then, Out = [[1.7,1.3],[3.6,3.4]]
+
+      where 1.7 = 1*0.3+2*(1-0.3),
+            1.3 = 2*0.3+1*(1-0.3),
+            3.6 = 3*0.4+4*(1-0.4),
+            3.4 = 4*0.4+3*(1-0.4)
+)DOC");
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+REGISTER_OP_WITHOUT_GRADIENT(interp, ops::InterpOp, ops::InterpOpMaker);

python/paddle/v2/framework/tests/test_fill_constant_op.py

+import unittest
+import numpy as np
+from op_test import OpTest
+
+
+class TestFillConstantOp1(OpTest):
+    def setUp(self):
+        '''Test fill_constant op with specified value
+        '''
+        self.op_type = "fill_constant"
+
+        self.inputs = {}
+        self.attrs = {'shape': [123, 92], 'value': 3.8}
+        self.outputs = {'Out': np.full((123, 92), 3.8)}
+
+    def test_check_output(self):
+        self.check_output()
+
+
+class TestFillConstantOp2(OpTest):
+    def setUp(self):
+        '''Test fill_constant op with default value
+        '''
+        self.op_type = "fill_constant"
+
+        self.inputs = {}
+        self.attrs = {'shape': [123, 92]}
+        self.outputs = {'Out': np.full((123, 92), 0.0)}
+
+    def test_check_output(self):
+        self.check_output()
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/v2/framework/tests/test_interp_op.py

+import unittest
+import numpy as np
+from op_test import OpTest
+
+
+class TestInterpOp(OpTest):
+    def setUp(self):
+        self.op_type = "interp"
+        x = np.random.random((2, 3)).astype("float32")
+        y = np.random.random((2, 3)).astype("float32")
+        w = np.random.random(2).astype("float32")
+
+        sub_out = x - y
+        mul_out = sub_out * w.reshape(2, 1)
+        out = mul_out + y
+
+        self.inputs = {'X': x, 'Y': y, 'W': w}
+        self.outputs = {'Out': out, 'SubOut': sub_out, 'MulOut': mul_out}
+
+    def test_check_output(self):
+        self.check_output()
+
+    def test_check_grad_normal(self):
+        self.check_grad(['X', 'Y'], 'Out')
+
+
+if __name__ == "__main__":
+    unittest.main()