Add seq_expand op

1. Add unitest
2. Add SeqExpandOpKernel

paddle/operators/seq_expand_op.cc

@@ -0,0 +1,125 @@
+/* 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/seq_expand_op.h"
+
+namespace paddle {
+namespace operators {
+
+using framework::Tensor;
+
+class SeqExpandOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+ protected:
+  void InferShape(framework::InferShapeContext* ctx) const override {
+    PADDLE_ENFORCE(ctx->HasInput("X"),
+                   "Input(X) of SeqExpandOp should not be null.");
+    int repeat = ctx->Attrs().Get<int>("repeat");
+    DDim out_dim;
+    if (repeat == 0) {
+      PADDLE_ENFORCE(
+          ctx->HasInput("Y"),
+          "Input(Y) of SeqExpandOp should not be null while repeat == 0.");
+      out_dim = ctx->GetInputDim("Y");
+      ctx->ShareLoD("Y", "Out");
+    } else {
+      out_dim = ctx->GetInputDim("X");
+      out_dim[0] = out_dim[0] * repeat;
+      ctx->SetOutputDim("Out", y_dim);
+    }
+    PADDLE_ENFORCE(ctx->HasOutput("Out"),
+                   "Output(Out) of PadOp should not be null.");
+    ctx->SetOutputDim("Out", out_dim);
+  }
+};
+
+class SeqExpandOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  SeqExpandOpMaker(framework::OpProto* proto,
+                   framework::OpAttrChecker* op_checker)
+      : OpProtoAndCheckerMaker(proto, op_checker) {
+    // TODO(wanghaoshuang): Add more comments
+    AddInput("X", "The input('X') of seq_expand op.");
+    AddInput("Y", "The reference input('Y') of seq_expand op.");
+    AddOutput("Out", "The output of seq_expand op.");
+    AddAttr<int>("repeat", "repeat times").SetDefault(0);
+    AddComment(R"DOC(
+As an example:
+
+Given:
+
+X = [1, 2 , 3]
+
+and
+
+repeat = 2
+
+
+then we get
+
+Out.data = [1, 1, 2, 2, 3, 3]
+Out.lod = [[0, 2, 4, 6]]
+
+)DOC");
+  }
+};
+
+class SeqExpandOpGrad : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+ protected:
+  void InferShape(framework::InferShapeContext* ctx) const override {
+    PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
+    PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
+                   "Input(Out@GRAD) should not be null");
+    auto x_dims = ctx->GetInputDim("X");
+    auto x_grad_name = framework::GradVarName("X");
+    if (ctx->HasOutput(x_grad_name)) {
+      ctx->SetOutputDim(x_grad_name, x_dims);
+    }
+  }
+};
+
+class SeqExpandOpGradMaker : public framework::SingleGradOpDescMaker {
+ public:
+  using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
+
+ protected:
+  std::unique_ptr<framework::OpDescBind> Apply() const override {
+    auto* bind = new framework::OpDescBind();
+    bind->SetInput("X", Input("X"));
+    bind->SetInput(framework::GradVarName("Out"), OutputGrad("Out"));
+    bind->SetOutput(framework::GradVarName("X"), InputGrad("X"));
+    bind->SetAttrMap(Attrs());
+    bind->SetType("seq_expand_grad");
+    return std::unique_ptr<framework::OpDescBind>(bind);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+
+REGISTER_OPERATOR(seq_expand, ops::SeqExpandOp, ops::SeqExpandOpMaker,
+                  ops::SeqExpandOpGradMaker);
+REGISTER_OPERATOR(seq_expand_grad, ops::SeqExpandOpGrad);
+REGISTER_OP_CPU_KERNEL(seq_expand,
+                       ops::SeqExpandKernel<paddle::platform::CPUPlace, float>);
+REGISTER_OP_CPU_KERNEL(
+    seq_expand_grad,
+    ops::SeqExpandGradKernel<paddle::platform::CPUPlace, float>);

paddle/operators/seq_expand_op.cu

@@ -0,0 +1,23 @@
+/* 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/operators/seq_expand_op.h"
+
+namespace ops = paddle::operators;
+REGISTER_OP_GPU_KERNEL(seq_expand,
+                       ops::SeqExpandKernel<paddle::platform::GPUPlace, float>);
+REGISTER_OP_GPU_KERNEL(
+    seq_expand_grad,
+    ops::SeqExpandGradKernel<paddle::platform::GPUPlace, float>);

paddle/operators/seq_expand_op.h

@@ -0,0 +1,83 @@
+/* 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 "hl_cuda.h"
+#include "paddle/framework/op_registry.h"
+
+namespace paddle {
+namespace operators {
+
+using LoDTensor = framework::LoDTensor;
+using LoD = paddle::framework::LoD;
+
+template <typename Place, typename T>
+class SeqExpandKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& context) const override {
+    auto* x = context.Input<LoDTensor>("X");
+    auto* out = context.Output<LoDTensor>("Out");
+    const T* x_data = x->data<T>();
+    T* out_data = out->mutable_data<T>(context.GetPlace());
+    size_t repeat = static_cast<size_t>(context.Attr<int>("repeat"));
+
+    if (repeat != 0) {
+      if (x->lod().size() == 0) {
+        std::vector<size_t> level0(x->dims()[0]);
+        for (size_t i = 0; i <= x->dims()[0]; i++) {
+          level0.push_back(i * repeat);
+        }
+        const LoD out_lod;
+        out_lod.push_back(level0);
+        out->set_lod(out_lod);
+      }
+    }
+    auto out_dim = out->dims();
+    size_t element_len = framework::product(out_dim) / out_dim[0];
+    std::vector<int> cpy_map(out_dim[0]);
+    if (x->lod().size() == 0) {
+      auto lod = out->lod();
+      for (int i = 0; i < lod.size() - 1; ++i) {
+        for (int j = lod[0][i]; i < lod[0][i + 1]; ++j) {
+          cpy_map[j] = i;
+        }
+      }
+    }
+    if (paddle::platform::CPUPlace() == Place) {
+      for (int i = 0; i < out_dim[0]; ++i) {
+        memcpy(out_data + element_len * i, x_data + element_len * cpy_map[i],
+               sizeof(T) * element_len);
+      }
+    } else {
+      for (int i = 0; i < out_dim[0]; ++i) {
+        hl_memcpy(out_data + element_len * i, x_data + element_len * cpy_map[i],
+                  sizeof(T) * element_len);
+      }
+    }
+  }
+};
+
+template <typename Place, typename T>
+class SeqExpandGradKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& context) const override {
+    // auto* d_out = context.Input<Tensor>(framework::GradVarName("Out"));
+    // auto* d_x = context.Output<Tensor>(framework::GradVarName("X"));
+    // d_x->mutable_data<T>(context.GetPlace());
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

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

@@ -0,0 +1,61 @@
+import unittest
+import numpy as np
+from op_test import OpTest
+
+
+class TestSeqExpand(OpTest):
+    #class TestSeqExpand():
+    def set_data(self):
+        self.op_type = 'seq_expand'
+        x = np.random.uniform(0.1, 1, [3, 2, 2]).astype('float32')
+        y = np.zeros((6, 2, 2)).astype('float32')
+        lod = [[0, 2, 3, 6]]
+        print "x = %s" % x
+        self.inputs = {'X': x, 'Y': (y, lod)}
+        self.repeat = None
+
+    def compute(self):
+        x = self.inputs['X']
+        cpy_map = {}
+        lod = []
+        out_shape = []
+        if self.repeat:
+            level0 = []
+            for i in range(x.shape[0] + 1):
+                level0.append(i * self.repeat)
+            lod.append(level0)
+
+            for i in x.shape:
+                out_shape.append(i)
+            out_shape[0] = out_shape[0] * self.repeat
+        else:
+            y, lod = self.inputs['Y']
+            out_shape = y.shape
+        out = np.zeros(out_shape).astype('float32')
+
+        start = 0
+
+        for i in range(len(lod[0]) - 1):
+            for j in range(lod[0][i], lod[0][i + 1]):
+                cpy_map[j] = i
+        print "cpy_map = %s" % cpy_map
+        for i in range(len(out)):
+            out[i] = x[cpy_map[i]]
+
+        print "out = %s" % out
+        self.outputs = {'Out': (out, lod)}
+
+    def setUp(self):
+        self.set_data()
+        self.compute()
+
+    def test_check_output(self):
+        self.check_output()
+
+    def test_check_grad(self):
+        self.check_grad(["X"], "Out")
+
+
+if __name__ == '__main__':
+    unittest.main()
+#    TestSeqExpand().setUp()