Rename seq to sequence in sequence_expand_op

paddle/operators/seq_expand_op.cc → paddle/operators/sequence_expand_op.cc

@@ -12,14 +12,14 @@
    See the License for the specific language governing permissions and
    limitations under the License. */
 
-#include "paddle/operators/seq_expand_op.h"
+#include "paddle/operators/sequence_expand_op.h"
 
 namespace paddle {
 namespace operators {
 
 using framework::Tensor;
 
-class SeqExpandOp : public framework::OperatorWithKernel {
+class SequenceExpandOp : public framework::OperatorWithKernel {
  public:
   using framework::OperatorWithKernel::OperatorWithKernel;
 
@@ -35,25 +35,25 @@ class SeqExpandOp : public framework::OperatorWithKernel {
   }
 };
 
-class SeqExpandOpMaker : public framework::OpProtoAndCheckerMaker {
+class SequenceExpandOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SeqExpandOpMaker(framework::OpProto* proto,
-                   framework::OpAttrChecker* op_checker)
+  SequenceExpandOpMaker(framework::OpProto* proto,
+                        framework::OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(Tensor or LoDTensor) The input(X) of this operator can be a "
              "LoDTensor or a base Tensor.");
     AddInput("Y",
-             "(LoDTensor)The reference input(Y) of seq_expand op."
+             "(LoDTensor)The reference input(Y) of sequence_expand op."
              "It must be a LoDTensor with k-level(k>0)."
              "The input(X) will be expanded according to LOD of input(Y)."
              "The element numbers of last level in input(Y) "
              "must be equal to dims[0] of input(X).");
     AddOutput("Out",
-              "(LodTensor)The output of seq_expand op."
+              "(LodTensor)The output of sequence_expand op."
               "The lod of output will be as same as input(Y)'s lod.");
     AddComment(R"DOC(
-Seq Expand Operator.
+Sequence Expand Operator.
 
 This operator expands input(X) according to LOD of input(Y).
 Following are cases to better explain how this works:
@@ -124,7 +124,7 @@ then we get 2-level LoDTensor
   }
 };
 
-class SeqExpandOpGrad : public framework::OperatorWithKernel {
+class SequenceExpandOpGrad : public framework::OperatorWithKernel {
  public:
   using framework::OperatorWithKernel::OperatorWithKernel;
 
@@ -146,11 +146,11 @@ class SeqExpandOpGrad : public framework::OperatorWithKernel {
 }  // namespace paddle
 
 namespace ops = paddle::operators;
-REGISTER_OP(seq_expand, ops::SeqExpandOp, ops::SeqExpandOpMaker,
-            seq_expand_grad, ops::SeqExpandOpGrad);
+REGISTER_OP(sequence_expand, ops::SequenceExpandOp, ops::SequenceExpandOpMaker,
+            sequence_expand_grad, ops::SequenceExpandOpGrad);
 REGISTER_OP_CPU_KERNEL(
-    seq_expand,
-    ops::SeqExpandKernel<paddle::platform::CPUDeviceContext, float>);
+    sequence_expand,
+    ops::SequenceExpandKernel<paddle::platform::CPUDeviceContext, float>);
 REGISTER_OP_CPU_KERNEL(
-    seq_expand_grad,
-    ops::SeqExpandGradKernel<paddle::platform::CPUDeviceContext, float>);
+    sequence_expand_grad,
+    ops::SequenceExpandGradKernel<paddle::platform::CPUDeviceContext, float>);

paddle/operators/seq_expand_op.cu → paddle/operators/sequence_expand_op.cu

@@ -13,12 +13,12 @@
    limitations under the License. */
 
 #define EIGEN_USE_GPU
-#include "paddle/operators/seq_expand_op.h"
+#include "paddle/operators/sequence_expand_op.h"
 
 namespace ops = paddle::operators;
 REGISTER_OP_CUDA_KERNEL(
-    seq_expand,
-    ops::SeqExpandKernel<paddle::platform::CUDADeviceContext, float>);
+    sequence_expand,
+    ops::SequenceExpandKernel<paddle::platform::CUDADeviceContext, float>);
 REGISTER_OP_CUDA_KERNEL(
-    seq_expand_grad,
-    ops::SeqExpandGradKernel<paddle::platform::CUDADeviceContext, float>);
+    sequence_expand_grad,
+    ops::SequenceExpandGradKernel<paddle::platform::CUDADeviceContext, float>);

paddle/operators/seq_expand_op.h → paddle/operators/sequence_expand_op.h

@@ -24,7 +24,7 @@ namespace operators {
 using LoDTensor = framework::LoDTensor;
 
 template <typename DeviceContext, typename T>
-class SeqExpandKernel : public framework::OpKernel<T> {
+class SequenceExpandKernel : public framework::OpKernel<T> {
  public:
   void Compute(const framework::ExecutionContext& context) const override {
     auto* x = context.Input<LoDTensor>("X");
@@ -71,7 +71,7 @@ class SeqExpandKernel : public framework::OpKernel<T> {
  *
  * */
 template <typename DeviceContext, typename T>
-class SeqExpandGradKernel : public framework::OpKernel<T> {
+class SequenceExpandGradKernel : public framework::OpKernel<T> {
  public:
   void Compute(const framework::ExecutionContext& context) const override {
     auto* d_out = context.Input<LoDTensor>(framework::GradVarName("Out"));

python/paddle/v2/fluid/tests/test_seq_expand.py → python/paddle/v2/fluid/tests/test_sequence_expand.py

@@ -3,7 +3,7 @@
 from op_test import OpTest
 
 
-class TestSeqExpand(OpTest):
+class TestSequenceExpand(OpTest):
     def set_data(self):
         x_data = np.random.uniform(0.1, 1, [3, 1]).astype('float32')
         y_data = np.random.uniform(0.1, 1, [8, 1]).astype('float32')
@@ -21,7 +21,7 @@ def compute(self):
         self.outputs = {'Out': out}
 
     def setUp(self):
-        self.op_type = 'seq_expand'
+        self.op_type = 'sequence_expand'
         self.set_data()
         self.compute()
 
@@ -32,7 +32,7 @@ def test_check_grad(self):
         self.check_grad(["X"], "Out")
 
 
-class TestSeqExpandCase1(TestSeqExpand):
+class TestSequenceExpandCase1(TestSequenceExpand):
     def set_data(self):
         x_data = np.random.uniform(0.1, 1, [5, 1]).astype('float32')
         x_lod = [[0, 2, 5]]
@@ -41,7 +41,7 @@ def set_data(self):
         self.inputs = {'X': (x_data, x_lod), 'Y': (y_data, y_lod)}
 
 
-class TestSeqExpandCase2(TestSeqExpand):
+class TestSequenceExpandCase2(TestSequenceExpand):
     def set_data(self):
         x_data = np.random.uniform(0.1, 1, [1, 2, 2]).astype('float32')
         x_lod = [[0, 1]]
@@ -50,7 +50,7 @@ def set_data(self):
         self.inputs = {'X': (x_data, x_lod), 'Y': (y_data, y_lod)}
 
 
-class TestSeqExpandCase3(TestSeqExpand):
+class TestSequenceExpandCase3(TestSequenceExpand):
     def set_data(self):
         x_data = np.random.uniform(0.1, 1, [4, 1]).astype('float32')
         x_lod = [[0, 1, 2, 3, 4]]