未验证 提交 e579dc1c 编写于 作者: W whs 提交者: GitHub

Merge pull request #6708 from wanghaoshuang/rename_seq

Rename seq to sequence in sequence_expand_op
......@@ -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>);
......@@ -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>);
......@@ -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"));
......
......@@ -3,7 +3,7 @@ import numpy as np
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 @@ class TestSeqExpand(OpTest):
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 @@ class TestSeqExpand(OpTest):
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 @@ class TestSeqExpandCase1(TestSeqExpand):
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 @@ class TestSeqExpandCase2(TestSeqExpand):
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]]
......
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