diff --git a/paddle/fluid/operators/reshape_op.cc b/paddle/fluid/operators/reshape_op.cc
index d72f85f2c4..b8fdc3f826 100644
--- a/paddle/fluid/operators/reshape_op.cc
+++ b/paddle/fluid/operators/reshape_op.cc
@@ -164,7 +164,7 @@ dimension value will be copied from Input(X) at runtime. Note that the index of
[2, 3, 4], Attr(shape) = [2, 3, 2, 0] is an invalid input.
3. Input(Shape) has a higher priority than Attr(shape) if it is provided, while
-Attr(shape) still should be set correctly to gurantee shape inference in
+Attr(shape) still should be set correctly to gurantee shape inference in
compile-time.
)DOC");
@@ -195,6 +195,7 @@ class ReshapeGradOp : public framework::OperatorWithKernel {
}
};
+template <typename T>
class ReshapeKernel {
public:
void operator()(const framework::ExecutionContext &ctx) const {
@@ -227,12 +228,15 @@ class ReshapeKernel {
"sequence_reshape op.");
}
- out->mutable_data(ctx.GetPlace(), in->type());
- framework::TensorCopySync(*in, ctx.GetPlace(), out);
+ if (in->data<T>() !=
+ reinterpret_cast<T *>(out->mutable_data(ctx.GetPlace(), in->type()))) {
+ framework::TensorCopySync(*in, ctx.GetPlace(), out);
+ }
out->Resize(out_dims);
}
};
+template <typename T>
class ReshapeGradKernel {
public:
void operator()(const framework::ExecutionContext &ctx) const {
@@ -240,8 +244,9 @@ class ReshapeGradKernel {
auto *d_x = ctx.Output<framework::Tensor>(framework::GradVarName("X"));
auto in_dims = d_x->dims();
- d_x->mutable_data(ctx.GetPlace(), d_out->type());
- framework::TensorCopySync(*d_out, ctx.GetPlace(), d_x);
+ if (d_out->data<T>() != d_x->mutable_data(ctx.GetPlace(), d_out->type())) {
+ framework::TensorCopySync(*d_out, ctx.GetPlace(), d_x);
+ }
d_x->Resize(in_dims);
}
};
@@ -259,7 +264,6 @@ class Reshape2Op : public ReshapeOp {
: ReshapeOp(type, inputs, outputs, attrs) {}
void InferShape(framework::InferShapeContext *ctx) const override {
- ReshapeOp::InferShape(ctx);
PADDLE_ENFORCE(ctx->HasOutput("XShape"),
"Output(XShape) of ReshapeOp should not be null.");
const auto &x_dims = ctx->GetInputDim("X");
@@ -270,6 +274,8 @@ class Reshape2Op : public ReshapeOp {
}
ctx->SetOutputDim("XShape", framework::make_ddim(xshape_dims));
ctx->ShareLoD("X", /*->*/ "XShape");
+
+ ReshapeOp::InferShape(ctx);
}
};
@@ -335,38 +341,46 @@ namespace ops = paddle::operators;
REGISTER_OPERATOR(reshape, ops::ReshapeOp, ops::ReshapeOpMaker,
paddle::framework::DefaultGradOpDescMaker<true>);
REGISTER_OPERATOR(reshape_grad, ops::ReshapeGradOp);
-REGISTER_OP_CPU_KERNEL_FUNCTOR(reshape, float, ops::ReshapeKernel, double,
- ops::ReshapeKernel, int, ops::ReshapeKernel,
- int64_t, ops::ReshapeKernel);
-REGISTER_OP_CPU_KERNEL_FUNCTOR(reshape_grad, float, ops::ReshapeGradKernel,
- double, ops::ReshapeGradKernel, int,
- ops::ReshapeGradKernel, int64_t,
- ops::ReshapeGradKernel);
+REGISTER_OP_CPU_KERNEL_FUNCTOR(reshape, float, ops::ReshapeKernel<float>,
+ double, ops::ReshapeKernel<double>, int,
+ ops::ReshapeKernel<int>, int64_t,
+ ops::ReshapeKernel<int64_t>);
+REGISTER_OP_CPU_KERNEL_FUNCTOR(reshape_grad, float,
+ ops::ReshapeGradKernel<float>, double,
+ ops::ReshapeGradKernel<double>, int,
+ ops::ReshapeGradKernel<int>, int64_t,
+ ops::ReshapeGradKernel<int64_t>);
REGISTER_OPERATOR(reshape2, ops::Reshape2Op, ops::Reshape2OpMaker,
ops::Reshape2GradMaker);
REGISTER_OPERATOR(reshape2_grad, ops::Reshape2GradOp);
-REGISTER_OP_CPU_KERNEL_FUNCTOR(reshape2, float, ops::ReshapeKernel, double,
- ops::ReshapeKernel, int, ops::ReshapeKernel,
- int64_t, ops::ReshapeKernel);
-REGISTER_OP_CPU_KERNEL_FUNCTOR(reshape2_grad, float, ops::ReshapeGradKernel,
- double, ops::ReshapeGradKernel, int,
- ops::ReshapeGradKernel, int64_t,
- ops::ReshapeGradKernel);
+REGISTER_OP_CPU_KERNEL_FUNCTOR(reshape2, float, ops::ReshapeKernel<float>,
+ double, ops::ReshapeKernel<double>, int,
+ ops::ReshapeKernel<int>, int64_t,
+ ops::ReshapeKernel<int64_t>);
+REGISTER_OP_CPU_KERNEL_FUNCTOR(reshape2_grad, float,
+ ops::ReshapeGradKernel<float>, double,
+ ops::ReshapeGradKernel<double>, int,
+ ops::ReshapeGradKernel<int>, int64_t,
+ ops::ReshapeGradKernel<int64_t>);
#ifdef PADDLE_WITH_CUDA
-REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape, float, ops::ReshapeKernel, double,
- ops::ReshapeKernel, int, ops::ReshapeKernel,
- int64_t, ops::ReshapeKernel);
-REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape_grad, float, ops::ReshapeGradKernel,
- double, ops::ReshapeGradKernel, int,
- ops::ReshapeGradKernel, int64_t,
- ops::ReshapeGradKernel);
-REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape2, float, ops::ReshapeKernel, double,
- ops::ReshapeKernel, int, ops::ReshapeKernel,
- int64_t, ops::ReshapeKernel);
-REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape2_grad, float, ops::ReshapeGradKernel,
- double, ops::ReshapeGradKernel, int,
- ops::ReshapeGradKernel, int64_t,
- ops::ReshapeGradKernel);
+REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape, float, ops::ReshapeKernel<float>,
+ double, ops::ReshapeKernel<double>, int,
+ ops::ReshapeKernel<int>, int64_t,
+ ops::ReshapeKernel<int64_t>);
+REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape_grad, float,
+ ops::ReshapeGradKernel<float>, double,
+ ops::ReshapeGradKernel<double>, int,
+ ops::ReshapeGradKernel<int>, int64_t,
+ ops::ReshapeGradKernel<int64_t>);
+REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape2, float, ops::ReshapeKernel<float>,
+ double, ops::ReshapeKernel<double>, int,
+ ops::ReshapeKernel<int>, int64_t,
+ ops::ReshapeKernel<int64_t>);
+REGISTER_OP_CUDA_KERNEL_FUNCTOR(reshape2_grad, float,
+ ops::ReshapeGradKernel<float>, double,
+ ops::ReshapeGradKernel<double>, int,
+ ops::ReshapeGradKernel<int>, int64_t,
+ ops::ReshapeGradKernel<int64_t>);
#endif
diff --git a/paddle/fluid/operators/sequence_concat_op.cc b/paddle/fluid/operators/sequence_concat_op.cc
index 397a318295..12b53be708 100644
--- a/paddle/fluid/operators/sequence_concat_op.cc
+++ b/paddle/fluid/operators/sequence_concat_op.cc
@@ -90,11 +90,12 @@ REGISTER_OPERATOR(sequence_concat, paddle::framework::OperatorWithKernel,
paddle::framework::DefaultGradOpDescMaker<false>);
template <typename T>
using Kernel = op::SeqConcatKernel<paddle::platform::CPUDeviceContext, T>;
-REGISTER_OP_CPU_KERNEL(sequence_concat, Kernel<float>, Kernel<double>);
+REGISTER_OP_CPU_KERNEL(sequence_concat, Kernel<float>, Kernel<double>,
+ Kernel<int64_t>);
REGISTER_OPERATOR(sequence_concat_grad, paddle::framework::OperatorWithKernel,
op::SeqConcatGradShapeInferer);
template <typename T>
using GradKernel =
op::SeqConcatGradKernel<paddle::platform::CPUDeviceContext, T>;
REGISTER_OP_CPU_KERNEL(sequence_concat_grad, GradKernel<float>,
- GradKernel<double>);
+ GradKernel<double>, GradKernel<int64_t>);