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@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
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limitations under the License. */
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limitations under the License. */
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#include "paddle/fluid/operators/transpose_op.h"
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#include "paddle/fluid/operators/transpose_op.h"
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#include <string>
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#include <vector>
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#include <vector>
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namespace paddle {
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namespace paddle {
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@ -24,7 +25,7 @@ class TransposeOp : public framework::OperatorWithKernel {
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public:
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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void InferShape(framework::InferShapeContext *ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
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PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
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PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should not be null");
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PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should not be null");
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auto x_dims = ctx->GetInputDim("X");
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auto x_dims = ctx->GetInputDim("X");
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@ -101,7 +102,7 @@ class TransposeOpGrad : public framework::OperatorWithKernel {
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public:
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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void InferShape(framework::InferShapeContext *ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
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PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
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PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
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PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
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"Input(Out@GRAD) should not be null");
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"Input(Out@GRAD) should not be null");
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@ -113,6 +114,93 @@ class TransposeOpGrad : public framework::OperatorWithKernel {
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}
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}
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};
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};
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// FIXME(zcd): transpose2 adds an intermediate output(XShape) based on
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// transpose, the XShape is used to carry the shape and lod of X which
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// will be used in transpose_grad, in this way, the framework can reuse
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// the memory of X immediately the transpose2_op is finished.
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// Considering compatibility issues, we could not fix transpose2_op
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class Transpose2Op : public TransposeOp {
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public:
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Transpose2Op(const std::string &type,
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const framework::VariableNameMap &inputs,
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const framework::VariableNameMap &outputs,
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const framework::AttributeMap &attrs)
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: TransposeOp(type, inputs, outputs, attrs) {}
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void InferShape(framework::InferShapeContext *ctx) const override {
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TransposeOp::InferShape(ctx);
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PADDLE_ENFORCE(ctx->HasOutput("XShape"),
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"Output(XShape) should not be null");
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const auto &in_dims = ctx->GetInputDim("X");
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std::vector<int64_t> x_shape_dim(in_dims.size() + 1);
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x_shape_dim[0] = 0;
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for (int i = 0; i < in_dims.size(); ++i) {
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x_shape_dim[i + 1] = in_dims[i];
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}
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ctx->SetOutputDim("XShape", framework::make_ddim(x_shape_dim));
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ctx->ShareLoD("X", /*->*/ "XShape");
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}
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protected:
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framework::OpKernelType GetExpectedKernelType(
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const framework::ExecutionContext &ctx) const override {
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return framework::OpKernelType(
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framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
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ctx.device_context());
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}
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};
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class Transpose2OpMaker : public TransposeOpMaker {
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public:
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void Make() override {
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TransposeOpMaker::Make();
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AddOutput("XShape", "(Tensor)The output tensor.").AsIntermediate();
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}
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};
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class Transpose2GradMaker : public framework::SingleGradOpDescMaker {
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public:
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using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
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std::unique_ptr<framework::OpDesc> Apply() const override {
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auto *grad_op = new framework::OpDesc();
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grad_op->SetType("transpose2_grad");
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grad_op->SetInput("XShape", Output("XShape"));
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grad_op->SetInput(framework::GradVarName("Out"), OutputGrad("Out"));
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grad_op->SetOutput(framework::GradVarName("X"), InputGrad("X"));
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grad_op->SetAttrMap(Attrs());
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return std::unique_ptr<framework::OpDesc>(grad_op);
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}
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};
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class Transpose2OpGrad : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext *ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("XShape"), "Input(XShape) should not be null");
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PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")),
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"Input(Out@GRAD) should not be null");
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if (ctx->HasOutput(framework::GradVarName("X"))) {
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auto xshape_dim = ctx->GetInputDim("XShape");
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auto x_shape_dim =
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framework::slice_ddim(xshape_dim, 1, xshape_dim.size());
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ctx->SetOutputDim(framework::GradVarName("X"), x_shape_dim);
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ctx->ShareLoD("XShape", framework::GradVarName("X"));
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}
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}
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protected:
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framework::OpKernelType GetExpectedKernelType(
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const framework::ExecutionContext &ctx) const override {
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return framework::OpKernelType(
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framework::ToDataType(
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ctx.Input<framework::LoDTensor>(framework::GradVarName("Out"))
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->type()),
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ctx.device_context());
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}
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};
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} // namespace operators
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} // namespace operators
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} // namespace paddle
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} // namespace paddle
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@ -120,8 +208,20 @@ namespace ops = paddle::operators;
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REGISTER_OPERATOR(transpose, ops::TransposeOp, ops::TransposeOpMaker,
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REGISTER_OPERATOR(transpose, ops::TransposeOp, ops::TransposeOpMaker,
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paddle::framework::DefaultGradOpDescMaker<true>);
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paddle::framework::DefaultGradOpDescMaker<true>);
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REGISTER_OPERATOR(transpose_grad, ops::TransposeOpGrad);
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REGISTER_OPERATOR(transpose_grad, ops::TransposeOpGrad);
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REGISTER_OP_CPU_KERNEL(
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REGISTER_OP_CPU_KERNEL(
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transpose, ops::TransposeKernel<paddle::platform::CPUDeviceContext, float>);
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transpose, ops::TransposeKernel<paddle::platform::CPUDeviceContext, float>);
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REGISTER_OP_CPU_KERNEL(
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REGISTER_OP_CPU_KERNEL(
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transpose_grad,
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transpose_grad,
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ops::TransposeGradKernel<paddle::platform::CPUDeviceContext, float>);
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ops::TransposeGradKernel<paddle::platform::CPUDeviceContext, float>);
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REGISTER_OPERATOR(transpose2, ops::Transpose2Op, ops::Transpose2OpMaker,
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ops::Transpose2GradMaker);
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REGISTER_OPERATOR(transpose2_grad, ops::Transpose2OpGrad);
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REGISTER_OP_CPU_KERNEL(
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transpose2,
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ops::TransposeKernel<paddle::platform::CPUDeviceContext, float>);
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REGISTER_OP_CPU_KERNEL(
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transpose2_grad,
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ops::TransposeGradKernel<paddle::platform::CPUDeviceContext, float>);
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luotao1
7 years ago