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supplement the function of slice. #34172

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merged 12 commits into from
Aug 4, 2021
Merged

supplement the function of slice. #34172

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f41ce1c
supplement the function of slice
hbwx24 Jul 19, 2021
3967d6b
edit unittest
hbwx24 Jul 19, 2021
661eb52
deal with conflict
hbwx24 Jul 20, 2021
0a476ea
strided_slice_op support .
hbwx24 Jul 26, 2021
ae19cc0
Merge remote-tracking branch 'upstream/develop' into slice/static_get…
hbwx24 Jul 26, 2021
0d14ffc
polish error message.
hbwx24 Jul 26, 2021
6e3c267
polish error message.
hbwx24 Jul 26, 2021
9812033
polish code.
hbwx24 Jul 26, 2021
8b94458
polish unittest.
hbwx24 Jul 26, 2021
39aa575
polish code.
hbwx24 Jul 27, 2021
3b6ad37
polish code
hbwx24 Jul 29, 2021
775b464
polish error message.
hbwx24 Jul 30, 2021
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61 changes: 58 additions & 3 deletions paddle/fluid/operators/strided_slice_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,13 @@ class StridedSliceOp : public framework::OperatorWithKernel {
void InferShape(framework::InferShapeContext *ctx) const override {
OP_INOUT_CHECK(ctx->HasInput("Input"), "Input", "Input", "StridedSlice");
OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "StridedSlice");

auto input_var_type = ctx->GetInputsVarType("Input")[0];
if (input_var_type == framework::proto::VarType::LOD_TENSOR_ARRAY) {
if (ctx->IsRuntime()) {
// shape is determined by Runtime.
return;
}
}
auto in_dims = ctx->GetInputDim("Input");
PADDLE_ENFORCE_LT(
in_dims.size(), 7,
Expand Down Expand Up @@ -154,6 +160,27 @@ class StridedSliceOp : public framework::OperatorWithKernel {
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext &ctx) const override {
auto *in_var = ctx.InputVar("Input");
auto is_in_var_array = in_var->IsType<framework::LoDTensorArray>();
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结合下面的code，会不会有这种情况，lodtensorarray里面tensor的place是cuda_pinned

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@hbwx24 hbwx24 Jul 29, 2021 •
edited
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Done, thx.

if (is_in_var_array) {
auto &tensor_array = in_var->Get<framework::LoDTensorArray>();
for (auto &tensor : tensor_array) {
if (!platform::is_cuda_pinned_place(tensor.place())) {
PADDLE_ENFORCE_EQ(
platform::is_same_place(tensor.place(),
ctx.device_context().GetPlace()),
true,
platform::errors::InvalidArgument(
"Place of context is %s. Place of input tensor is %s. They "
"are should be same, but reveived different place.",
string::to_string(ctx.device_context().GetPlace()),
string::to_string(tensor.place())));
}
}
return framework::OpKernelType(
OperatorWithKernel::IndicateVarDataType(ctx, "Input"),
ctx.device_context());
}
// NOTE: cuda pinned tensor need to copy its data to target place
auto in_tensor = ctx.Input<Tensor>("Input");
if (platform::is_cuda_pinned_place(in_tensor->place())) {
Expand All @@ -179,6 +206,14 @@ class StridedSliceOp : public framework::OperatorWithKernel {
}
};

class StridedSliceOpVarTypeInference : public framework::VarTypeInference {
public:
void operator()(framework::InferVarTypeContext *ctx) const override {
ctx->SetOutputType("Out", ctx->GetInputType("Input"));
ctx->SetOutputDataType("Out", ctx->GetInputDataType("Input"));
}
};

class StridedSliceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() override {
Expand Down Expand Up @@ -259,6 +294,13 @@ class StridedSliceOpGrad : public framework::OperatorWithKernel {
OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input",
"Out@GRAD", "StridedSliceGrad");

auto input_var_type = ctx->GetInputsVarType("Input")[0];
if (input_var_type == framework::proto::VarType::LOD_TENSOR_ARRAY) {
if (ctx->IsRuntime()) {
// shape is determined by Runtime
return;
}
}
auto x_dims = ctx->GetInputDim("Input");
auto x_grad_name = framework::GradVarName("Input");
if (ctx->HasOutput(x_grad_name)) {
Expand Down Expand Up @@ -308,6 +350,16 @@ class StridedSliceOpGradMaker : public framework::SingleGradOpMaker<T> {
bind->SetType("strided_slice_grad");
}
};
class StridedSliceGradOpVarTypeInference : public framework::VarTypeInference {
public:
void operator()(framework::InferVarTypeContext *ctx) const override {
ctx->SetOutputType(framework::GradVarName("Input"),
ctx->GetInputType(framework::GradVarName("Out")));
ctx->SetOutputDataType(
framework::GradVarName("Input"),
ctx->GetInputDataType(framework::GradVarName("Out")));
}
};

DECLARE_NO_NEED_BUFFER_VARS_INFERER(StridedSliceOpGradNoNeedBufferVarsInferer,
"Input");
Expand All @@ -318,9 +370,12 @@ DECLARE_NO_NEED_BUFFER_VARS_INFERER(StridedSliceOpGradNoNeedBufferVarsInferer,
namespace ops = paddle::operators;
REGISTER_OPERATOR(strided_slice, ops::StridedSliceOp, ops::StridedSliceOpMaker,
ops::StridedSliceOpGradMaker<paddle::framework::OpDesc>,
ops::StridedSliceOpGradMaker<paddle::imperative::OpBase>);
ops::StridedSliceOpGradMaker<paddle::imperative::OpBase>,
ops::StridedSliceOpVarTypeInference);

REGISTER_OPERATOR(strided_slice_grad, ops::StridedSliceOpGrad,
ops::StridedSliceOpGradNoNeedBufferVarsInferer);
ops::StridedSliceOpGradNoNeedBufferVarsInferer,
ops::StridedSliceGradOpVarTypeInference);

REGISTER_OP_CPU_KERNEL(
strided_slice,
Expand Down
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