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Fix bug caused by split infershape #40116

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merged 3 commits into from
Mar 4, 2022
Merged

Fix bug caused by split infershape #40116

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d785d44
fix bug caused by split infershape
zyfncg Mar 3, 2022
3151663
revert infer_shape of split
zyfncg Mar 3, 2022
08dcb3d
revert split
zyfncg Mar 3, 2022
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52 changes: 47 additions & 5 deletions paddle/fluid/operators/split_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,52 @@ class SplitOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;

void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE_EQ(ctx->HasInput("X"), true,
platform::errors::InvalidArgument(
"Input(X) of SplitOp should not be null."));
PADDLE_ENFORCE_GE(ctx->Outputs("Out").size(), 1UL,
platform::errors::InvalidArgument(
"Outputs(Out) of SplitOp should not be empty."));
auto in_dims = ctx->GetInputDim("X");
auto outs_names = ctx->Outputs("Out");
size_t axis = static_cast<size_t>(ctx->Attrs().Get<int>("axis"));
size_t num = static_cast<size_t>(ctx->Attrs().Get<int>("num"));
std::vector<int> sections = static_cast<std::vector<int>>(
ctx->Attrs().Get<std::vector<int>>("sections"));
const size_t outs_number = outs_names.size();

if (sections.size() > 0) {
PADDLE_ENFORCE_EQ(
sections.size(), outs_number,
platform::errors::InvalidArgument("tensor split sections size "
"should be equal to output size."));
}

if (ctx->HasInput("AxisTensor")) {
auto out_dims = phi::make_ddim(std::vector<int>(in_dims.size(), -1));
std::vector<framework::DDim> outs_dims(outs_number, out_dims);
ctx->SetOutputsDim("Out", outs_dims);
for (size_t i = 0; i < outs_number; ++i) {
ctx->ShareLoD("X", "Out", 0, i);
}
return;
}

bool each_section_is_known =
(sections.size() > 0 && !ctx->HasInputs("SectionsTensorList"));

auto outs_dims = UpdateOutsDims(ctx->IsRuntime(), each_section_is_known,
in_dims, num, sections, axis, outs_number);
ctx->SetOutputsDim("Out", outs_dims);
if (axis != 0) {
// Only pass LoD when not spliting along the first dim.
for (size_t i = 0; i < outs_number; ++i) {
ctx->ShareLoD("X", "Out", 0, i);
}
}
}

protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext &ctx) const override {
Expand Down Expand Up @@ -125,10 +171,6 @@ This operator splits the input tensor into multiple sub-tensors.

namespace ops = paddle::operators;

DELCARE_INFER_SHAPE_FUNCTOR(split, SplitInferShapeFunctor,
PT_INFER_META(phi::SplitInferMeta));

REGISTER_OPERATOR(split, ops::SplitOp, ops::SplitOpMaker,
ops::SplitGradMaker<paddle::framework::OpDesc>,
ops::SplitGradMaker<paddle::imperative::OpBase>,
SplitInferShapeFunctor);
ops::SplitGradMaker<paddle::imperative::OpBase>);
80 changes: 36 additions & 44 deletions paddle/phi/infermeta/unary.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -508,17 +508,6 @@ void SplitInferMeta(const MetaTensor& x,
const Scalar& axis,
std::vector<MetaTensor*> out,
MetaConfig config) {
if (!config.is_runtime) {
if (axis.FromTensor() || num_or_sections.FromTensor()) {
auto out_dims = phi::make_ddim(std::vector<int>(x.dims().size(), -1));
for (auto* item : out) {
item->set_dims(out_dims);
item->share_lod(x);
}
return;
}
}

int axis_value = axis.to<int>();
int rank = x.dims().size();
PADDLE_ENFORCE_EQ(
Expand All @@ -533,44 +522,38 @@ void SplitInferMeta(const MetaTensor& x,
axis_value = axis_value + rank;
}

std::vector<phi::DDim> out_dims(out.size(), x.dims());

auto input_axis_dim = x.dims().at(axis_value);
auto num_or_sections_data = num_or_sections.GetData();
// step1: get formated sections
std::vector<int64_t> sections;
// num_or_sections is a number
if (num_or_sections_data.size() == 1) {
if (config.is_runtime || input_axis_dim > 0) {
int num = num_or_sections_data.at(0);
PADDLE_ENFORCE_EQ(
input_axis_dim % num,
0,
phi::errors::InvalidArgument(
"The input's size along the split dimension "
"must be evenly divisible by Attr(num_or_sections). "
"But received Attr(num_or_sections) "
"= %d, input(X)'s shape = [%s], Attr(dim) = %d.",
num,
x.dims(),
axis_value));
int num = num_or_sections_data.at(0);

size_t out_axis_dim = input_axis_dim / num;
for (auto& out_dim : out_dims) {
out_dim[axis_value] = out_axis_dim;
}
} else {
for (auto& out_dim : out_dims) {
out_dim[axis_value] = -1;
}
PADDLE_ENFORCE_EQ(input_axis_dim % num,
0,
phi::errors::InvalidArgument(
"The input's size along the split dimension "
"must be evenly divisible by Attr(num_or_sections). "
"But received Attr(num_or_sections) "
"= %d, input(X)'s shape = [%s], Attr(dim) = %d.",
num,
x.dims(),
axis_value));

for (int i = 0; i < num; ++i) {
sections.push_back(input_axis_dim / num);
}
} else {
// num_or_sections is a sections
const int unknow_dim_val = -1;
int unknow_dim_idx = -1;
int num_of_unknow = 0;
int sum_of_section = 0;
std::vector<int64_t> sections = num_or_sections_data;

for (size_t i = 0; i < num_or_sections_data.size(); ++i) {
sections.push_back(num_or_sections_data[i]);

if (num_or_sections_data[i] == unknow_dim_val) {
num_of_unknow++;
unknow_dim_idx = i;
Expand Down Expand Up @@ -622,22 +605,31 @@ void SplitInferMeta(const MetaTensor& x,
x.dims(),
axis_value));
}
for (size_t i = 0; i < out_dims.size(); ++i) {
}

// setp2: fill out dims
std::vector<phi::DDim> out_dims(sections.size(), x.dims());
if (config.is_runtime || input_axis_dim > 0) {
for (size_t i = 0; i < sections.size(); ++i) {
out_dims[i][axis_value] = sections[i];
}
} else {
for (size_t i = 0; i < sections.size(); ++i) {
out_dims[i][axis_value] = -1;
}
}

for (size_t i = 0; i < out.size(); ++i) {
for (size_t i = 0; i < sections.size(); ++i) {
if (axis_value != 0) {
// Only pass LoD when not spliting along the first dim.
out.at(i)->set_dtype(x.dtype());
out.at(i)->set_dims(out_dims[i]);
out.at(i)->set_layout(x.layout());
out[i]->set_dtype(x.dtype());
out[i]->set_dims(out_dims[i]);
out[i]->set_layout(x.layout());
} else {
out.at(i)->set_dtype(x.dtype());
out.at(i)->set_dims(out_dims[i]);
out.at(i)->set_layout(x.layout());
out.at(i)->share_lod(x);
out[i]->set_dtype(x.dtype());
out[i]->set_dims(out_dims[i]);
out[i]->set_layout(x.layout());
out[i]->share_lod(x);
}
}
}
Expand Down
17 changes: 17 additions & 0 deletions paddle/phi/kernels/cpu/split_kernel.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -28,6 +28,23 @@ void SplitKernel(const Context& dev_ctx,
const ScalarArray& num_or_sections,
const Scalar& axis_scalar,
std::vector<DenseTensor*> outs) {
// need to infershape output
if (num_or_sections.FromTensor() || axis_scalar.FromTensor()) {
std::vector<MetaTensor> out_metas;
out_metas.reserve(outs.size());
std::vector<MetaTensor*> out_metas_ptr;
for (size_t i = 0; i < outs.size(); ++i) {
out_metas.push_back(outs[i]);
out_metas_ptr.push_back(&out_metas.back());
}

phi::SplitInferMeta(x, num_or_sections, axis_scalar, out_metas_ptr, true);

for (size_t i = 0; i < out_metas.size(); ++i) {
outs[i]->Resize(out_metas[i].dims());
}
}

std::vector<const DenseTensor*> shape_refer;
for (size_t j = 0; j < outs.size(); ++j) {
dev_ctx.template Alloc<T>(outs[j]);
Expand Down
17 changes: 17 additions & 0 deletions paddle/phi/kernels/gpu/split_kernel.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,23 @@ void SplitKernel(const Context& dev_ctx,
const ScalarArray& num_or_sections,
const Scalar& axis_scalar,
std::vector<DenseTensor*> outs) {
// need to infershape output
if (num_or_sections.FromTensor() || axis_scalar.FromTensor()) {
std::vector<MetaTensor> out_metas;
out_metas.reserve(outs.size());
std::vector<MetaTensor*> out_metas_ptr;
for (size_t i = 0; i < outs.size(); ++i) {
out_metas.push_back(outs[i]);
out_metas_ptr.push_back(&out_metas.back());
}

phi::SplitInferMeta(x, num_or_sections, axis_scalar, out_metas_ptr, true);

for (size_t i = 0; i < out_metas.size(); ++i) {
outs[i]->Resize(out_metas[i].dims());
}
}

std::vector<const DenseTensor*> shape_refer;
for (size_t j = 0; j < outs.size(); ++j) {
dev_ctx.template Alloc<T>(outs[j]);
Expand Down