Skip to content

[CINN] Refine infer_symbol_shape of unique_consecutive op #72394

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Apr 22, 2025
Merged

[CINN] Refine infer_symbol_shape of unique_consecutive op #72394

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
46 changes: 34 additions & 12 deletions paddle/fluid/pir/dialect/operator/interface/infer_symbolic_shape/unary_infer_sym.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4170,15 +4170,9 @@ bool UniqueOpInferSymbolicShape(pir::Operation *op,
pir::InferSymbolicShapeContext *infer_context) {
const auto &x_shape_or_data =
infer_context->GetShapeOrDataForValue(op->operand_source(0));
PADDLE_ENFORCE_EQ(
x_shape_or_data.data().has_value(),
false,
common::errors::InvalidArgument(
"InferSymbolicShape of UniqueOp only support input with "
"value now."));
const auto &x_dims_sym = x_shape_or_data.shape();
const size_t rank = x_dims_sym.size();
std::vector<int> axes =
const std::vector<int> axes =
paddle::dialect::details::GetVectorAttr<int>(op, "axis");

symbol::DimExpr unique_dim_sym =
Expand Down Expand Up @@ -4246,8 +4240,40 @@ bool UniqueConsecutiveOpInferSymbolicShape(
infer_context->GetShapeOrDataForValue(op->operand_source(0));
const auto &x_dims_sym = x_shape_or_data.shape();
const size_t rank = x_dims_sym.size();
std::vector<int> axes =
const std::vector<int> axes =
paddle::dialect::details::GetVectorAttr<int>(op, "axis");
const bool return_inverse = GetBoolAttr(op, "return_inverse");
const bool return_counts = GetBoolAttr(op, "return_counts");
symbol::ShapeOrDataDimExprs empty{symbol::TensorShapeOrDataDimExprs{}};

// x has data
if (x_shape_or_data.data().has_value() && (rank == 1 || axes.empty())) {
const auto &x_data = x_shape_or_data.data().value();
const bool is_all_const = [&] {
for (const auto &x_value : x_data) {
if (!x_value.isa<int64_t>()) return false;
}
return true;
}();
if (is_all_const) {
auto out_data = x_data;
auto last = std::unique(out_data.begin(), out_data.end());
out_data.erase(last, out_data.end());
const std::vector<symbol::DimExpr> out_size{
static_cast<int64_t>(out_data.size())};

infer_context->SetShapeOrDataForValue(
op->result(0), symbol::TensorShapeOrDataDimExprs{out_size, out_data});
infer_context->SetShapeOrDataForValue(
op->result(1),
return_inverse ? symbol::TensorShapeOrDataDimExprs{x_dims_sym}
: empty);
infer_context->SetShapeOrDataForValue(
op->result(2),
return_counts ? symbol::TensorShapeOrDataDimExprs{out_size} : empty);
return true;
}
}

symbol::DimExpr unique_dim_sym =
infer_context->GetNextSymName(); // unknown until runtime
Expand Down Expand Up @@ -4286,10 +4312,6 @@ bool UniqueConsecutiveOpInferSymbolicShape(
return inverse_dims;
}();

bool return_inverse = GetBoolAttr(op, "return_inverse");
bool return_counts = GetBoolAttr(op, "return_counts");

symbol::ShapeOrDataDimExprs empty{symbol::TensorShapeOrDataDimExprs{}};
infer_context->SetShapeOrDataForValue(
op->result(0), symbol::TensorShapeOrDataDimExprs{out_dims});
infer_context->SetShapeOrDataForValue(
Expand Down
Loading