}

std::optional<RankedTensorType> InferXlaConvOutputShape(
    llvm::SmallVector<int64_t> input_tensor_dims,
    llvm::SmallVector<int64_t> kernel_tensor_dims,
    llvm::SmallVector<int64_t> window_strides,
    llvm::SmallVector<std::pair<int64_t, int64_t>> paddings,
    llvm::SmallVector<int64_t> lhs_dilations,
    llvm::SmallVector<int64_t> rhs_dilations, int64_t batch_group_count,

  auto dict_attr = fn->getAttrOfType<mlir::DictionaryAttr>("tf.entry_function");
  if (!dict_attr) return;

  llvm::SmallVector<llvm::StringRef, 2> input_names;
  llvm::SmallVector<llvm::StringRef, 2> output_names;
  if (auto str =
          mlir::dyn_cast_or_null<mlir::StringAttr>(dict_attr.get("inputs"))) {
    str.getValue().split(input_names, ',', /*MaxSplit=*/-1,