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Fix typo: 'recieve' → 'receive' in comments (#157544)
This PR corrects minor typos in developer-facing comments: - Replaces 'recieve' with 'receive' in: - `FunctionalTensorWrapper.cpp` - `make_boxed_from_unboxed_functor.h` These changes improve code readability and maintain comment correctness. Thank you for reviewing! Pull Request resolved: https://github.com/pytorch/pytorch/pull/157544 Approved by: https://github.com/soulitzer
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@ -178,7 +178,7 @@ bool FunctionalTensorWrapper::is_up_to_date() const {
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// See Note [Functionalization Pass - Inplace View Ops]
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void FunctionalTensorWrapper::mutate_view_meta(const at::functionalization::ViewMeta& meta) {
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view_metas_.push_back(meta);
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// Manually track the fact that this tensor recieved a metadata mutation!
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// Manually track the fact that this tensor received a metadata mutation!
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has_metadata_mutation_ = true;
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// Mark this tensor as being symbolic if there are any symbolic inputs used by the view operation.
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maybe_mark_symbolic(meta);
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@ -579,7 +579,7 @@ std::vector<Tensor> from_functional_tensor(ITensorListRef t_list) {
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for (const auto& tensor : t_list) {
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// from_functional_tensor(Tensor) has asserts to make sure you don't accidentally call
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// it on a non-functional input,
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// but from_functional_tensor(TensorList) can recieve a list containing both
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// but from_functional_tensor(TensorList) can receive a list containing both
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// functional and non-functional tensors.
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// Example of when that can happen: torch.cat(function_input_tensor, global_state_tensor).
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// When that happens, we're okay with only unwrapping the functional tensors.
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@ -105,7 +105,7 @@ using supported_primitive_arg_types = guts::typelist::typelist<
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// So a valid input type is one that our boxed functor wrapper can
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// unbox from an IValue into a C++ value.
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//
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// Whereas a valid output type is one that our wrapper can recieve
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// Whereas a valid output type is one that our wrapper can receive
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// as a C++ value from the unboxed functor, and box into an IValue.
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//
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