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[BE][8/16] fix typos in torch/ (torch/csrc/jit/) (#156318)

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Pull Request resolved: https://github.com/pytorch/pytorch/pull/156318
Approved by: https://github.com/albanD
This commit is contained in:
Xuehai Pan
2025-07-03 02:11:53 +08:00
committed by PyTorch MergeBot
parent c0e155a8d2
commit 541584d22e
45 changed files with 76 additions and 77 deletions
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8
torch/csrc/jit/serialization/export_module.cpp
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@ -131,7 +131,7 @@ std::string get_named_tuple_str_or_default(
// str() return "Tensor" and repr_str() return "Tensor (inferred)". If
// it's not inferred type, str() return "Tensor[]" and repr_str()
// return "Tensor". In cpp, repr_str() will always return "Tensor"
// regardless inferred type. When exporing custom type in bytecode,
// regardless inferred type. When exporting custom type in bytecode,
// "Tensor" is the preferred way to deserialize Tensor type
std::string named_tuple_type_str = it->is_inferred_type()
? named_tuple_type->str()
@ -554,7 +554,7 @@ void ScriptModuleSerializer::writeArchive(
}
WriteableTensorData writable_td = getWriteableTensorData(td);
if (use_storage_context && serialized_tensors.count(tensor_name)) {
// storage has been serialzed already, skip
// storage has been serialized already, skip
continue;
}
writer_.writeRecord(
@ -698,10 +698,10 @@ void ScriptModuleSerializer::writeByteCode(
// debug handles.
// The reason we save debug handles conditionally is so that
// we dont end up with a model that has debug handles but has not
// debug map to correlate debug handels with.
// debug map to correlate debug handles with.
// Once we have a model with both handles and debug map, we can
// strip off debug map and have a lean model served to production.
// If exception ocurrs we have a model with debug map that can be
// If exception occurs we have a model with debug map that can be
// used to symbolicate debug handles
writeArchive(
debug_info_telements,