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Remove guard_size_oblivious from default contiguity python check, and add aten.sym_is_contiguous. [attempt2] (#160869)

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[relanding again after fixing internal build]
Summary:
This might cause some new DDEs on call sites that do not use is_contiguous_or_false() or sym_is_contiguous()
but want to find those call sites to handle this properly by calling  is_contiguous_or_false() and not is_contiguous() explitly when appropriate.
I had to fix one issue after removing the implicit size oblivious reasoning. here is context

we defined in this https://github.com/pytorch/pytorch/pull/157472 sym_is_contiguous to be the function computing contiguity for dynamic shapes in c++. It returns a symbolic expression that represents contiguity and guaranteed not to throw a DDE.

when people call is_contiguous we do sym_is_contiguous().guard_bool()
when people call is_contiguous_or_false we do sym_is_contiguous().guard_or_false()

one issue not handled well was this path
```
c10::SymBool TensorImpl::sym_is_contiguous_custom(
    at::MemoryFormat memory_format) const {
  if (C10_UNLIKELY(matches_python_custom(SizesStridesPolicy::CustomStrides))) {
    return pyobj_slot_.load_pyobj_interpreter()->is_contiguous(
        this, memory_format);
  }

  return sym_is_contiguous_default(memory_format);
}
```
namely if we call sym_is_contiguous_custom but we have matches_python_custom(SizesStridesPolicy::CustomStrides) return true , then we used to call is_contiguous(this, memory_format);

This used to go through the load_pyobj_interpreter and end up calling the python is_contiguous call which used implicit size oblivious reasoning.
once we removed that implicit size oblivious reasoning, the right thing we want is to call
return pyobj_slot_.load_pyobj_interpreter()->sym_is_contiguous(this, memory_format);
otherwise we would get DDE even if the caller is doing sym_is_contiguous.

so I had to define it for pyinterpreter, and then I had to override it for nested tensors.

Approved by: https://github.com/ezyang

Test Plan:
contbuild & OSS CI, see e444cd24d4

Rollback Plan:

Differential Revision: D80435179

Pull Request resolved: https://github.com/pytorch/pytorch/pull/160869
Approved by: https://github.com/ezyang
This commit is contained in:
Laith Sakka
2025-09-08 22:59:13 +00:00
committed by PyTorch MergeBot
parent 5fd6b6a2db
commit 189a054cfb
21 changed files with 142 additions and 34 deletions
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2
torchgen/api/types/types.py
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@ -79,6 +79,7 @@ tensorOptionsT = BaseCppType("at", "TensorOptions")
typeAndSizeT = BaseCppType("torch::autograd::generated", "TypeAndSize")
tensorGeometryT = BaseCppType("at", "TensorGeometry")
SymIntT = BaseCppType("c10", "SymInt")
SymBoolT = BaseCppType("c10", "SymBool")
symIntArrayRefT = BaseCppType("c10", "SymIntArrayRef")
# Types representing template parameters. Technically, we probably shouldn't
@ -125,6 +126,7 @@ BaseTypeToCppMapping: dict[BaseTy, BaseCppType] = {
BaseTy.Storage: storageT,
BaseTy.Stream: streamT,
BaseTy.SymInt: SymIntT,
BaseTy.SymBool: SymBoolT,
}
# CTypes encode C++ type structure as needed for translation.