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Revert "Add check-sparse-tensor-invariants flag to Context. (#90849)"

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This reverts commit b9a035c1c58630f3eef5242cb4849881b8376b39.

Reverted https://github.com/pytorch/pytorch/pull/90849 on behalf of https://github.com/DanilBaibak due to Break internal build
This commit is contained in:
PyTorch MergeBot
2023-01-12 09:58:16 +00:00
parent 05d0c4cee3
commit c7a22bb7c7
18 changed files with 96 additions and 493 deletions
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106
torch/sparse/__init__.py
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@ -18,7 +18,6 @@ else:
__all__ = [
'addmm',
'check_sparse_tensor_invariants',
'mm',
'sum',
'softmax',
@ -358,108 +357,3 @@ Specifying a positive offset::
[0, 0, 0, 0, 0],
[0, 0, 0, 0, 0]])
""")
class check_sparse_tensor_invariants(object):
"""A tool to control checking sparse tensor invariants.
The following options exists to manage sparsr tensor invariants
checking in sparse tensor construction:
1. Using a context manager:
.. code:: python
with torch.sparse.check_sparse_tensor_invariants():
run_my_model()
2. Using a procedural approach:
.. code:: python
prev_checks_enabled = torch.sparse.check_sparse_tensor_invariants.is_enabled()
torch.sparse.check_sparse_tensor_invariants.enable()
run_my_model()
if not prev_checks_enabled:
torch.sparse.check_sparse_tensor_invariants.disable()
3. Using function decoration:
.. code:: python
@torch.sparse.check_sparse_tensor_invariants()
def run_my_model():
...
run_my_model()
4. Using ``check_invariants`` keyword argument in sparse tensor constructor call.
For example:
>>> torch.sparse_csr_tensor([0, 1, 3], [0, 1], [1, 2], check_invariants=True)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
RuntimeError: `crow_indices[..., -1] == nnz` is not satisfied.
"""
@staticmethod
def is_enabled():
r"""Returns True if the sparse tensor invariants checking is enabled.
.. note::
Use :func:`torch.sparse.check_sparse_tensor_invariants.enable` or
:func:`torch.sparse.check_sparse_tensor_invariants.disable` to
manage the state of the sparse tensor invariants checks.
"""
return torch._C._check_sparse_tensor_invariants()
@staticmethod
def enable():
r"""Enable sparse tensor invariants checking in sparse tensor constructors.
.. note::
By default, the sparse tensor invariants checks are disabled. Use
:func:`torch.sparse.check_sparse_tensor_invariants.is_enabled` to
retrieve the current state of sparse tensor invariants checking.
.. note::
The sparse tensor invariants check flag is effective to all sparse
tensor constructors, both in Python and ATen.
The flag can be locally overridden by the ``check_invariants``
optional argument of the sparse tensor constructor functions.
"""
torch._C._set_check_sparse_tensor_invariants(True)
@staticmethod
def disable():
r"""Disable sparse tensor invariants checking in sparse tensor constructors.
See :func:`torch.sparse.check_sparse_tensor_invariants.enable` for more information.
"""
torch._C._set_check_sparse_tensor_invariants(False)
# context manager support
def __init__(self, enable=True):
self.state = enable
self.saved_state = self.is_enabled()
def __enter__(self):
torch._C._set_check_sparse_tensor_invariants(self.state)
def __exit__(self, type, value, traceback):
torch._C._set_check_sparse_tensor_invariants(self.saved_state)
# decorator support
def __call__(self, mth):
def test_mth(*args, **kwargs):
with type(self)(self.state):
return mth(*args, **kwargs)
return test_mth