Add deterministic path for CUDA cumsum (#136224)

Change `cumsum` to call its decomposition when `use_deterministic_algorithms(True)` and input is CUDA.

Fixes #89492

Pull Request resolved: https://github.com/pytorch/pytorch/pull/136224
Approved by: https://github.com/ezyang, https://github.com/justinchuby

torch/_torch_docs.py

@@ -3317,38 +3317,6 @@ Example::
 """.format(**reduceops_common_args),
 )
 
-add_docstr(
-    torch.cumsum,
-    r"""
-cumsum(input, dim, *, dtype=None, out=None) -> Tensor
-
-Returns the cumulative sum of elements of :attr:`input` in the dimension
-:attr:`dim`.
-
-For example, if :attr:`input` is a vector of size N, the result will also be
-a vector of size N, with elements.
-
-.. math::
-    y_i = x_1 + x_2 + x_3 + \dots + x_i
-
-Args:
-    {input}
-    dim  (int): the dimension to do the operation over
-
-Keyword args:
-    {dtype}
-    {out}
-
-Example::
-
-    >>> a = torch.randint(1, 20, (10,))
-    >>> a
-    tensor([13,  7,  3, 10, 13,  3, 15, 10,  9, 10])
-    >>> torch.cumsum(a, dim=0)
-    tensor([13, 20, 23, 33, 46, 49, 64, 74, 83, 93])
-""".format(**reduceops_common_args),
-)
-
 add_docstr(
     torch.count_nonzero,
     r"""