frozenleaves/pytorch
1
0
Fork 0
mirror of https://github.com/pytorch/pytorch.git synced 2025-10-21 05:34:18 +08:00
Code Issues Packages Projects Releases Wiki Activity

Remove deprecated info argument in btrifact (#14935)

Browse Source 
Summary:
As specified in title.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/14935

Differential Revision: D13394449

Pulled By: soumith

fbshipit-source-id: 569d59414f3a1a43ea641bded4b5433eb53e3490
This commit is contained in:
vishwakftw
2018-12-09 15:53:34 -08:00
committed by Facebook Github Bot
parent 86e03b8a30
commit fc30e2782c
5 changed files with 43 additions and 70 deletions
Download Patch File Download Diff File Expand all files Collapse all files

48
torch/functional.py
View File

@ -10,7 +10,6 @@ __all__ = [
'argmax',
'argmin',
'argsort',
'btrifact',
'btriunpack',
'chain_matmul',
'einsum',
@ -75,53 +74,6 @@ def split(tensor, split_size_or_sections, dim=0):
return tensor.split(split_size_or_sections, dim)
def btrifact(A, info=None, pivot=True):
r"""Batch LU factorization.
Returns a tuple containing the LU factorization and pivots. Pivoting is done if
:attr:`pivot` is set.
The optional argument :attr:`info` stores information if the factorization
succeeded for each minibatch example. The :attr:`info` is provided as an
`IntTensor`, its values will be filled from dgetrf and a non-zero value
indicates an error occurred. Specifically, the values are from cublas if cuda is
being used, otherwise LAPACK.
.. warning::
The :attr:`info` argument is deprecated in favor of :meth:`torch.btrifact_with_info`.
Arguments:
A (Tensor): the tensor to factor
info (IntTensor, optional): (deprecated) an `IntTensor` to store values
indicating whether factorization succeeds
pivot (bool, optional): controls whether pivoting is done
Returns:
A tuple containing factorization and pivots.
Example::
>>> A = torch.randn(2, 3, 3)
>>> A_LU, pivots = torch.btrifact(A)
>>> A_LU
tensor([[[ 1.3506, 2.5558, -0.0816],
[ 0.1684, 1.1551, 0.1940],
[ 0.1193, 0.6189, -0.5497]],
[[ 0.4526, 1.2526, -0.3285],
[-0.7988, 0.7175, -0.9701],
[ 0.2634, -0.9255, -0.3459]]])
>>> pivots
tensor([[ 3, 3, 3],
[ 3, 3, 3]], dtype=torch.int32)
"""
# Overwriting reason:
# `info` is being deprecated in favor of `btrifact_with_info`. This warning
# is in tensor.py, which we call here.
return A.btrifact(info, pivot)
def btriunpack(LU_data, LU_pivots, unpack_data=True, unpack_pivots=True):
r"""Unpacks the data and pivots from a batched LU factorization (btrifact) of a tensor.