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[codemod][lint][fbcode/c*] Enable BLACK by default

Browse Source 
Test Plan: manual inspection & sandcastle

Reviewed By: zertosh

Differential Revision: D30279364

fbshipit-source-id: c1ed77dfe43a3bde358f92737cd5535ae5d13c9a
This commit is contained in:
Zsolt Dollenstein
2021-08-12 10:56:55 -07:00
committed by Facebook GitHub Bot
parent aac3c7bd06
commit b004307252
188 changed files with 56875 additions and 28744 deletions
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31
torch/random.py
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@ -1,8 +1,8 @@
import contextlib
import warnings
from torch._C import default_generator
import torch
from torch._C import default_generator
def set_rng_state(new_state: torch.Tensor) -> None:
@ -82,6 +82,7 @@ def fork_rng(devices=None, enabled=True, _caller="fork_rng", _devices_kw="device
"""
import torch.cuda
global _fork_rng_warned_already
# Internal arguments:
@ -96,18 +97,22 @@ def fork_rng(devices=None, enabled=True, _caller="fork_rng", _devices_kw="device
num_devices = torch.cuda.device_count()
if num_devices > 1 and not _fork_rng_warned_already:
warnings.warn(
("CUDA reports that you have {num_devices} available devices, and you "
"have used {caller} without explicitly specifying which devices are being used. "
"For safety, we initialize *every* CUDA device by default, which "
"can be quite slow if you have a lot of GPUs. If you know that you are only "
"making use of a few CUDA devices, set the environment variable CUDA_VISIBLE_DEVICES "
"or the '{devices_kw}' keyword argument of {caller} with the set of devices "
"you are actually using. For example, if you are using CPU only, "
"set CUDA_VISIBLE_DEVICES= or devices=[]; if you are using "
"GPU 0 only, set CUDA_VISIBLE_DEVICES=0 or devices=[0]. To initialize "
"all devices and suppress this warning, set the '{devices_kw}' keyword argument "
"to `range(torch.cuda.device_count())`."
).format(num_devices=num_devices, caller=_caller, devices_kw=_devices_kw))
(
"CUDA reports that you have {num_devices} available devices, and you "
"have used {caller} without explicitly specifying which devices are being used. "
"For safety, we initialize *every* CUDA device by default, which "
"can be quite slow if you have a lot of GPUs. If you know that you are only "
"making use of a few CUDA devices, set the environment variable CUDA_VISIBLE_DEVICES "
"or the '{devices_kw}' keyword argument of {caller} with the set of devices "
"you are actually using. For example, if you are using CPU only, "
"set CUDA_VISIBLE_DEVICES= or devices=[]; if you are using "
"GPU 0 only, set CUDA_VISIBLE_DEVICES=0 or devices=[0]. To initialize "
"all devices and suppress this warning, set the '{devices_kw}' keyword argument "
"to `range(torch.cuda.device_count())`."
).format(
num_devices=num_devices, caller=_caller, devices_kw=_devices_kw
)
)
_fork_rng_warned_already = True
devices = list(range(num_devices))
else: