File size: 1,794 Bytes
ad16788 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
import logging
import os
import chainer
import torch
def set_deterministic_pytorch(args):
"""Ensures pytorch produces deterministic results depending on the program arguments
:param Namespace args: The program arguments
"""
# seed setting
torch.manual_seed(args.seed)
# debug mode setting
# 0 would be fastest, but 1 seems to be reasonable
# considering reproducibility
# remove type check
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = (
False # https://github.com/pytorch/pytorch/issues/6351
)
if args.debugmode < 2:
chainer.config.type_check = False
logging.info("torch type check is disabled")
# use deterministic computation or not
if args.debugmode < 1:
torch.backends.cudnn.deterministic = False
torch.backends.cudnn.benchmark = True
logging.info("torch cudnn deterministic is disabled")
def set_deterministic_chainer(args):
"""Ensures chainer produces deterministic results depending on the program arguments
:param Namespace args: The program arguments
"""
# seed setting (chainer seed may not need it)
os.environ["CHAINER_SEED"] = str(args.seed)
logging.info("chainer seed = " + os.environ["CHAINER_SEED"])
# debug mode setting
# 0 would be fastest, but 1 seems to be reasonable
# considering reproducibility
# remove type check
if args.debugmode < 2:
chainer.config.type_check = False
logging.info("chainer type check is disabled")
# use deterministic computation or not
if args.debugmode < 1:
chainer.config.cudnn_deterministic = False
logging.info("chainer cudnn deterministic is disabled")
else:
chainer.config.cudnn_deterministic = True
|