/
config.py
35 lines (24 loc) · 981 Bytes
/
config.py
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
import torch
import os
import logging
from datetime import datetime
# smaller images(h5) -"dataset/data/2_2_2_downsampled/train"
# larger images(nrrd) - "dataset/data/nrrd_data/train"
# dataset_path = "/misc/lmbssd/venkatev/data/data/train"
dataset_path = "/misc/lmbssd/venkatev/data/data/"
output_path = os.path.join("output")
device = "cuda" if torch.cuda.is_available() else "cpu"
max_image_dim = [80, 512, 512]
n_channels = 1
n_classes = 2
ignore_label = [2]
checkpoint_dir = os.path.join("checkpoints")
def get_logger():
logging.basicConfig(handlers=[
logging.FileHandler(filename=datetime.now().strftime('logs/training_log_%H_%M_%d_%m_%Y.log'),
encoding='utf-8')], format='%(asctime)s %(message)s', datefmt='%m/%d/%Y %I:%M:%S %p')
# Creating an object
logger = logging.getLogger()
# Setting the threshold of logger to DEBUG
logger.setLevel(logging.DEBUG)
return logger