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utils.py
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utils.py
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from __future__ import absolute_import
import os
import sys
import errno
import shutil
import json
import os.path as osp
import torch
def mkdir_if_missing(directory):
if not osp.exists(directory):
try:
os.makedirs(directory)
except OSError as e:
if e.errno != errno.EEXIST:
raise
class AverageMeter(object):
"""Computes and stores the average and current value.
Code imported from https://github.com/pytorch/examples/blob/master/imagenet/main.py#L247-L262
"""
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
def update(self, val, n=1):
self.val = val
self.sum += val * n
self.count += n
self.avg = self.sum / self.count
def save_checkpoint(state, is_best, fpath='checkpoint.pth.tar'):
mkdir_if_missing(osp.dirname(fpath))
torch.save(state, fpath)
if is_best:
shutil.copy(fpath, osp.join(osp.dirname(fpath), 'best_model.pth.tar'))
class Logger(object):
"""
Write console output to external text file.
Code imported from https://github.com/Cysu/open-reid/blob/master/reid/utils/logging.py.
"""
def __init__(self, fpath=None):
self.console = sys.stdout
self.file = None
if fpath is not None:
mkdir_if_missing(os.path.dirname(fpath))
self.file = open(fpath, 'w')
def __del__(self):
self.close()
def __enter__(self):
pass
def __exit__(self, *args):
self.close()
def write(self, msg):
self.console.write(msg)
if self.file is not None:
self.file.write(msg)
def flush(self):
self.console.flush()
if self.file is not None:
self.file.flush()
os.fsync(self.file.fileno())
def close(self):
self.console.close()
if self.file is not None:
self.file.close()
def read_json(fpath):
with open(fpath, 'r') as f:
obj = json.load(f)
return obj
def write_json(obj, fpath):
mkdir_if_missing(osp.dirname(fpath))
with open(fpath, 'w') as f:
json.dump(obj, f, indent=4, separators=(',', ': '))