python tqdm库的使用

from tqdm import tqdm

 for i in tqdm(range(2)): 
 pass

desc=None,     str类型，作为进度条说明
total=None,     预期的迭代次数   
file=None,     输出方式，默认为sys.stderr
ncols=None,    进度条长度
mininterval=0.1,   进度条最小的更新间隔，单位秒，默认：0.1
maxinterval=10.0,  进度条最大更新间隔，单位秒，默认：10
unit='it',      单位，默认it每秒迭代数
bar_format=None,  进度条格式
postfix       字典形式信息，例如：速度=5

  Specify a custom bar string formatting. May impact performance.
  [default: '{l_bar}{bar}{r_bar}'], where
  l_bar='{desc}: {percentage:3.0f}%|' and
  r_bar='| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, '
   '{rate_fmt}{postfix}]'
  Possible vars: l_bar, bar, r_bar, n, n_fmt, total, total_fmt,
   percentage, elapsed, elapsed_s, ncols, nrows, desc, unit,
   rate, rate_fmt, rate_noinv, rate_noinv_fmt,
   rate_inv, rate_inv_fmt, postfix, unit_divisor,
   remaining, remaining_s.
  Note that a trailing ": " is automatically removed after {desc}
  if the latter is empty.

percentage:百分比
n_fmt：当前数
total_fmt：总数
elapsed：消耗的时间
remaining：剩余时间
rate_fmt：速率
postifx：后缀字典描述
desc、postfix默认为空；

import numpy as np
from torch.utils.data import DataLoader
import time
from tqdm import tqdm, tqdm_notebook
from random import random

data =np.array([1,2,3,4])
data_loader = DataLoader(data, batch_size=2, num_workers=0, shuffle=False)

iterator = tqdm(data_loader,maxinterval=10,
        mininterval=2, ncols=80,
        bar_format='{l_bar}|{bar}| {n_fmt}/{total_fmt} [{rate_fmt}{postfix}|{elapsed}<{remaining}]',
        nrows=10,smoothing=0.1)
epoch =0
for d in iterator:
  time.sleep(2)
  epoch +=1
  print(d)
  iterator.set_description('epoch %d' %epoch)
  iterator.set_postfix_str('loss={:^7.3f}'.format(random()))