58 lines
1.5 KiB
Python
58 lines
1.5 KiB
Python
import torch
|
|
import numpy as np
|
|
|
|
|
|
class MovAvg(object):
|
|
"""Class for moving average. Usage:
|
|
::
|
|
|
|
>>> stat = MovAvg(size=66)
|
|
>>> stat.add(torch.tensor(5))
|
|
5.0
|
|
>>> stat.add(float('inf')) # which will not add to stat
|
|
5.0
|
|
>>> stat.add([6, 7, 8])
|
|
6.5
|
|
>>> stat.get()
|
|
6.5
|
|
>>> print(f'{stat.mean():.2f}±{stat.std():.2f}')
|
|
6.50±1.12
|
|
"""
|
|
def __init__(self, size=100):
|
|
super().__init__()
|
|
self.size = size
|
|
self.cache = []
|
|
|
|
def add(self, x):
|
|
"""Add a scalar into :class:`MovAvg`. You can add ``torch.Tensor`` with
|
|
only one element, a python scalar, or a list of python scalar. It will
|
|
exclude the infinity.
|
|
"""
|
|
if isinstance(x, torch.Tensor):
|
|
x = x.item()
|
|
if isinstance(x, list):
|
|
for _ in x:
|
|
if _ != np.inf:
|
|
self.cache.append(_)
|
|
elif x != np.inf:
|
|
self.cache.append(x)
|
|
if self.size > 0 and len(self.cache) > self.size:
|
|
self.cache = self.cache[-self.size:]
|
|
return self.get()
|
|
|
|
def get(self):
|
|
"""Get the average."""
|
|
if len(self.cache) == 0:
|
|
return 0
|
|
return np.mean(self.cache)
|
|
|
|
def mean(self):
|
|
"""Get the average. Same as :meth:`get`."""
|
|
return self.get()
|
|
|
|
def std(self):
|
|
"""Get the standard deviation."""
|
|
if len(self.cache) == 0:
|
|
return 0
|
|
return np.std(self.cache)
|