178 lines
No EOL
4.5 KiB
Python
178 lines
No EOL
4.5 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from abc import ABCMeta
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from abc import abstractmethod
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import six
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import collections
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from functools import lru_cache
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import numpy as np
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__all__ = ["MetricMeter", "StandardMeter", "AverageMeter", "MovingAverageMeter", "MemoryLessMovingAverageMeter"]
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# Supported Numpy DTypes: `np.sctypes`
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ACCEPTED_INT_NUMBER_FORMATS = (
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int,
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np.uint8,
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np.uint16,
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np.uint32,
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np.uint64,
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np.int,
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np.int8,
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np.int16,
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np.int32,
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np.int64,
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)
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ACCEPTED_FLOAT_NUMBER_FORMATS = (
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float,
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np.float,
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np.float16,
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np.float32,
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np.float64,
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np.float128,
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)
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ACCEPTED_STR_NUMBER_FORMATS = (
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str,
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np.str,
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)
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ACCEPTED_NUMBER_FORMATS = \
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ACCEPTED_INT_NUMBER_FORMATS + \
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ACCEPTED_FLOAT_NUMBER_FORMATS + \
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ACCEPTED_STR_NUMBER_FORMATS
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@six.add_metaclass(ABCMeta)
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class AbstractMeterMixin(object):
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@abstractmethod
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def AUTHORIZED_DTYPES(self):
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pass
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@six.add_metaclass(ABCMeta)
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class MetricMeter(AbstractMeterMixin):
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# Supported Numpy DTypes: `np.sctypes`
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AUTHORIZED_DTYPES = tuple(ACCEPTED_NUMBER_FORMATS)
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@lru_cache(maxsize=128)
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def __init__(self):
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self._values = np.array([])
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def reset(self):
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self._values = np.array([])
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@lru_cache(maxsize=128)
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def __str__(self):
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return self.__class__.__name__
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def get_last(self):
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try:
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return self._values[-1]
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except IndexError:
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raise ValueError("Impossible to get the last value. No value has been recorded yet")
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def record(self, val):
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if not isinstance(val, MetricMeter.AUTHORIZED_DTYPES):
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raise TypeError("Unsupported datatype received: %s" % str(type(val)))
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if np.isnan(val) or np.isinf(val):
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raise ValueError("invalid value received: %s" % str(val))
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self._values = np.append(self._values, val)
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@abstractmethod
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def read(self):
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raise NotImplementedError()
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class StandardMeter(MetricMeter):
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def read(self):
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return self.get_last()
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class AverageMeter(MetricMeter):
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def read(self):
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if len(self._values):
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return np.mean(self._values)
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else:
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raise ValueError("NaN Result, Impossible to compute the average of an empty list")
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class MovingAverageMeter(MetricMeter):
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def __init__(self, window_size):
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super(MovingAverageMeter, self).__init__()
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if not isinstance(window_size, int):
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raise ValueError("`window_size` must be an integer")
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if window_size < 1:
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raise ValueError("`window_size` must be superior or equal to 1")
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self._window_size = window_size
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@lru_cache(maxsize=128)
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def __str__(self):
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return "%s(window_size=%d)" % (super(MovingAverageMeter, self).__str__(), self._window_size)
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def read(self):
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if len(self._values):
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return np.mean(self._values[-self._window_size:])
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else:
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raise ValueError("NaN Result, Impossible to compute the moving average of an empty list")
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class MemoryLessMovingAverageMeter(MetricMeter):
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def __init__(self, window_size):
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super(MemoryLessMovingAverageMeter, self).__init__()
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self._values = collections.deque(maxlen=window_size)
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if not isinstance(window_size, int):
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raise ValueError("`window_size` must be an integer")
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if window_size < 1:
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raise ValueError("`window_size` must be superior or equal to 1")
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self._window_size = window_size
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def reset(self):
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self._values = collections.deque(maxlen=self._window_size)
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@lru_cache(maxsize=128)
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def __str__(self):
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return "%s(window_size=%d)" % (super(MemoryLessMovingAverageMeter, self).__str__(), self._window_size)
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def read(self):
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if len(self._values):
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return np.mean(self._values)
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else:
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raise ValueError("NaN Result, Impossible to compute the moving average of an empty list") |