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AverageMeter

danling.metrics.average_meter

AverageMeter

Computes and stores the average and current value.

Attributes:

Name Type Description
val float

Results of current batch on current device.
bat

Results of current batch on all devices.
avg

Results of all results on all devices.
sum float

Sum of values.
count float

Number of values.
See Also

[MetricMeter]: Average Meter with metric function built-in. [AverageMeters]: Manage multiple average meters in one object. [MultiTaskAverageMeters]: Manage multiple average meters in one object with multi-task support.

Examples:

Python Console Session
>>> meter = AverageMeter()
>>> meter.update(0.7)
>>> meter.val
0.7
>>> meter.avg
0.7
>>> meter.update(0.9)
>>> meter.val
0.9
>>> meter.avg
0.8
>>> meter.sum
1.6
>>> meter.count
2
>>> meter.reset()
>>> meter.val
0
>>> meter.avg
nan
Source code in danling/metrics/average_meter.py
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class AverageMeter:
    r"""
    Computes and stores the average and current value.

    Attributes:
        val: Results of current batch on current device.
        bat: Results of current batch on all devices.
        avg: Results of all results on all devices.
        sum: Sum of values.
        count: Number of values.

    See Also:
        [`MetricMeter`]: Average Meter with metric function built-in.
        [`AverageMeters`]: Manage multiple average meters in one object.
        [`MultiTaskAverageMeters`]: Manage multiple average meters in one object with multi-task support.

    Examples:
        >>> meter = AverageMeter()
        >>> meter.update(0.7)
        >>> meter.val
        0.7
        >>> meter.avg
        0.7
        >>> meter.update(0.9)
        >>> meter.val
        0.9
        >>> meter.avg
        0.8
        >>> meter.sum
        1.6
        >>> meter.count
        2
        >>> meter.reset()
        >>> meter.val
        0
        >>> meter.avg
        nan
    """

    val: float = 0
    n: float = 1
    sum: float = 0
    count: float = 0

    def __init__(self) -> None:
        self.reset()

    def reset(self) -> None:
        r"""
        Resets the meter.
        """

        self.val = 0
        self.n = 1
        self.sum = 0
        self.count = 0

    def update(self, value, n: float = 1) -> None:
        r"""
        Updates the average and current value in the meter.

        Args:
            value: Value to be added to the average.
            n: Number of values to be added.
        """

        self.val = value
        self.n = n
        self.sum += value * n
        self.count += n

    def value(self):
        return self.val

    def batch(self):
        world_size = get_world_size()
        if world_size == 1:
            return self.val / self.n if self.n != 0 else float("nan")
        synced_tuple = [None for _ in range(world_size)]
        dist.all_gather_object(synced_tuple, (self.val * self.n, self.n))
        val, n = zip(*synced_tuple)
        count = sum(n)
        if count == 0:
            return float("nan")
        return sum(val) / count

    def average(self):
        world_size = get_world_size()
        if world_size == 1:
            return self.sum / self.count if self.count != 0 else float("nan")
        synced_tuple = [None for _ in range(world_size)]
        dist.all_gather_object(synced_tuple, (self.sum, self.count))
        val, n = zip(*synced_tuple)
        count = sum(n)
        if count == 0:
            return float("nan")
        return sum(val) / count

    @property
    def bat(self):
        return self.batch()

    @property
    def avg(self):
        return self.average()

    def __format__(self, format_spec) -> str:
        return f"{self.val.__format__(format_spec)} ({self.avg.__format__(format_spec)})"

reset

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reset() -> None

Resets the meter.

Source code in danling/metrics/average_meter.py
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def reset(self) -> None:
    r"""
    Resets the meter.
    """

    self.val = 0
    self.n = 1
    self.sum = 0
    self.count = 0

update

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update(value, n: float = 1) -> None

Updates the average and current value in the meter.

Parameters:

Name Type Description Default
value

Value to be added to the average.

 required
n float

Number of values to be added.

 1
Source code in danling/metrics/average_meter.py
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def update(self, value, n: float = 1) -> None:
    r"""
    Updates the average and current value in the meter.

    Args:
        value: Value to be added to the average.
        n: Number of values to be added.
    """

    self.val = value
    self.n = n
    self.sum += value * n
    self.count += n

AverageMeters

Bases: MetricsDict

Manages multiple average meters in one object.

See Also

[AverageMeter]: Computes and stores the average and current value. [MultiTaskAverageMeters]: Manage multiple average meters in one object with multi-task support. [MetricMeters]: Manage multiple metric meters in one object.

Examples:

Python Console Session
>>> meters = AverageMeters()
>>> meters.update({"loss": 0.6, "auroc": 0.7, "r2": 0.8})
>>> f"{meters:.4f}"
'loss: 0.6000 (0.6000)\tauroc: 0.7000 (0.7000)\tr2: 0.8000 (0.8000)'
>>> meters['loss'].update(value=0.9, n=1)
>>> f"{meters:.4f}"
'loss: 0.9000 (0.7500)\tauroc: 0.7000 (0.7000)\tr2: 0.8000 (0.8000)'
>>> meters.sum.dict()
{'loss': 1.5, 'auroc': 0.7, 'r2': 0.8}
>>> meters.count.dict()
{'loss': 2, 'auroc': 1, 'r2': 1}
>>> meters.reset()
>>> f"{meters:.4f}"
'loss: 0.0000 (nan)\tauroc: 0.0000 (nan)\tr2: 0.0000 (nan)'
Source code in danling/metrics/average_meter.py
Python
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class AverageMeters(MetricsDict):
    r"""
    Manages multiple average meters in one object.

    See Also:
        [`AverageMeter`]: Computes and stores the average and current value.
        [`MultiTaskAverageMeters`]: Manage multiple average meters in one object with multi-task support.
        [`MetricMeters`]: Manage multiple metric meters in one object.

    Examples:
        >>> meters = AverageMeters()
        >>> meters.update({"loss": 0.6, "auroc": 0.7, "r2": 0.8})
        >>> f"{meters:.4f}"
        'loss: 0.6000 (0.6000)\tauroc: 0.7000 (0.7000)\tr2: 0.8000 (0.8000)'
        >>> meters['loss'].update(value=0.9, n=1)
        >>> f"{meters:.4f}"
        'loss: 0.9000 (0.7500)\tauroc: 0.7000 (0.7000)\tr2: 0.8000 (0.8000)'
        >>> meters.sum.dict()
        {'loss': 1.5, 'auroc': 0.7, 'r2': 0.8}
        >>> meters.count.dict()
        {'loss': 2, 'auroc': 1, 'r2': 1}
        >>> meters.reset()
        >>> f"{meters:.4f}"
        'loss: 0.0000 (nan)\tauroc: 0.0000 (nan)\tr2: 0.0000 (nan)'
    """

    def __init__(self, *args, default_factory: Type[AverageMeter] = AverageMeter, **kwargs) -> None:
        for meter in args:
            if not isinstance(meter, AverageMeter):
                raise ValueError(f"Expected meter to be an instance of AverageMeter, but got {type(meter)}")
        for name, meter in kwargs.items():
            if not isinstance(meter, AverageMeter):
                raise ValueError(f"Expected {name} to be an instance of AverageMeter, but got {type(meter)}")
        super().__init__(*args, default_factory=default_factory, **kwargs)

    @property
    def sum(self) -> FlatDict[str, float]:
        return FlatDict({key: meter.sum for key, meter in self.all_items()})

    @property
    def count(self) -> FlatDict[str, int]:
        return FlatDict({key: meter.count for key, meter in self.all_items()})

    def update(self, *args: Dict, **values: int | float) -> None:  # pylint: disable=W0237
        r"""
        Updates the average and current value in all meters.

        Args:
            values: Dict of values to be added to the average.
            n: Number of values to be added.

        Raises:
            ValueError: If the value is not an instance of (int, float).
        """  # noqa: E501

        if args:
            if len(args) > 1:
                raise ValueError("Expected only one positional argument, but got multiple.")
            values = args[0].update(values) or args[0] if values else args[0]

        for meter, value in values.items():
            if not isinstance(value, (int, float)):
                raise ValueError(f"Expected values to be int or float, but got {type(value)}")
            self[meter].update(value)

    def set(self, name: str, meter: AverageMeter) -> None:  # pylint: disable=W0237
        if not isinstance(meter, AverageMeter):
            raise ValueError(f"Expected meter to be an instance of AverageMeter, but got {type(meter)}")
        super().set(name, meter)

update

Python
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update(*args: Dict, **values: int | float) -> None

Updates the average and current value in all meters.

Parameters:

Name Type Description Default
values int | float

Dict of values to be added to the average.

 {}
n

Number of values to be added.

 required

Raises:

Type Description
ValueError

If the value is not an instance of (int, float).
Source code in danling/metrics/average_meter.py
Python
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def update(self, *args: Dict, **values: int | float) -> None:  # pylint: disable=W0237
    r"""
    Updates the average and current value in all meters.

    Args:
        values: Dict of values to be added to the average.
        n: Number of values to be added.

    Raises:
        ValueError: If the value is not an instance of (int, float).
    """  # noqa: E501

    if args:
        if len(args) > 1:
            raise ValueError("Expected only one positional argument, but got multiple.")
        values = args[0].update(values) or args[0] if values else args[0]

    for meter, value in values.items():
        if not isinstance(value, (int, float)):
            raise ValueError(f"Expected values to be int or float, but got {type(value)}")
        self[meter].update(value)

MultiTaskAverageMeters

Bases: MultiTaskDict

Manages multiple average meters in one object with multi-task support.

See Also

[AverageMeter]: Computes and stores the average and current value. [AverageMeters]: Manage multiple average meters in one object. [MetricMeters]: Manage multiple metric meters in one object.

Examples:

Python Console Session
>>> meters = MultiTaskAverageMeters()
>>> meters.update({"loss": 0.6, "dataset1.cls.auroc": 0.7, "dataset1.reg.r2": 0.8, "dataset2.r2": 0.9})
>>> f"{meters:.4f}"
'loss: 0.6000 (0.6000)\ndataset1.cls.auroc: 0.7000 (0.7000)\ndataset1.reg.r2: 0.8000 (0.8000)\ndataset2.r2: 0.9000 (0.9000)'
>>> meters['loss'].update(0.9, n=1)
>>> f"{meters:.4f}"
'loss: 0.9000 (0.7500)\ndataset1.cls.auroc: 0.7000 (0.7000)\ndataset1.reg.r2: 0.8000 (0.8000)\ndataset2.r2: 0.9000 (0.9000)'
>>> meters.sum.dict()
{'loss': 1.5, 'dataset1': {'cls': {'auroc': 0.7}, 'reg': {'r2': 0.8}}, 'dataset2': {'r2': 0.9}}
>>> meters.count.dict()
{'loss': 2, 'dataset1': {'cls': {'auroc': 1}, 'reg': {'r2': 1}}, 'dataset2': {'r2': 1}}
>>> meters.reset()
>>> f"{meters:.4f}"
'loss: 0.0000 (nan)\ndataset1.cls.auroc: 0.0000 (nan)\ndataset1.reg.r2: 0.0000 (nan)\ndataset2.r2: 0.0000 (nan)'
>>> meters = MultiTaskAverageMeters(return_average=True)
>>> meters.update({"loss": 0.6, "dataset1.a.auroc": 0.7, "dataset1.b.auroc": 0.8, "dataset2.auroc": 0.9})
>>> f"{meters:.4f}"
'loss: 0.6000 (0.6000)\ndataset1.a.auroc: 0.7000 (0.7000)\ndataset1.b.auroc: 0.8000 (0.8000)\ndataset2.auroc: 0.9000 (0.9000)'
>>> meters.update({"loss": 0.9, "dataset1.a.auroc": 0.8, "dataset1.b.auroc": 0.9, "dataset2.auroc": 1.0})
>>> f"{meters:.4f}"
'loss: 0.9000 (0.7500)\ndataset1.a.auroc: 0.8000 (0.7500)\ndataset1.b.auroc: 0.9000 (0.8500)\ndataset2.auroc: 1.0000 (0.9500)'
Source code in danling/metrics/average_meter.py
Python
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class MultiTaskAverageMeters(MultiTaskDict):
    r"""
    Manages multiple average meters in one object with multi-task support.

    See Also:
        [`AverageMeter`]: Computes and stores the average and current value.
        [`AverageMeters`]: Manage multiple average meters in one object.
        [`MetricMeters`]: Manage multiple metric meters in one object.

    Examples:
        >>> meters = MultiTaskAverageMeters()
        >>> meters.update({"loss": 0.6, "dataset1.cls.auroc": 0.7, "dataset1.reg.r2": 0.8, "dataset2.r2": 0.9})
        >>> f"{meters:.4f}"
        'loss: 0.6000 (0.6000)\ndataset1.cls.auroc: 0.7000 (0.7000)\ndataset1.reg.r2: 0.8000 (0.8000)\ndataset2.r2: 0.9000 (0.9000)'
        >>> meters['loss'].update(0.9, n=1)
        >>> f"{meters:.4f}"
        'loss: 0.9000 (0.7500)\ndataset1.cls.auroc: 0.7000 (0.7000)\ndataset1.reg.r2: 0.8000 (0.8000)\ndataset2.r2: 0.9000 (0.9000)'
        >>> meters.sum.dict()
        {'loss': 1.5, 'dataset1': {'cls': {'auroc': 0.7}, 'reg': {'r2': 0.8}}, 'dataset2': {'r2': 0.9}}
        >>> meters.count.dict()
        {'loss': 2, 'dataset1': {'cls': {'auroc': 1}, 'reg': {'r2': 1}}, 'dataset2': {'r2': 1}}
        >>> meters.reset()
        >>> f"{meters:.4f}"
        'loss: 0.0000 (nan)\ndataset1.cls.auroc: 0.0000 (nan)\ndataset1.reg.r2: 0.0000 (nan)\ndataset2.r2: 0.0000 (nan)'
        >>> meters = MultiTaskAverageMeters(return_average=True)
        >>> meters.update({"loss": 0.6, "dataset1.a.auroc": 0.7, "dataset1.b.auroc": 0.8, "dataset2.auroc": 0.9})
        >>> f"{meters:.4f}"
        'loss: 0.6000 (0.6000)\ndataset1.a.auroc: 0.7000 (0.7000)\ndataset1.b.auroc: 0.8000 (0.8000)\ndataset2.auroc: 0.9000 (0.9000)'
        >>> meters.update({"loss": 0.9, "dataset1.a.auroc": 0.8, "dataset1.b.auroc": 0.9, "dataset2.auroc": 1.0})
        >>> f"{meters:.4f}"
        'loss: 0.9000 (0.7500)\ndataset1.a.auroc: 0.8000 (0.7500)\ndataset1.b.auroc: 0.9000 (0.8500)\ndataset2.auroc: 1.0000 (0.9500)'
    """  # noqa: E501

    @property
    def sum(self) -> NestedDict[str, float]:
        return NestedDict({key: meter.sum for key, meter in self.all_items()})

    @property
    def count(self) -> NestedDict[str, int]:
        return NestedDict({key: meter.count for key, meter in self.all_items()})

    def update(self, *args: Dict, **values: float) -> None:  # pylint: disable=W0237
        r"""
        Updates the average and current value in all meters.

        Args:
            values: Dict of values to be added to the average.
            n: Number of values to be added.

        Raises:
            ValueError: If the value is not an instance of (int, float, Mapping).
        """  # noqa: E501

        if args:
            if len(args) > 1:
                raise ValueError("Expected only one positional argument, but got multiple.")
            values = args[0].update(values) or args[0] if values else args[0]

        for meter, value in values.items():
            if not isinstance(value, (int, float, Mapping)):
                raise ValueError(f"Expected values to be int, float, or a Mapping, but got {type(value)}")
            self[meter].update(value)

    # evil hack, as the default_factory must not be set to make `NestedDict` happy
    # this have some side effects, it will break attribute style intermediate nested dict auto creation
    # but everything has a price
    def get(self, name: Any, default=None) -> Any:
        if not name.startswith("_") and not name.endswith("_"):
            return self.setdefault(name, AverageMeter())
        return super().get(name, default)

    def set(self, name: str, meter: AverageMeter | AverageMeters) -> None:  # pylint: disable=W0237
        if not isinstance(meter, (AverageMeter, AverageMeters)):
            raise ValueError(
                f"Expected meter to be an instance of AverageMeter or AverageMeters, but got {type(meter)}"
            )
        super().set(name, meter)

update

Python
1
update(*args: Dict, **values: float) -> None

Updates the average and current value in all meters.

Parameters:

Name Type Description Default
values float

Dict of values to be added to the average.

 {}
n

Number of values to be added.

 required

Raises:

Type Description
ValueError

If the value is not an instance of (int, float, Mapping).
Source code in danling/metrics/average_meter.py
Python
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def update(self, *args: Dict, **values: float) -> None:  # pylint: disable=W0237
    r"""
    Updates the average and current value in all meters.

    Args:
        values: Dict of values to be added to the average.
        n: Number of values to be added.

    Raises:
        ValueError: If the value is not an instance of (int, float, Mapping).
    """  # noqa: E501

    if args:
        if len(args) > 1:
            raise ValueError("Expected only one positional argument, but got multiple.")
        values = args[0].update(values) or args[0] if values else args[0]

    for meter, value in values.items():
        if not isinstance(value, (int, float, Mapping)):
            raise ValueError(f"Expected values to be int, float, or a Mapping, but got {type(value)}")
        self[meter].update(value)