orbit.actions.NewBestMetric

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Condition that is satisfied when a new best metric is achieved.

orbit.actions.NewBestMetric(
    metric: Union[str, MetricFn],
    higher_is_better: bool = True,
    filename: Optional[str] = None,
    write_metric=True
)

This class keeps track of the best metric value seen so far, optionally in a persistent (preemption-safe) way.

Two methods are provided, which each satisfy the Action protocol: test for only testing whether a new best metric is achieved by a given train/eval output, and commit, which both tests and records the new best metric value if it is achieved. These separate methods enable the same NewBestMetric instance to be reused as a condition multiple times, and can also provide additional preemption/failure safety. For example, to avoid updating the best metric if a model export fails or is pre-empted:

new_best_metric = orbit.actions.NewBestMetric(
  'accuracy', filename='/model/dir/best_metric')
action = orbit.actions.ConditionalAction(
    condition=new_best_metric.test,
    action=[
      orbit.actions.ExportSavedModel(...),
      new_best_metric.commit
    ])

The default __call__ implementation is equivalent to commit.

This class is safe to use in multi-client settings if all clients can be guaranteed to compute the same metric. However when saving metrics it may be helpful to avoid unnecessary writes by setting the write_value parameter to False for most clients.

Args
metric	Either a string key name to use to look up a metric (assuming the train/eval output is a dictionary), or a callable that accepts the train/eval output and returns a metric value.
higher_is_better	Whether higher metric values are better. If True, a new best metric is achieved when the metric value is strictly greater than the previous best metric. If False, a new best metric is achieved when the metric value is strictly less than the previous best metric.
filename	A filename to use for storage of the best metric value seen so far, to allow peristence of the value across preemptions. If None (default), values aren't persisted.
write_metric	If filename is set, this controls whether this instance will write new best metric values to the file, or just read from the file to obtain the initial value. Setting this to False for most clients in some multi-client setups can avoid unnecessary file writes. Has no effect if filename is None.

Attributes
metric	The metric passed to init (may be a string key or a callable that can be applied to train/eval output).
higher_is_better	Whether higher metric values are better.
best_value	Returns the best metric value seen so far.

Methods

commit

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commit(
    output: runner.Output
) -> bool

Tests output and updates the current best value if necessary.

Unlike test above, if output does contain a new best metric value, this method does save it (i.e., subsequent calls to this method with the same output will return False).

Args
output	The train or eval output to test.

Returns
True if output contains a new best metric value, False otherwise.

metric_value

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metric_value(
    output: runner.Output
) -> float

Computes the metric value for the given output.

test

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test(
    output: runner.Output
) -> bool

Tests output to see if it contains a new best metric value.

If output does contain a new best metric value, this method does not save it (i.e., calling this method multiple times in a row with the same output will continue to return True).

Args
output	The train or eval output to test.

Returns
True if output contains a new best metric value, False otherwise.

__call__

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__call__(
    output: runner.Output
) -> bool

Tests output and updates the current best value if necessary.

This is equivalent to commit below.

Args
output	The train or eval output to test.

Returns
True if output contains a new best metric value, False otherwise.