tf.keras.metrics.MeanMetricWrapper | TensorFlow v2.16.1 (original) (raw)
tf.keras.metrics.MeanMetricWrapper
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Wrap a stateless metric function with the Mean metric.
tf.keras.metrics.MeanMetricWrapper(
fn, name=None, dtype=None, **kwargs
)
You could use this class to quickly build a mean metric from a function. The function needs to have the signature fn(y_true, y_pred) and return a per-sample loss array. MeanMetricWrapper.result() will return the average metric value across all samples seen so far.
For example:
def mse(y_true, y_pred):
return (y_true - y_pred) ** 2
mse_metric = MeanMetricWrapper(fn=mse)
| Args | |
|---|---|
| fn | The metric function to wrap, with signaturefn(y_true, y_pred, **kwargs). |
| name | (Optional) string name of the metric instance. |
| dtype | (Optional) data type of the metric result. |
| **kwargs | Keyword arguments to pass on to fn. |
| Attributes | | | ---------- | | | dtype | | | variables | |
Methods
add_variable
add_variable(
shape, initializer, dtype=None, aggregation='sum', name=None
)
add_weight
add_weight(
shape=(), initializer=None, dtype=None, name=None
)
from_config
@classmethod
from_config( config )
get_config
get_config()
Return the serializable config of the metric.
reset_state
reset_state()
Reset all of the metric state variables.
This function is called between epochs/steps, when a metric is evaluated during training.
result
result()
Compute the current metric value.
| Returns |
|---|
| A scalar tensor, or a dictionary of scalar tensors. |
stateless_reset_state
stateless_reset_state()
stateless_result
stateless_result(
metric_variables
)
stateless_update_state
stateless_update_state(
metric_variables, *args, **kwargs
)
update_state
update_state(
y_true, y_pred, sample_weight=None
)
Accumulate statistics for the metric.
__call__
__call__(
*args, **kwargs
)
Call self as a function.