<br />

|---|
| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/model-analysis/blob/v0.46.0/tensorflow_model_analysis/metrics/metric_types.py#L794-L888) |

Metric wraps a set of metric computations.

    tfma.metrics.Metric(
        create_computations_fn: Callable[..., https://www.tensorflow.org/tfx/model_analysis/api_docs/python/tfma/metrics/MetricComputations],
        **kwargs
    )

This class exists to provide similarity between tfma.metrics.Metric and
tf.keras.metics.Metric.

Calling computations creates the metric computations. The parameters passed to
**init** will be combined with the parameters passed to the computations
method. This allows some of the parameters (e.g. model_names, output_names,
sub_keys) to be set at the time the computations are created instead of when
the metric is defined.

<br />

<br />

<br />

| ## Args ||
|---|---|
| `create_computations_fn` | Function to create the metrics computations (e.g. mean_label, etc). This function should take the args passed to **init** as as input along with any of eval_config, schema, model_names, output_names, sub_keys, aggregation_type, or query_key (where needed). |
| `**kwargs` | Any additional kwargs to pass to create_computations_fn. These should only contain primitive types or lists/dicts of primitive types. The kwargs passed to computations have precendence over these kwargs. |

<br />

<br />

<br />

<br />

| ## Attributes ||
|---|---|
| `compute_confidence_interval` | Whether to compute confidence intervals for this metric. <br /> Note that this may not completely remove the computational overhead involved in computing a given metric. This is only respected by the jackknife confidence interval method. |

<br />

## Methods

### `computations`

[View source](https://github.com/tensorflow/model-analysis/blob/v0.46.0/tensorflow_model_analysis/metrics/metric_types.py#L862-L888)

    computations(
        eval_config: Optional[https://www.tensorflow.org/tfx/model_analysis/api_docs/python/tfma/EvalConfig] = None,
        schema: Optional[schema_pb2.Schema] = None,
        model_names: Optional[List[str]] = None,
        output_names: Optional[List[str]] = None,
        sub_keys: Optional[List[Optional[SubKey]]] = None,
        aggregation_type: Optional[AggregationType] = None,
        class_weights: Optional[Dict[int, float]] = None,
        example_weighted: bool = False,
        query_key: Optional[str] = None
    ) -> https://www.tensorflow.org/tfx/model_analysis/api_docs/python/tfma/metrics/MetricComputations

Creates computations associated with metric.

### `from_config`

[View source](https://github.com/tensorflow/model-analysis/blob/v0.46.0/tensorflow_model_analysis/metrics/metric_types.py#L842-L847)

    @classmethod
    from_config(
        config: Dict[str, Any]
    ) -> 'Metric'

### `get_config`

[View source](https://github.com/tensorflow/model-analysis/blob/v0.46.0/tensorflow_model_analysis/metrics/metric_types.py#L838-L840)

    get_config() -> Dict[str, Any]

Returns serializable config.