<br />

|---|
| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/keras-team/keras/tree/v3.15.1/keras/src/metrics/reduction_metrics.py#L96-L158) |

Compute the (weighted) mean of the given values.

Inherits From: [`Metric`](https://www.tensorflow.org/api_docs/python/tf/keras/Metric)

    tf.keras.metrics.Mean(
        name='mean', dtype=None
    )

### Used in the notebooks

| Used in the guide | Used in the tutorials |
|---|---|
| - [Effective Tensorflow 2](https://www.tensorflow.org/guide/effective_tf2) - [Mixed precision](https://www.tensorflow.org/guide/mixed_precision) - [Use TPUs](https://www.tensorflow.org/guide/tpu) | - [TensorFlow 2 quickstart for experts](https://www.tensorflow.org/tutorials/quickstart/advanced) - [Custom training: walkthrough](https://www.tensorflow.org/tutorials/customization/custom_training_walkthrough) - [Custom training with tf.distribute.Strategy](https://www.tensorflow.org/tutorials/distribute/custom_training) - [Convolutional Variational Autoencoder](https://www.tensorflow.org/tutorials/generative/cvae) - [Training with Orbit](https://www.tensorflow.org/tfmodels/orbit/index) |

For example, if values is `[1, 3, 5, 7]` then the mean is 4.
If `sample_weight` was specified as `[1, 1, 0, 0]` then the mean would be 2.

This metric creates two variables, `total` and `count`.
The mean value returned is simply `total` divided by `count`.

<br />

<br />

<br />

| ## Args ||
|---|---|
| `name` | (Optional) string name of the metric instance. |
| `dtype` | (Optional) data type of the metric result. |

<br />

#### Example:

    m = Mean()
    m.update_state([1, 3, 5, 7])
    m.result()
    4.0

    m.reset_state()
    m.update_state([1, 3, 5, 7], sample_weight=[1, 1, 0, 0])
    m.result()
    2.0

<br />

<br />

<br />

| ## Attributes ||
|---|---|
| `dtype` | <br /> <br /> |
| `variables` | <br /> <br /> |

<br />

## Methods

### `add_variable`

[View source](https://github.com/keras-team/keras/tree/v3.15.1/keras/src/metrics/metric.py#L192-L209)

    add_variable(
        shape, initializer, dtype=None, aggregation='sum', name=None
    )

### `add_weight`

[View source](https://github.com/keras-team/keras/tree/v3.15.1/keras/src/metrics/metric.py#L211-L215)

    add_weight(
        shape=(), initializer=None, dtype=None, name=None
    )

### `from_config`

[View source](https://github.com/keras-team/keras/tree/v3.15.1/keras/src/metrics/metric.py#L233-L235)

    @classmethod
    from_config(
        config
    )

### `get_config`

[View source](https://github.com/keras-team/keras/tree/v3.15.1/keras/src/metrics/metric.py#L229-L231)

    get_config()

Return the serializable config of the metric.

### `reset_state`

[View source](https://github.com/keras-team/keras/tree/v3.15.1/keras/src/metrics/reduction_metrics.py#L151-L153)

    reset_state()

Reset all of the metric state variables.

This function is called between epochs/steps,
when a metric is evaluated during training.

### `result`

[View source](https://github.com/keras-team/keras/tree/v3.15.1/keras/src/metrics/reduction_metrics.py#L155-L158)

    result()

Compute the current metric value.

<br />

<br />

<br />

| Returns ||
|---|---|
| A scalar tensor, or a dictionary of scalar tensors. ||

<br />

### `stateless_reset_state`

[View source](https://github.com/keras-team/keras/tree/v3.15.1/keras/src/metrics/metric.py#L170-L183)

    stateless_reset_state()

### `stateless_result`

[View source](https://github.com/keras-team/keras/tree/v3.15.1/keras/src/metrics/metric.py#L154-L168)

    stateless_result(
        metric_variables
    )

### `stateless_update_state`

[View source](https://github.com/keras-team/keras/tree/v3.15.1/keras/src/metrics/metric.py#L121-L144)

    stateless_update_state(
        metric_variables, *args, **kwargs
    )

### `update_state`

[View source](https://github.com/keras-team/keras/tree/v3.15.1/keras/src/metrics/reduction_metrics.py#L138-L149)

    update_state(
        values, sample_weight=None
    )

Accumulate statistics for the metric.

### `__call__`

[View source](https://github.com/keras-team/keras/tree/v3.15.1/keras/src/metrics/metric.py#L224-L227)

    __call__(
        *args, **kwargs
    )

Call self as a function.