Have a question? Connect with the community at the TensorFlow Forum

# tf.keras.metrics.Mean

Computes the (weighted) mean of the given values.

Inherits From: `Metric`, `Layer`, `Module`

### Used in the notebooks

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

This metric creates two variables, `total` and `count` that are used to compute the average of `values`. This average is ultimately returned as `mean` which is an idempotent operation that simply divides `total` by `count`.

If `sample_weight` is `None`, weights default to 1. Use `sample_weight` of 0 to mask values.

`name` (Optional) string name of the metric instance.
`dtype` (Optional) data type of the metric result.

#### Standalone usage:

````m = tf.keras.metrics.Mean()`
`m.update_state([1, 3, 5, 7])`
`m.result().numpy()`
`4.0`
`m.reset_state()`
`m.update_state([1, 3, 5, 7], sample_weight=[1, 1, 0, 0])`
`m.result().numpy()`
`2.0`
```

Usage with `compile()` API:

``````model.add_metric(tf.keras.metrics.Mean(name='mean_1')(outputs))
model.compile(optimizer='sgd', loss='mse')
``````

## Methods

### `reset_state`

View source

Resets all of the metric state variables.

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

### `result`

View source

Computes and returns the metric value tensor.

Result computation is an idempotent operation that simply calculates the metric value using the state variables.

### `update_state`

View source

Accumulates statistics for computing the metric.

Args
`values` Per-example value.
`sample_weight` Optional weighting of each example. Defaults to 1.

Returns
Update op.

[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]