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# tf.keras.metrics.Accuracy

Calculates how often predictions equal labels.

### Used in the notebooks

Used in the guide Used in the tutorials

This metric creates two local variables, `total` and `count` that are used to compute the frequency with which `y_pred` matches `y_true`. This frequency is ultimately returned as `binary accuracy`: 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.Accuracy()`
`m.update_state([[1], [2], [3], [4]], [[0], [2], [3], [4]])`
`m.result().numpy()`
`0.75`
```
````m.reset_state()`
`m.update_state([[1], [2], [3], [4]], [[0], [2], [3], [4]],`
`               sample_weight=[1, 1, 0, 0])`
`m.result().numpy()`
`0.5`
```

Usage with `compile()` API:

``````model.compile(optimizer='sgd',
loss='mse',
metrics=[tf.keras.metrics.Accuracy()])
``````

## Methods

### `merge_state`

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Merges the state from one or more metrics.

This method can be used by distributed systems to merge the state computed by different metric instances. Typically the state will be stored in the form of the metric's weights. For example, a tf.keras.metrics.Mean metric contains a list of two weight values: a total and a count. If there were two instances of a tf.keras.metrics.Accuracy that each independently aggregated partial state for an overall accuracy calculation, these two metric's states could be combined as follows:

````m1 = tf.keras.metrics.Accuracy()`
`_ = m1.update_state([[1], [2]], [[0], [2]])`
```
````m2 = tf.keras.metrics.Accuracy()`
`_ = m2.update_state([[3], [4]], [[3], [4]])`
```
````m2.merge_state([m1])`
`m2.result().numpy()`
`0.75`
```

Args
`metrics` an iterable of metrics. The metrics must have compatible state.

Raises
`ValueError` If the provided iterable does not contain metrics matching the metric's required specifications.

View source