# tf.keras.layers.MaxPool1D

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|---|---|
| [![](https://www.tensorflow.org/images/tf_logo_32px.png) TensorFlow 1 version](https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/keras/layers/MaxPool1D) | [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.0.0/tensorflow/python/keras/layers/pooling.py#L112-L151) |

Max pooling operation for temporal data.

#### View aliases


**Main aliases**

[`tf.keras.layers.MaxPooling1D`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/MaxPool1D)
**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.keras.layers.MaxPool1D`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/MaxPool1D), [`tf.compat.v1.keras.layers.MaxPooling1D`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/MaxPool1D)

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    tf.keras.layers.MaxPool1D(
        pool_size=2, strides=None, padding='valid', data_format='channels_last',
        **kwargs
    )

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| ## Arguments ||
|---|---|
| `pool_size` | Integer, size of the max pooling windows. |
| `strides` | Integer, or None. Factor by which to downscale. E.g. 2 will halve the input. If None, it will default to `pool_size`. |
| `padding` | One of `"valid"` or `"same"` (case-insensitive). |
| `data_format` | A string, one of `channels_last` (default) or `channels_first`. The ordering of the dimensions in the inputs. `channels_last` corresponds to inputs with shape `(batch, steps, features)` while `channels_first` corresponds to inputs with shape `(batch, features, steps)`. |

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#### Input shape:

- If `data_format='channels_last'`: 3D tensor with shape `(batch_size, steps, features)`.
- If `data_format='channels_first'`: 3D tensor with shape `(batch_size, features, steps)`.

#### Output shape:

- If `data_format='channels_last'`: 3D tensor with shape `(batch_size, downsampled_steps, features)`.
- If `data_format='channels_first'`: 3D tensor with shape `(batch_size, features, downsampled_steps)`.