tf.compat.v1.layers.max_pooling1d

Max Pooling layer for 1D inputs.

tf.compat.v1.layers.max_pooling1d(
    inputs,
    pool_size,
    strides,
    padding='valid',
    data_format='channels_last',
    name=None
)

Migrate to TF2

This API is not compatible with eager execution or tf.function.

Please refer to tf.layers section of the migration guide to migrate a TensorFlow v1 model to Keras. The corresponding TensorFlow v2 layer is tf.keras.layers.MaxPooling1D.

None of the supported arguments have changed name.

Before:

 y = tf.compat.v1.layers.max_pooling1d(x, pool_size=2, strides=2)

After:

To migrate code using TF1 functional layers use the Keras Functional API:

 x = tf.keras.Input((28, 28, 1))
 y = tf.keras.layers.MaxPooling1D(pool_size=2, strides=2)(x)
 model = tf.keras.Model(x, y)

Args
`inputs`	The tensor over which to pool. Must have rank 3.
`pool_size`	An integer or tuple/list of a single integer, representing the size of the pooling window.
`strides`	An integer or tuple/list of a single integer, specifying the strides of the pooling operation.
`padding`	A string. The padding method, either '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, length, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, length)`.
`name`	A string, the name of the layer.

Returns
The output tensor, of rank 3.

Raises
`ValueError`	if eager execution is enabled.