description: Global max pooling operation for spatial data.

tf.keras.layers.GlobalMaxPool2D

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Global max pooling operation for spatial data.

Inherits From: Layer, Module

View aliases

Main aliases

tf.keras.layers.GlobalMaxPooling2D

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.layers.GlobalMaxPool2D, tf.compat.v1.keras.layers.GlobalMaxPooling2D

tf.keras.layers.GlobalMaxPool2D(
    data_format=None, **kwargs
)

Examples:

>>> input_shape = (2, 4, 5, 3)
>>> x = tf.random.normal(input_shape)
>>> y = tf.keras.layers.GlobalMaxPool2D()(x)
>>> print(y.shape)
(2, 3)

Arguments
`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, height, width, channels)` while `channels_first` corresponds to inputs with shape `(batch, channels, height, width)`. It defaults to the `image_data_format` value found in your Keras config file at `~/.keras/keras.json`. If you never set it, then it will be "channels_last".

Arguments

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, height, width, channels) while channels_first corresponds to inputs with shape (batch, channels, height, width). It defaults to the image_data_format value found in your Keras config file at ~/.keras/keras.json. If you never set it, then it will be "channels_last".

Input shape:

If data_format='channels_last': 4D tensor with shape (batch_size, rows, cols, channels).
If data_format='channels_first': 4D tensor with shape (batch_size, channels, rows, cols).

Output shape:

2D tensor with shape (batch_size, channels).