tf.keras.layers.MaxPool2D | TensorFlow v2.0.0 (original) (raw)

tf.keras.layers.MaxPool2D

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Max pooling operation for spatial data.

Main aliases

tf.keras.layers.MaxPooling2D

Compat aliases for migration

SeeMigration guide for more details.

tf.keras.layers.MaxPool2D(
    pool_size=(2, 2), strides=None, padding='valid', data_format=None, **kwargs
)

Arguments
pool_size	integer or tuple of 2 integers, factors by which to downscale (vertical, horizontal).(2, 2) will halve the input in both spatial dimension. If only one integer is specified, the same window length will be used for both dimensions.
strides	Integer, tuple of 2 integers, or None. Strides values. 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, height, width, channels) while channels_firstcorresponds 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".

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).

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

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Last updated 2020-10-01 UTC.