tf.keras.layers.ZeroPadding2D | TensorFlow v2.0.0 (original) (raw)

tf.keras.layers.ZeroPadding2D

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Zero-padding layer for 2D input (e.g. picture).

Inherits From: Layer

View aliases

Compat aliases for migration

tf.compat.v1.keras.layers.ZeroPadding2D

tf.keras.layers.ZeroPadding2D(
    padding=(1, 1), data_format=None, **kwargs
)

This layer can add rows and columns of zeros at the top, bottom, left and right side of an image tensor.

Arguments
padding	Int, or tuple of 2 ints, or tuple of 2 tuples of 2 ints. If int: the same symmetric padding is applied to height and width. If tuple of 2 ints: interpreted as two different symmetric padding values for height and width:(symmetric_height_pad, symmetric_width_pad). If tuple of 2 tuples of 2 ints: interpreted as((top_pad, bottom_pad), (left_pad, right_pad))
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".

Arguments

padding

Int, or tuple of 2 ints, or tuple of 2 tuples of 2 ints. If int: the same symmetric padding is applied to height and width. If tuple of 2 ints: interpreted as two different symmetric padding values for height and width:(symmetric_height_pad, symmetric_width_pad). If tuple of 2 tuples of 2 ints: interpreted as((top_pad, bottom_pad), (left_pad, right_pad))

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".

Input shape:

4D tensor with shape:

If data_format is "channels_last":(batch, rows, cols, channels)
If data_format is "channels_first":(batch, channels, rows, cols)

Output shape:

4D tensor with shape:

If data_format is "channels_last":(batch, padded_rows, padded_cols, channels)
If data_format is "channels_first":(batch, channels, padded_rows, padded_cols)

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Last updated 2020-10-01 UTC.