tf.keras.layers.UpSampling3D

Upsampling layer for 3D inputs.

Inherits From: Layer, Module

View aliases

Compat aliases for migration

`tf.compat.v1.keras.layers.UpSampling3D`

tf.keras.layers.UpSampling3D(
    size=(2, 2, 2), data_format=None, **kwargs
)

Repeats the 1st, 2nd and 3rd dimensions of the data by size[0], size[1] and size[2] respectively.

Examples:

input_shape = (2, 1, 2, 1, 3)
x = tf.constant(1, shape=input_shape)
y = tf.keras.layers.UpSampling3D(size=2)(x)
print(y.shape)
(2, 2, 4, 2, 3)

Args
`size`	Int, or tuple of 3 integers. The upsampling factors for dim1, dim2 and dim3.
`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_size, spatial_dim1, spatial_dim2, spatial_dim3, channels)` while `channels_first` corresponds to inputs with shape `(batch_size, channels, spatial_dim1, spatial_dim2, spatial_dim3)`. When unspecified, uses `image_data_format` value found in your Keras config file at `~/.keras/keras.json` (if exists) else 'channels_last'. Defaults to 'channels_last'.

Args

size Int, or tuple of 3 integers. The upsampling factors for dim1, dim2 and dim3.

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_size, spatial_dim1, spatial_dim2, spatial_dim3, channels) while channels_first corresponds to inputs with shape (batch_size, channels, spatial_dim1, spatial_dim2, spatial_dim3). When unspecified, uses image_data_format value found in your Keras config file at ~/.keras/keras.json (if exists) else 'channels_last'. Defaults to 'channels_last'.

Input shape
5D tensor with shape: If `data_format` is `"channels_last"`: `(batch_size, dim1, dim2, dim3, channels)` If `data_format` is `"channels_first"`: `(batch_size, channels, dim1, dim2, dim3)`

Input shape

5D tensor with shape:

If data_format is "channels_last": (batch_size, dim1, dim2, dim3, channels)
If data_format is "channels_first": (batch_size, channels, dim1, dim2, dim3)

Output shape
5D tensor with shape: If `data_format` is `"channels_last"`: `(batch_size, upsampled_dim1, upsampled_dim2, upsampled_dim3, channels)` If `data_format` is `"channels_first"`: `(batch_size, channels, upsampled_dim1, upsampled_dim2, upsampled_dim3)`

Output shape

5D tensor with shape:

If data_format is "channels_last": (batch_size, upsampled_dim1, upsampled_dim2, upsampled_dim3, channels)
If data_format is "channels_first": (batch_size, channels, upsampled_dim1, upsampled_dim2, upsampled_dim3)