UpSampling3D
classkeras.layers.UpSampling3D(size=(2, 2, 2), data_format=None, **kwargs)
Upsampling layer for 3D inputs.
Repeats the 1st, 2nd and 3rd dimensions
of the data by size[0]
, size[1]
and size[2]
respectively.
Example
>>> input_shape = (2, 1, 2, 1, 3)
>>> x = np.ones(input_shape)
>>> y = keras.layers.UpSampling3D(size=(2, 2, 2))(x)
>>> y.shape
(2, 2, 4, 2, 3)
Arguments
"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)
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)