TensorFlow 2 version | View source on GitHub |
Upsampling layer for 3D inputs.
Inherits From: Layer
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.
Arguments | |
---|---|
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, spatial_dim1, spatial_dim2, spatial_dim3, channels)
while channels_first corresponds to inputs with shape
(batch, channels, spatial_dim1, spatial_dim2, spatial_dim3) .
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:
5D tensor with shape:
- If
data_format
is"channels_last"
:(batch, dim1, dim2, dim3, channels)
- If
data_format
is"channels_first"
:(batch, channels, dim1, dim2, dim3)
Output shape:
5D tensor with shape:
- If
data_format
is"channels_last"
:(batch, upsampled_dim1, upsampled_dim2, upsampled_dim3, channels)
- If
data_format
is"channels_first"
:(batch, channels, upsampled_dim1, upsampled_dim2, upsampled_dim3)