tf.keras.layers.UpSampling3D | TensorFlow v2.16.1 (original) (raw)
tf.keras.layers.UpSampling3D
Stay organized with collections Save and categorize content based on your preferences.
Upsampling layer for 3D inputs.
Inherits From: Layer, Operation
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.
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)
| 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, usesimage_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) |
| Attributes | |
|---|---|
| input | Retrieves the input tensor(s) of a symbolic operation.Only returns the tensor(s) corresponding to the _first time_the operation was called. |
| output | Retrieves the output tensor(s) of a layer.Only returns the tensor(s) corresponding to the _first time_the operation was called. |
Methods
from_config
@classmethod
from_config( config )
Creates a layer from its config.
This method is the reverse of get_config, capable of instantiating the same layer from the config dictionary. It does not handle layer connectivity (handled by Network), nor weights (handled by set_weights).
| Args | |
|---|---|
| config | A Python dictionary, typically the output of get_config. |
| Returns |
|---|
| A layer instance. |
symbolic_call
symbolic_call(
*args, **kwargs
)