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, uses
image_data_format value found in your Keras config file at
~/.keras/keras.json (if exists) else "channels_last" .
Defaults to "channels_last" .
|
|
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
View source
@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
View source
symbolic_call(
*args, **kwargs
)
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2024-06-07 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-06-07 UTC."],[],[]]