View source on GitHub |
Upsampling layer for 1D inputs.
Inherits From: Layer
, Operation
tf.keras.layers.UpSampling1D(
size=2, **kwargs
)
Repeats each temporal step size
times along the time axis.
Example:
input_shape = (2, 2, 3)
x = np.arange(np.prod(input_shape)).reshape(input_shape)
x
[[[ 0 1 2]
[ 3 4 5]]
[[ 6 7 8]
[ 9 10 11]]]
y = keras.layers.UpSampling1D(size=2)(x)
y
[[[ 0. 1. 2.]
[ 0. 1. 2.]
[ 3. 4. 5.]
[ 3. 4. 5.]]
[[ 6. 7. 8.] [ 6. 7. 8.] [ 9. 10. 11.] [ 9. 10. 11.]]]
Args | |
---|---|
size
|
Integer. Upsampling factor. |
Input shape | |
---|---|
3D tensor with shape: (batch_size, steps, features) .
|
Output shape | |
---|---|
3D tensor with shape: (batch_size, upsampled_steps, features) .
|
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
)