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.
|
|
3D tensor with shape: (batch_size, steps, features).
|
Output shape |
3D tensor with shape: (batch_size, upsampled_steps, features).
|
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 an operation from its config.
This method is the reverse of get_config, capable of instantiating the
same operation from the config dictionary.
if "dtype" in config and isinstance(config["dtype"], dict):
policy = dtype_policies.deserialize(config["dtype"])
| Args |
config
|
A Python dictionary, typically the output of get_config.
|
| Returns |
|
An operation instance.
|