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tf.keras.layers.UpSampling1D

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)`.

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
)

© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/keras/layers/UpSampling1D