tf.keras.layers.ZeroPadding1D | TensorFlow v2.16.1 (original) (raw)
Zero-padding layer for 1D input (e.g. temporal sequence).
Inherits From: Layer, Operation
tf.keras.layers.ZeroPadding1D(
padding=1, **kwargs
)
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.ZeroPadding1D(padding=2)(x)
y
[[[ 0 0 0]
[ 0 0 0]
[ 0 1 2]
[ 3 4 5]
[ 0 0 0]
[ 0 0 0]]
[[ 0 0 0]
[ 0 0 0]
[ 6 7 8]
[ 9 10 11]
[ 0 0 0]
[ 0 0 0]]]
| Args | |
|---|---|
| padding | Int, or tuple of int (length 2), or dictionary. If int: how many zeros to add at the beginning and end of the padding dimension (axis 1). If tuple of 2 ints: how many zeros to add at the beginning and the end of the padding dimension ((left_pad, right_pad)). |
| Input shape |
|---|
| 3D tensor with shape (batch_size, axis_to_pad, features) |
| Output shape |
|---|
| 3D tensor with shape (batch_size, padded_axis, 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
@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
)