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) ).
|
|
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
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
)