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Cropping layer for 1D input (e.g. temporal sequence).

Inherits From: Layer, Operation

tf.keras.layers.Cropping1D(
    cropping=(1, 1), **kwargs
)

It crops along the time dimension (axis 1).

Example:

input_shape = (2, 3, 2)
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.Cropping1D(cropping=1)(x)
y
[[[2 3]]
 [[8 9]]]

cropping Int, or tuple of int (length 2), or dictionary.

  • If int: how many units should be trimmed off at the beginning and end of the cropping dimension (axis 1).
  • If tuple of 2 ints: how many units should be trimmed off at the beginning and end of the cropping dimension ((left_crop, right_crop)).

3D tensor with shape (batch_size, axis_to_crop, features)

3D tensor with shape (batch_size, cropped_axis, features)

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

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@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

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symbolic_call(
    *args, **kwargs
)