|  View source on GitHub | 
A preprocessing layer which randomly flips images during training.
Inherits From: Layer, Operation
tf.keras.layers.RandomFlip(
    mode=HORIZONTAL_AND_VERTICAL, seed=None, **kwargs
)
Used in the notebooks
| Used in the guide | Used in the tutorials | 
|---|---|
This layer will flip the images horizontally and or vertically based on the
mode attribute. During inference time, the output will be identical to
input. Call the layer with training=True to flip the input.
Input pixel values can be of any range (e.g. [0., 1.) or [0, 255]) and
of integer or floating point dtype.
By default, the layer will output floats.
| Input shape | |
|---|---|
| 3D | unbatched) or 4D (batched) tensor with shape
 | 
| Output shape | |
|---|---|
| 3D | unbatched) or 4D (batched) tensor with shape
 | 
Methods
from_config
@classmethodfrom_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
)