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# tf.keras.layers.RandomRotation

A preprocessing layer which randomly rotates images during training.

Inherits From: `Layer`, `Module`

### Used in the notebooks

Used in the guide Used in the tutorials

This layer will apply random rotations to each image, filling empty space according to `fill_mode`.

By default, random rotations are only applied during training. At inference time, the layer does nothing. If you need to apply random rotations at inference time, set `training` to True when calling the layer.

For an overview and full list of preprocessing layers, see the preprocessing guide.

#### Input shape:

3D (unbatched) or 4D (batched) tensor with shape: `(..., height, width, channels)`, in `"channels_last"` format

#### Output shape:

3D (unbatched) or 4D (batched) tensor with shape: `(..., height, width, channels)`, in `"channels_last"` format

`factor` a float represented as fraction of 2 Pi, or a tuple of size 2 representing lower and upper bound for rotating clockwise and counter-clockwise. A positive values means rotating counter clock-wise, while a negative value means clock-wise. When represented as a single float, this value is used for both the upper and lower bound. For instance, `factor=(-0.2, 0.3)` results in an output rotation by a random amount in the range `[-20% * 2pi, 30% * 2pi]`. `factor=0.2` results in an output rotating by a random amount in the range `[-20% * 2pi, 20% * 2pi]`.
`fill_mode` Points outside the boundaries of the input are filled according to the given mode (one of `{"constant", "reflect", "wrap", "nearest"}`).

• reflect: `(d c b a | a b c d | d c b a)` The input is extended by reflecting about the edge of the last pixel.
• constant: `(k k k k | a b c d | k k k k)` The input is extended by filling all values beyond the edge with the same constant value k = 0.
• wrap: `(a b c d | a b c d | a b c d)` The input is extended by wrapping around to the opposite edge.
• nearest: `(a a a a | a b c d | d d d d)` The input is extended by the nearest pixel.
`interpolation` Interpolation mode. Supported values: `"nearest"`, `"bilinear"`.
`seed` Integer. Used to create a random seed.
`fill_value` a float represents the value to be filled outside the boundaries when `fill_mode="constant"`.
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