`GridMask`

class```
keras_cv.layers.GridMask(
ratio_factor=(0, 0.5),
rotation_factor=0.15,
fill_mode="constant",
fill_value=0.0,
seed=None,
**kwargs
)
```

GridMask class for grid-mask augmentation.

**Input shape**

Int or float tensor with values in the range [0, 255].
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

**Arguments**

**ratio_factor**: A float, tuple of two floats, or`keras_cv.FactorSampler`

. Ratio determines the ratio from spacings to grid masks. Lower values make the grid size smaller, and higher values make the grid mask large. Floats should be in the range [0, 1]. 0.5 indicates that grid and spacing will be of equal size. To always use the same value, pass a`keras_cv.ConstantFactorSampler()`

.Defaults to

`(0, 0.5)`

. -**rotation_factor**: The rotation_factor will be used to randomly rotate the grid_mask during training. Default to 0.1, which results in an output rotating by a random amount in the range [-10% * 2pi, 10% * 2pi].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**: Pixels inside the gridblock are filled according to the given mode (one of`{"constant", "gaussian_noise"}`

). Default: "constant". -*constant*: Pixels are filled with the same constant value. -*gaussian_noise*: Pixels are filled with random gaussian noise. -**fill_value**: an integer represents of value to be filled inside the gridblock when`fill_mode="constant"`

. Valid integer range [0 to 255] -**seed**: Integer. Used to create a random seed.

Usage:

```
(images, labels), _ = tf.keras.datasets.cifar10.load_data()
random_gridmask = keras_cv.layers.preprocessing.GridMask()
augmented_images = random_gridmask(images)
```

**References**