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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/keras-team/keras/tree/v2.15.0/keras/preprocessing/image.py#L2259-L2300) |

Performs a random spatial shear of a Numpy image tensor.

    tf.keras.preprocessing.image.random_shear(
        x,
        intensity,
        row_axis=1,
        col_axis=2,
        channel_axis=0,
        fill_mode='nearest',
        cval=0.0,
        interpolation_order=1
    )

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| ## Args ||
|---|---|
| `x` | Input tensor. Must be 3D. |
| `intensity` | Transformation intensity in degrees. |
| `row_axis` | Index of axis for rows in the input tensor. |
| `col_axis` | Index of axis for columns in the input tensor. |
| `channel_axis` | Index of axis for channels in the input tensor. |
| `fill_mode` | Points outside the boundaries of the input are filled according to the given mode (one of `{'constant', 'nearest', 'reflect', 'wrap'}`). |
| `cval` | Value used for points outside the boundaries of the input if `mode='constant'`. |
| `interpolation_order` | int, order of spline interpolation. see `ndimage.interpolation.affine_transform` |

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| ## Returns ||
|---|---|
| Sheared Numpy image tensor. ||

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