# tf.keras.datasets.cifar10.load_data

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/keras-team/keras/tree/v2.13.1/keras/datasets/cifar10.py#L29-L115) |

Loads the CIFAR10 dataset.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

\`tf.compat.v1.keras.datasets.cifar10.load_data\`

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    tf.keras.datasets.cifar10.load_data()

This is a dataset of 50,000 32x32 color training images and 10,000 test
images, labeled over 10 categories. See more info at the
[CIFAR homepage](https://www.cs.toronto.edu/%7Ekriz/cifar.html).

#### The classes are:

| Label | Description |
|---|---|
| 0 | airplane |
| 1 | automobile |
| 2 | bird |
| 3 | cat |
| 4 | deer |
| 5 | dog |
| 6 | frog |
| 7 | horse |
| 8 | ship |
| 9 | truck |

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| ## Returns ||
|---|---|
| Tuple of NumPy arrays: `(x_train, y_train), (x_test, y_test)`. ||

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**x_train** : uint8 NumPy array of grayscale image data with shapes
`(50000, 32, 32, 3)`, containing the training data. Pixel values range
from 0 to 255.

**y_train** : uint8 NumPy array of labels (integers in range 0-9)
with shape `(50000, 1)` for the training data.

**x_test** : uint8 NumPy array of grayscale image data with shapes
`(10000, 32, 32, 3)`, containing the test data. Pixel values range
from 0 to 255.

**y_test** : uint8 NumPy array of labels (integers in range 0-9)
with shape `(10000, 1)` for the test data.

#### Example:

    (x_train, y_train), (x_test, y_test) = keras.datasets.cifar10.load_data()
    assert x_train.shape == (50000, 32, 32, 3)
    assert x_test.shape == (10000, 32, 32, 3)
    assert y_train.shape == (50000, 1)
    assert y_test.shape == (10000, 1)