tf.keras.ops.one_hot

Converts integer tensor x into a one-hot tensor.

tf.keras.ops.one_hot(
    x, num_classes, axis=-1, dtype=None, sparse=False
)

The one-hot encoding is a representation where each integer value is converted into a binary vector with a length equal to num_classes, and the index corresponding to the integer value is marked as 1, while all other indices are marked as 0.

x Integer tensor to be encoded. The shape can be arbitrary, but the dtype should be integer.
num_classes Number of classes for the one-hot encoding.
axis Axis along which the encoding is performed. Defaults to -1, which represents the last axis.
dtype (Optional) Data type of the output tensor. If not provided, it defaults to the default data type of the backend.
sparse Whether to return a sparse tensor; for backends that support sparse tensors.

Integer tensor: One-hot encoded tensor with the same shape as x except for the specified axis dimension, which will have a length of num_classes. The dtype of the output tensor is determined by dtype or the default data type of the backend.

Example:

x = keras.ops.convert_to_tensor([1, 3, 2, 0])
one_hot(x, num_classes=4)
array([[0. 1. 0. 0.]
       [0. 0. 0. 1.]
       [0. 0. 1. 0.]
       [1. 0. 0. 0.]], shape=(4, 4), dtype=float32)