tf.keras.ops.multi_hot

Encodes integer labels as multi-hot vectors.

tf.keras.ops.multi_hot(
    inputs, num_classes=None, axis=-1, dtype=None, sparse=False, **kwargs
)

This function encodes integer labels as multi-hot vectors, where each label is mapped to a binary value in the resulting vector.

inputs Tensor of integer labels to be converted to multi-hot vectors.
num_classes Integer, the total number of unique classes.
axis (optional) Axis along which the multi-hot encoding should be added. Defaults to -1, which corresponds to the last dimension.
dtype (optional) The data type of the resulting tensor. Default is backend's float type.
sparse Whether to return a sparse tensor; for backends that support sparse tensors.

Tensor The multi-hot encoded tensor.

Example:

data = keras.ops.convert_to_tensor([0, 4])
keras.ops.multi_hot(data, num_classes=5)
array([1.0, 0.0, 0.0, 0.0, 1.0], dtype=float32)