tf.keras.ops.multi_hot
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Encodes integer labels as multi-hot vectors.

Main aliases

tf.keras.ops.nn.multi_hot

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.

Args
`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.

Returns
`Tensor`	The multi-hot encoded tensor.

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)

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Last updated 2024-06-07 UTC.

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