tf.keras.ops.multi_hot | TensorFlow v2.16.1 (original) (raw)
tf.keras.ops.multi_hot
Encodes integer labels as multi-hot vectors.
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Main aliases
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. |
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)
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Last updated 2024-06-07 UTC.