tf.keras.ops.one_hot | TensorFlow v2.16.1 (original) (raw)
tf.keras.ops.one_hot
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Converts integer tensor x into a one-hot tensor.
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Main aliases
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.
| Args | |
|---|---|
| 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. |
| Returns |
|---|
| Integer tensor: One-hot encoded tensor with the same shape as xexcept 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)
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Last updated 2024-06-07 UTC.