one_hot#

ray.rllib.utils.numpy.one_hot(x: NDArray[Any] | jnp.ndarray | tf.Tensor | torch.Tensor | int, depth: int = 0, on_value: float = 1.0, off_value: float = 0.0, dtype: type = <class 'numpy.float32'>) → ndarray[source]#

One-hot utility function for numpy.

Thanks to qianyizhang: https://gist.github.com/qianyizhang/07ee1c15cad08afb03f5de69349efc30.

Parameters:

x (NDArray[Any] | jnp.ndarray | tf.Tensor | torch.Tensor | int) – The input to be one-hot encoded.
depth (int) – The max. number to be one-hot encoded (size of last rank).
on_value (float) – The value to use for on. Default: 1.0.
off_value (float) – The value to use for off. Default: 0.0.

Returns:

The one-hot encoded equivalent of the input array.

Return type:

ndarray