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jax.nn.one_hot

jax.nn.one_hot(x, num_classes, *, dtype=<class 'jax._src.numpy.lax_numpy.float64'>)[source]

One-hot encodes the given indicies.

Each index in the input x is encoded as a vector of zeros of length num_classes with the element at index set to one:

>>> jax.nn.one_hot(jnp.array([0, 1, 2]), 3)
DeviceArray([[1., 0., 0.],

[0., 1., 0.], [0., 0., 1.]], dtype=float32)

Indicies outside the range [0, num_classes) will be encoded as zeros:

>>> jax.nn.one_hot(jnp.array([-1, 3]), 3)
DeviceArray([[0., 0., 0.],

[0., 0., 0.]], dtype=float32)

Parameters

  • x – A tensor of indices.

  • num_classes – Number of classes in the one-hot dimension.

  • dtype – optional, a float dtype for the returned values (default float64 if jax_enable_x64 is true, otherwise float32).