jax.numpy.argwhere(a, *, size=None, fill_value=None)[source]#

Find the indices of nonzero array elements

JAX implementation of numpy.argwhere().

jnp.argwhere(x) is essentially equivalent to jnp.column_stack(jnp.nonzero(x)) with special handling for zero-dimensional (i.e. scalar) inputs.

Because the size of the output of argwhere is data-dependent, the function is not typically compatible with JIT. The JAX version adds the optional size argument, which specifies the size of the leading dimension of the output - it must be specified statically for jnp.argwhere to be compiled with non-static operands. See jax.numpy.nonzero() for a full discussion of size and its semantics.

  • a (ArrayLike) – array for which to find nonzero elements

  • size (int | None) – optional integer specifying statically the number of expected nonzero elements. This must be specified in order to use argwhere within JAX transformations like jax.jit(). See jax.numpy.nonzero() for more information.

  • fill_value (ArrayLike | None) – optional array specifying the fill value when size is specified. See jax.numpy.nonzero() for more information.


a two-dimensional array of shape [size, x.ndim]. If size is not specified as an argument, it is equal to the number of nonzero elements in x.

Return type:



Two-dimensional array:

>>> x = jnp.array([[1, 0, 2],
...                [0, 3, 0]])
>>> jnp.argwhere(x)
Array([[0, 0],
       [0, 2],
       [1, 1]], dtype=int32)

Equivalent computation using jax.numpy.column_stack() and jax.numpy.nonzero():

>>> jnp.column_stack(jnp.nonzero(x))
Array([[0, 0],
       [0, 2],
       [1, 1]], dtype=int32)

Special case for zero-dimensional (i.e. scalar) inputs:

>>> jnp.argwhere(1)
Array([], shape=(1, 0), dtype=int32)
>>> jnp.argwhere(0)
Array([], shape=(0, 0), dtype=int32)