`np.testing.assert_array_equal()` not compatible with bfloat16 when the value is `nan`

[ayaka14732]

import numpy as np
import jax.numpy as jnp

a = jnp.array([jnp.nan], dtype=jnp.float32)
np.testing.assert_array_equal(a, a)  # No error

a = jnp.array([jnp.nan], dtype=jnp.bfloat16)
np.testing.assert_array_equal(a, a)  # AssertionError

The cause is that np.testing.assert_array_equal() does not recognise bfloat16 as a "number" type: https://github.com/numpy/numpy/blob/b3ddf2fd33232b8939f48c7c68a61c10257cd0c5/numpy/testing/_private/utils.py#L773

[jakevdp]

This is one of the many examples you can probably find of where NumPy hard-codes logic about its built-in set of dtypes. There's nothing that downstream dtype implementations like ml_dtypes can do to change this. We might think about raising this issue upstream in the NumPy package.