[BUG] np.ndarray of bfloat16 using ml_dtypes is being interpreted as complex64

[lkarthee]

Describe the bug

np.ndarray of bfloat16 using ml_dtypes is being interpreted as complex64 by mlx.

To Reproduce

>>> from ml_dtypes import bfloat16
>>> import numpy as np
>>> x = np.array(1., dtype=bfloat16)
>>> import mlx.core as mx
>>> mx.array(x)
array(1+0j, dtype=complex64)
>>> x = np.array(1)
>>> mx.array(x)
array(1, dtype=int64)
>>> x = np.array(1., dtype=bfloat16)
>>> x.dtype
dtype(bfloat16)
>>> type(x.dtype)
<class 'numpy.dtype[bfloat16]'>
>>>

Expected behavior
Conversion to complex should not happen. Should remain as bfloat16

Desktop (please complete the following information):

• OS Version: [e.g. MacOS 14.1.2] MacOS 14.1.1
• Version [e.g. 0.7.0] 0.11

Additional context
Originally posted by @lkarthee in #1066 (comment)