ml-explore
[BUG] `Invalid type ndarray` for complex, non-contiguous `np.array` input to `mx.array`
Describe the bug
Cannot initialize mx.array from a complex, non-contiguous np.array, and the error message is confusing.
To Reproduce
import numpy as np
import mlx.core as mx
contiguous_array = np.random.rand(10, 10).astype(np.complex64)
# Make the array non-contiguous by transposing it
non_contiguous_array = contiguous_array.T
# Ensure the array is non-contiguous
assert not non_contiguous_array.flags["C_CONTIGUOUS"]
# Attempt to move the non-contiguous array to the GPU
gpu_array = mx.array(non_contiguous_array)
# Perform a simple operation just to check
result = mx.sum(gpu_array)
Expected behavior Expected to run without errors.
Actual error:
Traceback (most recent call last):
File ".../mlx_complex.py", line 14, in <module>
gpu_array = mx.array(non_contiguous_array)
ValueError: Invalid type ndarray received in array initialization.
Note: workarounds are:
- forcing the array to be contiguous with
np.ascontiguousarray, which works, but took me a while to figure out that this is a requirement - use real-valued array (okay in this toy example, but I am interested in using this for complex data)
Desktop (please complete the following information):
- OS Version: Sonoma 14.6.1 (23G93)
- Version: 0.16.3
❯ pip list | grep mlx
mlx 0.16.3
❯ pip list | grep numpy
numpy 1.26.4
Additional context Add any other context about the problem here.
This looks like a Nanobind issue. FIled here https://github.com/wjakob/nanobind/issues/709, let's see if it is something they can fix.
This is fixed in nanobind on the main branch. Since there is a work-around using ascontiguousarray I will wait until the next Nanobind release, then we can bump MLXs nanobind dependency and close this. The Nanobind release cycle is about 3 months so it could be a couple months before this is closed.
If it's more urgent we could always discuss versioning our own Nanobind on PyPi.. but I don't think it's merited just for this.