strange astype casting behavior on MacOS x86_64

- [x] I read [the conda-forge documentation](https://conda-forge.org/docs/user/introduction.html#how-can-i-install-packages-from-conda-forge) and could not find the solution for my problem there.

We saw some strange test failures on x86_64 MacOS builds in https://github.com/conda-forge/scikit-image-feedstock/pull/85. There is apparently a NumPy issue completely unrelated to scikit-image that is causing these failures.

Consider the following example with an out-of-range float32 value being cast to uint8. On my linux system an array of float32 with value 485. becomes an array of 229's when converted to uint8 `(485 % 256 = 229)`.

However, with the conda-forge NumPy on MacOS I see different behavior depending on the data length (making me suspect this is a SIMD-related issue):

```Python
np.full((5,), 485., dtype=np.float32).astype(np.uint8)
```
gives the expected: array([229, 229, 229, 229, 229], dtype=uint8)

but for a longer array:
```Python
np.full((8,), 485., dtype=np.float32).astype(np.uint8)
```
gives unexpected: `array([255, 255, 255, 255, 255, 255, 255, 255], dtype=uint8)`

and an odd-sized array
```Python
np.full((9,), 485., dtype=np.float32).astype(np.uint8)
```
gives unexpected: `array([255, 255, 255, 255, 255, 255, 255, 229], dtype=uint8)`
Note here that the first 8 values are unexpected, but the last value is what would be expected (probably computed in a separate final loop without SIMD).

These size differences are what make me suspect this is a SIMD-related bug. However, using a pip installed NumPy does not show the same issue.

This was observed for `numpy 1.21.4 py39h7eed0ac_0 conda-forge`

Environment (conda list):

```
$ conda list

```
# Name Version Build Channel
ca-certificates 2021.10.8 h033912b_0 conda-forge
libblas 3.9.0 12_osx64_openblas conda-forge
libcblas 3.9.0 12_osx64_openblas conda-forge
libffi 3.4.2 h0d85af4_5 conda-forge
libgfortran 5.0.0 9_3_0_h6c81a4c_23 conda-forge
libgfortran5 9.3.0 h6c81a4c_23 conda-forge
liblapack 3.9.0 12_osx64_openblas conda-forge
libopenblas 0.3.18 openmp_h3351f45_0 conda-forge
libzlib 1.2.11 h9173be1_1013 conda-forge
llvm-openmp 12.0.1 hda6cdc1_1 conda-forge
ncurses 6.2 h2e338ed_4 conda-forge
numpy 1.21.4 py39h7eed0ac_0 conda-forge
openssl 3.0.0 h0d85af4_2 conda-forge
pip 21.3.1 pyhd8ed1ab_0 conda-forge
python 3.9.7 h38b4d05_3_cpython conda-forge
python_abi 3.9 2_cp39 conda-forge
readline 8.1 h05e3726_0 conda-forge
setuptools 59.4.0 py39h6e9494a_0 conda-forge
sqlite 3.37.0 h23a322b_0 conda-forge
tk 8.6.11 h5dbffcc_1 conda-forge
tzdata 2021e he74cb21_0 conda-forge
wheel 0.37.0 pyhd8ed1ab_1 conda-forge
xz 5.2.5 haf1e3a3_1 conda-forge
zlib 1.2.11 h9173be1_1013 conda-forge

Details about conda and system ( conda info ):

```
$ conda info

active environment : py39pip
active env location : /Users/glee/mambaforge/envs/py39pip
shell level : 2
user config file : /Users/glee/.condarc
populated config files : /Users/glee/mambaforge/.condarc
conda version : 4.10.3
conda-build version : 3.21.7
python version : 3.9.7.final.0
virtual packages : __osx=12.0.1=0
__unix=0=0
__archspec=1=x86_64
base environment : /Users/glee/mambaforge (writable)
conda av data dir : /Users/glee/mambaforge/etc/conda
conda av metadata url : None
channel URLs : https://conda.anaconda.org/conda-forge/osx-64
https://conda.anaconda.org/conda-forge/noarch
package cache : /Users/glee/mambaforge/pkgs
/Users/glee/.conda/pkgs
envs directories : /Users/glee/mambaforge/envs
/Users/glee/.conda/envs
platform : osx-64
user-agent : conda/4.10.3 requests/2.26.0 CPython/3.9.7 Darwin/21.1.0 OSX/12.0.1
UID:GID : 502:20
netrc file : None
offline mode : False

```