# PyMC V4 install issue: WARNING (Using NumPy C-API based implementation for BLAS functions

**URL:** <https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621>\
**Category:** v5\
**Created:** [June 12, 2022, 2:57am UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621 "2022-06-12T02:57:34Z")\
**Posts on this page:** 17\
**Page:** 1

<div class="post-metadata">

**Author:** ![Mark](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/mark/32/170_2.png) [@Mark](https://discourse.pymc.io/u/Mark)\
**Post date:** [June 12, 2022, 2:57am UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/1 "2022-06-12T02:57:34Z")

</div>

PyMC V4 on M1 MacBook Pro getting this message - WARNING (aesara.tensor.blas): Using NumPy C-API based implementation for BLAS functions.

Install is from Anaconda, just as described in the install instructions.

Any help would be sincerely appreciated.

---

<div class="post-metadata">

**Author:** ![DanhPhan](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/danhphan/32/4799_2.png) [@DanhPhan](https://discourse.pymc.io/u/DanhPhan)\
**Post date:** [June 12, 2022, 5:39am UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/2 "2022-06-12T05:39:43Z")

</div>

Hi, it may help to address the `blas` warnings by using `mamba` to install `pymc` v4 as follow:

```auto
conda create --name pymc4 -c conda-forge python=3.9
conda activate pymc4
conda install -c conda-forge mamba
mamba install -c conda-forge "pymc>=4.0.0"

```

---

<div class="post-metadata">

**Author:** ![Mark](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/mark/32/170_2.png) [@Mark](https://discourse.pymc.io/u/Mark)\
**Post date:** [June 12, 2022, 1:53pm UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/3 "2022-06-12T13:53:18Z")

</div>

Still seeing "WARNING (aesara.tensor.blas): Using NumPy C-API based implementation for BLAS functions” after install with mamba. Thanks for the recommendation, but it didn’t fix it. Other ideas?

---

<div class="post-metadata">

**Author:** ![twiecki](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/twiecki/32/6930_2.png) [@twiecki](https://discourse.pymc.io/u/twiecki)\
**Post date:** [June 12, 2022, 4:54pm UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/4 "2022-06-12T16:54:09Z")

</div>

Can you share the output of `conda list`?

---

<div class="post-metadata">

**Author:** ![Mark](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/mark/32/170_2.png) [@Mark](https://discourse.pymc.io/u/Mark)\
**Post date:** [June 12, 2022, 8:44pm UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/5 "2022-06-12T20:44:14Z")

</div>

Here is conda list:

(pymc4) ➜ ~ conda list

# packages in environment at /Users/shackelford/opt/anaconda3/envs/pymc4:

# 

# Name Version Build Channel

aeppl 0.0.31 pyhd8ed1ab\_0 conda-forge  
aesara 2.6.6 py39h7086893\_0 conda-forge  
arviz 0.12.1 pyhd8ed1ab\_0 conda-forge  
brotli 1.0.9 h5eb16cf\_7 conda-forge  
brotli-bin 1.0.9 h5eb16cf\_7 conda-forge  
brotlipy 0.7.0 py39h63b48b0\_1004 conda-forge  
bzip2 1.0.8 h0d85af4\_4 conda-forge  
c-ares 1.18.1 h0d85af4\_0 conda-forge  
c-compiler 1.4.2 had99412\_0 conda-forge  
ca-certificates 2022.5.18.1 h033912b\_0 conda-forge  
cachetools 5.0.0 pyhd8ed1ab\_0 conda-forge  
cctools 973.0.1 h351d84c\_10 conda-forge  
cctools\_osx-64 973.0.1 h3eff9a4\_10 conda-forge  
certifi 2022.5.18.1 py39h6e9494a\_0 conda-forge  
cffi 1.15.0 py39he338e87\_0 conda-forge  
cftime 1.6.0 py39h86b5767\_1 conda-forge  
charset-normalizer 2.0.12 pyhd8ed1ab\_0 conda-forge  
clang 13.0.1 h694c41f\_0 conda-forge  
clang-13 13.0.1 default\_he082bbe\_0 conda-forge  
clang\_osx-64 13.0.1 h71a8856\_2 conda-forge  
clangxx 13.0.1 default\_he082bbe\_0 conda-forge  
clangxx\_osx-64 13.0.1 heae0f87\_2 conda-forge  
cloudpickle 2.1.0 pyhd8ed1ab\_0 conda-forge  
colorama 0.4.4 pyh9f0ad1d\_0 conda-forge  
compiler-rt 13.0.1 he01351e\_0 conda-forge  
compiler-rt\_osx-64 13.0.1 hd3f61c9\_0 conda-forge  
conda 4.13.0 py39h6e9494a\_1 conda-forge  
conda-package-handling 1.8.1 py39h63b48b0\_1 conda-forge  
cons 0.4.5 pyhd8ed1ab\_0 conda-forge  
cryptography 37.0.2 py39h9c2a9ce\_0 conda-forge  
curl 7.83.1 h372c54d\_0 conda-forge  
cxx-compiler 1.4.2 h1b54a9f\_0 conda-forge  
cycler 0.11.0 pyhd8ed1ab\_0 conda-forge  
etuples 0.3.5 pyhd8ed1ab\_0 conda-forge  
fastprogress 1.0.2 pyhd8ed1ab\_0 conda-forge  
filelock 3.7.1 pyhd8ed1ab\_0 conda-forge  
fonttools 4.33.3 py39h701faf5\_0 conda-forge  
freetype 2.10.4 h4cff582\_1 conda-forge  
giflib 5.2.1 hbcb3906\_2 conda-forge  
hdf4 4.2.15 hefd3b78\_3 conda-forge  
hdf5 1.12.1 nompi\_ha60fbc9\_104 conda-forge  
icu 70.1 h96cf925\_0 conda-forge  
idna 3.3 pyhd8ed1ab\_0 conda-forge  
importlib-metadata 4.11.4 py39h6e9494a\_0 conda-forge  
importlib\_metadata 4.11.4 hd8ed1ab\_0 conda-forge  
jpeg 9e h5eb16cf\_1 conda-forge  
kiwisolver 1.4.2 py39h7248d28\_1 conda-forge  
krb5 1.19.3 hb49756b\_0 conda-forge  
lcms2 2.12 h577c468\_0 conda-forge  
ld64 609 ha328185\_10 conda-forge  
ld64\_osx-64 609 h6fbe7a8\_10 conda-forge  
lerc 3.0 he49afe7\_0 conda-forge  
libarchive 3.5.2 hde4784d\_2 conda-forge  
libblas 3.9.0 15\_osx64\_openblas conda-forge  
libbrotlicommon 1.0.9 h5eb16cf\_7 conda-forge  
libbrotlidec 1.0.9 h5eb16cf\_7 conda-forge  
libbrotlienc 1.0.9 h5eb16cf\_7 conda-forge  
libcblas 3.9.0 15\_osx64\_openblas conda-forge  
libclang-cpp13 13.0.1 default\_he082bbe\_0 conda-forge  
libcurl 7.83.1 h372c54d\_0 conda-forge  
libcxx 14.0.5 hc203e6f\_0 conda-forge  
libdeflate 1.10 h0d85af4\_0 conda-forge  
libedit 3.1.20191231 h0678c8f\_2 conda-forge  
libev 4.33 haf1e3a3\_1 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  
libiconv 1.16 haf1e3a3\_0 conda-forge  
liblapack 3.9.0 15\_osx64\_openblas conda-forge  
libllvm13 13.0.1 h64f94b2\_2 conda-forge  
libmamba 0.24.0 h2d3d89a\_1 conda-forge  
libmambapy 0.24.0 py39h3f08081\_1 conda-forge  
libnetcdf 4.8.1 nompi\_h6609ca0\_102 conda-forge  
libnghttp2 1.47.0 h942079c\_0 conda-forge  
libopenblas 0.3.20 openmp\_hb3cd9ec\_0 conda-forge  
libpng 1.6.37 h7cec526\_2 conda-forge  
libsolv 0.7.22 hd9580d2\_0 conda-forge  
libssh2 1.10.0 h52ee1ee\_2 conda-forge  
libtiff 4.4.0 hfca7e8f\_0 conda-forge  
libwebp 1.2.2 h28dabe5\_0 conda-forge  
libwebp-base 1.2.2 h0d85af4\_1 conda-forge  
libxcb 1.13 h0d85af4\_1004 conda-forge  
libxml2 2.9.14 h08a9926\_0 conda-forge  
libzip 1.8.0 h8b0c345\_1 conda-forge  
libzlib 1.2.12 h6c3fc93\_0 conda-forge  
llvm-openmp 14.0.4 ha654fa7\_0 conda-forge  
llvm-tools 13.0.1 h64f94b2\_2 conda-forge  
logical-unification 0.4.5 pyhd8ed1ab\_0 conda-forge  
lz4-c 1.9.3 he49afe7\_1 conda-forge  
lzo 2.10 haf1e3a3\_1000 conda-forge  
mamba 0.24.0 py39ha435c47\_1 conda-forge  
matplotlib-base 3.5.2 py39h64a0072\_0 conda-forge  
minikanren 1.0.3 pyhd8ed1ab\_0 conda-forge  
mkl 2022.1.0 h860c996\_928 conda-forge  
mkl-service 2.4.0 py39h05e0b47\_0 conda-forge  
multipledispatch 0.6.0 py\_0 conda-forge  
munkres 1.1.4 pyh9f0ad1d\_0 conda-forge  
ncurses 6.3 h96cf925\_1 conda-forge  
netcdf4 1.5.8 nompi\_py39he7d1c46\_101 conda-forge  
numpy 1.22.4 py39h677350a\_0 conda-forge  
openjpeg 2.4.0 h6e7aa92\_1 conda-forge  
openssl 1.1.1o hfe4f2af\_0 conda-forge  
packaging 21.3 pyhd8ed1ab\_0 conda-forge  
pandas 1.4.2 py39hf72b562\_2 conda-forge  
pillow 9.1.1 py39h579eac4\_1 conda-forge  
pip 22.1.2 pyhd8ed1ab\_0 conda-forge  
pthread-stubs 0.4 hc929b4f\_1001 conda-forge  
pybind11-abi 4 hd8ed1ab\_3 conda-forge  
pycosat 0.6.3 py39h63b48b0\_1010 conda-forge  
pycparser 2.21 pyhd8ed1ab\_0 conda-forge  
pymc 4.0.0 py39h360fd21\_1 conda-forge  
pymc-base 4.0.0 py39h6e9494a\_1 conda-forge  
pyopenssl 22.0.0 pyhd8ed1ab\_0 conda-forge  
pyparsing 3.0.9 pyhd8ed1ab\_0 conda-forge  
pysocks 1.7.1 py39h6e9494a\_5 conda-forge  
python 3.9.13 h57e37ff\_0\_cpython conda-forge  
python-dateutil 2.8.2 pyhd8ed1ab\_0 conda-forge  
python\_abi 3.9 2\_cp39 conda-forge  
pytz 2022.1 pyhd8ed1ab\_0 conda-forge  
readline 8.1.2 h3899abd\_0 conda-forge  
reproc 14.2.3 h0d85af4\_0 conda-forge  
reproc-cpp 14.2.3 he49afe7\_0 conda-forge  
requests 2.28.0 pyhd8ed1ab\_0 conda-forge  
ruamel\_yaml 0.15.80 py39h701faf5\_1007 conda-forge  
scipy 1.8.1 py39hfa1a3ab\_0 conda-forge  
setuptools 62.3.4 py39h6e9494a\_0 conda-forge  
sigtool 0.1.3 h57ddcff\_0 conda-forge  
six 1.16.0 pyh6c4a22f\_0 conda-forge  
sqlite 3.38.5 hd9f0692\_0 conda-forge  
tapi 1100.0.11 h9ce4665\_0 conda-forge  
tbb 2021.5.0 hbb4e6a2\_1 conda-forge  
tk 8.6.12 h5dbffcc\_0 conda-forge  
toolz 0.11.2 pyhd8ed1ab\_0 conda-forge  
tqdm 4.64.0 pyhd8ed1ab\_0 conda-forge  
typing-extensions 3.10.0.2 hd8ed1ab\_0 conda-forge  
typing\_extensions 3.10.0.2 pyha770c72\_0 conda-forge  
tzdata 2022a h191b570\_0 conda-forge  
unicodedata2 14.0.0 py39h63b48b0\_1 conda-forge  
urllib3 1.26.9 pyhd8ed1ab\_0 conda-forge  
wheel 0.37.1 pyhd8ed1ab\_0 conda-forge  
xarray 2022.3.0 pyhd8ed1ab\_0 conda-forge  
xarray-einstats 0.2.2 pyhd8ed1ab\_0 conda-forge  
xorg-libxau 1.0.9 h35c211d\_0 conda-forge  
xorg-libxdmcp 1.1.3 h35c211d\_0 conda-forge  
xz 5.2.5 haf1e3a3\_1 conda-forge  
yaml 0.2.5 h0d85af4\_2 conda-forge  
yaml-cpp 0.7.0 hb486fe8\_1 conda-forge  
zipp 3.8.0 pyhd8ed1ab\_0 conda-forge  
zlib 1.2.12 h6c3fc93\_0 conda-forge  
zstd 1.5.2 ha9df2e0\_1 conda-forge

---

<div class="post-metadata">

**Author:** ![twiecki](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/twiecki/32/6930_2.png) [@twiecki](https://discourse.pymc.io/u/twiecki)\
**Post date:** [June 13, 2022, 8:43am UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/6 "2022-06-13T08:43:26Z")

</div>

That all looks correct. What’s the output of:  
`python -m aesara.misc.check_blas`

---

<div class="post-metadata">

**Author:** ![Mark](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/mark/32/170_2.png) [@Mark](https://discourse.pymc.io/u/Mark)\
**Post date:** [June 13, 2022, 12:14pm UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/7 "2022-06-13T12:14:09Z")

</div>

This machine is only a few months old, and when I got it, I did the ‘migration’ process from my previous 2012 MacBook. I’m wondering if something was copied or set up wrong from the old machine? Thanks.  
Here is the output of the python -m apsara.misc.check\_blas:

(pymc4) ➜ ~ python -m aesara.misc.check\_blas  
WARNING (aesara.tensor.blas): Using NumPy C-API based implementation for BLAS functions.

```
    Some results that you can compare against. They were 10 executions
    of gemm in float64 with matrices of shape 2000x2000 (M=N=K=2000).
    All memory layout was in C order.

    CPU tested: Xeon E5345(2.33Ghz, 8M L2 cache, 1333Mhz FSB),
                Xeon E5430(2.66Ghz, 12M L2 cache, 1333Mhz FSB),
                Xeon E5450(3Ghz, 12M L2 cache, 1333Mhz FSB),
                Xeon X5560(2.8Ghz, 12M L2 cache, hyper-threads?)
                Core 2 E8500, Core i7 930(2.8Ghz, hyper-threads enabled),
                Core i7 950(3.07GHz, hyper-threads enabled)
                Xeon X5550(2.67GHz, 8M l2 cache?, hyper-threads enabled)

    Libraries tested:
        * numpy with ATLAS from distribution (FC9) package (1 thread)
        * manually compiled numpy and ATLAS with 2 threads
        * goto 1.26 with 1, 2, 4 and 8 threads
        * goto2 1.13 compiled with multiple threads enabled

                      Xeon Xeon Xeon Core2 i7 i7 Xeon Xeon
    lib/nb threads E5345 E5430 E5450 E8500 930 950 X5560 X5550

    numpy 1.3.0 blas 775.92s
    numpy_FC9_atlas/1 39.2s 35.0s 30.7s 29.6s 21.5s 19.60s
    goto/1 18.7s 16.1s 14.2s 13.7s 16.1s 14.67s
    numpy_MAN_atlas/2 12.0s 11.6s 10.2s 9.2s 9.0s
    goto/2 9.5s 8.1s 7.1s 7.3s 8.1s 7.4s
    goto/4 4.9s 4.4s 3.7s - 4.1s 3.8s
    goto/8 2.7s 2.4s 2.0s - 4.1s 3.8s
    openblas/1 14.04s
    openblas/2 7.16s
    openblas/4 3.71s
    openblas/8 3.70s
    mkl 11.0.083/1 7.97s
    mkl 10.2.2.025/1 13.7s
    mkl 10.2.2.025/2 7.6s
    mkl 10.2.2.025/4 4.0s
    mkl 10.2.2.025/8 2.0s
    goto2 1.13/1 14.37s
    goto2 1.13/2 7.26s
    goto2 1.13/4 3.70s
    goto2 1.13/8 1.94s
    goto2 1.13/16 3.16s

    Test time in float32. There were 10 executions of gemm in
    float32 with matrices of shape 5000x5000 (M=N=K=5000)
    All memory layout was in C order.

    cuda version 8.0 7.5 7.0
    gpu
    M40 0.45s 0.47s
    k80 0.92s 0.96s
    K6000/NOECC 0.71s 0.69s
    P6000/NOECC 0.25s

    Titan X (Pascal) 0.28s
    GTX Titan X 0.45s 0.45s 0.47s
    GTX Titan Black 0.66s 0.64s 0.64s
    GTX 1080 0.35s
    GTX 980 Ti 0.41s
    GTX 970 0.66s
    GTX 680 1.57s
    GTX 750 Ti 2.01s 2.01s
    GTX 750 2.46s 2.37s
    GTX 660 2.32s 2.32s
    GTX 580 2.42s
    GTX 480 2.87s
    TX1 7.6s (float32 storage and computation)
    GT 610 33.5s

```

Some Aesara flags:  
blas\_\_ldflags=  
compiledir= /Users/shackelford/.aesara/compiledir\_macOS-12.4-x86\_64-i386-64bit-i386-3.9.13-64  
floatX= float64  
device= cpu  
Some OS information:  
sys.platform= darwin  
sys.version= 3.9.13 | packaged by conda-forge | (main, May 27 2022, 17:00:52)  
[Clang 13.0.1]  
sys.prefix= /Users/shackelford/opt/anaconda3/envs/pymc4  
Some environment variables:  
MKL\_NUM\_THREADS= None  
OMP\_NUM\_THREADS= None  
GOTO\_NUM\_THREADS= None

Numpy config: (used when the Aesara flag “blas\_\_ldflags” is empty)  
blas\_info:  
libraries = [‘cblas’, ‘blas’, ‘cblas’, ‘blas’]  
library\_dirs = [’/Users/shackelford/opt/anaconda3/envs/pymc4/lib’]  
include\_dirs = [’/Users/shackelford/opt/anaconda3/envs/pymc4/include’]  
language = c  
define\_macros = [(‘HAVE\_CBLAS’, None)]  
blas\_opt\_info:  
define\_macros = [(‘NO\_ATLAS\_INFO’, 1), (‘HAVE\_CBLAS’, None)]  
libraries = [‘cblas’, ‘blas’, ‘cblas’, ‘blas’]  
library\_dirs = [’/Users/shackelford/opt/anaconda3/envs/pymc4/lib’]  
include\_dirs = [’/Users/shackelford/opt/anaconda3/envs/pymc4/include’]  
language = c  
lapack\_info:  
libraries = [‘lapack’, ‘blas’, ‘lapack’, ‘blas’]  
library\_dirs = [’/Users/shackelford/opt/anaconda3/envs/pymc4/lib’]  
language = f77  
lapack\_opt\_info:  
libraries = [‘lapack’, ‘blas’, ‘lapack’, ‘blas’, ‘cblas’, ‘blas’, ‘cblas’, ‘blas’]  
library\_dirs = [’/Users/shackelford/opt/anaconda3/envs/pymc4/lib’]  
language = c  
define\_macros = [(‘NO\_ATLAS\_INFO’, 1), (‘HAVE\_CBLAS’, None)]  
include\_dirs = [’/Users/shackelford/opt/anaconda3/envs/pymc4/include’]  
Supported SIMD extensions in this NumPy install:  
baseline = SSE,SSE2,SSE3  
found = SSSE3,SSE41,POPCNT,SSE42  
not found = AVX,F16C,FMA3,AVX2,AVX512F,AVX512CD,AVX512\_KNL,AVX512\_SKX,AVX512\_CLX,AVX512\_CNL,AVX512\_ICL  
Numpy dot module: numpy  
Numpy location: /Users/shackelford/opt/anaconda3/envs/pymc4/lib/python3.9/site-packages/numpy/ **init**.py  
Numpy version: 1.22.4

We executed 10 calls to gemm with a and b matrices of shapes (5000, 5000) and (5000, 5000).

Total execution time: 23.88s on CPU (with direct Aesara binding to blas).

Try to run this script a few times. Experience shows that the first time is not as fast as following calls. The difference is not big, but consistent.

---

<div class="post-metadata">

**Author:** ![twiecki](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/twiecki/32/6930_2.png) [@twiecki](https://discourse.pymc.io/u/twiecki)\
**Post date:** [June 13, 2022, 5:18pm UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/8 "2022-06-13T17:18:46Z")

</div>

Oh you have an intel chip. In that case you need to install `mkl-service` as well.

---

<div class="post-metadata">

**Author:** ![Mark](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/mark/32/170_2.png) [@Mark](https://discourse.pymc.io/u/Mark)\
**Post date:** [June 13, 2022, 10:46pm UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/9 "2022-06-13T22:46:02Z")

</div>

Wow, that’s news to me. My computer thinks different. See below. Not sure what to do next. I guess major reset to factory setting. Thanks

Hardware Overview:

Model Name: MacBook Pro  
Model Identifier: MacBookPro18,3  
Chip: Apple M1 Pro  
Total Number of Cores: 8 (6 performance and 2 efficiency)  
Memory: 16 GB  
System Firmware Version: 7459.121.3  
OS Loader Version: 7459.121.3  
Serial Number (system): HGXQC7DQF7  
Hardware UUID: 4EA2ADE3-6B7F-53B7-BAF6-EDBF59A7D3B3  
Provisioning UDID: 00006000-000411D63E62801E  
Activation Lock Status: Disabled

---

<div class="post-metadata">

**Author:** ![cluhmann](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/cluhmann/32/3083_2.png) [@cluhmann](https://discourse.pymc.io/u/cluhmann)\
**Post date:** [June 14, 2022, 2:00am UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/10 "2022-06-14T02:00:34Z")

</div>

> [@Mark](#):
>
> when I got it, I did the ‘migration’ process from my previous 2012 MacBook

Can you describe how you migrated from your prior machine? That might explain some of the confusion.

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<div class="post-metadata">

**Author:** ![twiecki](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/twiecki/32/6930_2.png) [@twiecki](https://discourse.pymc.io/u/twiecki)\
**Post date:** [June 14, 2022, 8:20am UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/11 "2022-06-14T08:20:02Z")

</div>

Oh sorry, I was confused, you do have an M1 chip. Then I don’t know why you’re seeing this.

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<div class="post-metadata">

**Author:** ![twiecki](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/twiecki/32/6930_2.png) [@twiecki](https://discourse.pymc.io/u/twiecki)\
**Post date:** [June 14, 2022, 9:46am UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/12 "2022-06-14T09:46:52Z")

</div>

Are you running in Rosetta compatibility mode by any chance?

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<div class="post-metadata">

**Author:** ![CameronBieganek](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/cameronbieganek/32/5276_2.png) [@CameronBieganek](https://discourse.pymc.io/u/CameronBieganek)\
**Post date:** [June 18, 2022, 2:23pm UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/13 "2022-06-18T14:23:02Z")

</div>

Possible solution described here:

> [@WARNING: g++ not detected](https://discourse.pymc.io/t/warning-g-not-detected/9661/3):
>
> I managed to accidentally resolve this issue. I recently updated my operating system from an old version of macOS to the new macOS Monterrey. I was occasionally getting what seemed like an unrelated error when using the terminal (not the python REPL): xcrun: error: invalid active developer path (/Library/Developer/CommandLineTools), missing xcrun at: /Library/Developer/CommandLineTools/usr/bin/xcrun I was able to resolve that by running xcode-select --install in the terminal, as described in t…

In short, you might need to install/re-install `xcode-select` via the following terminal command:

```plaintext
xcode-select --install

```

---

<div class="post-metadata">

**Author:** ![Mark](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/mark/32/170_2.png) [@Mark](https://discourse.pymc.io/u/Mark)\
**Post date:** [June 18, 2022, 4:24pm UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/14 "2022-06-18T16:24:09Z")

</div>

I did a complete factory wipe/reset because I figured that my problem was due to some unknown issue with the original install “migration” from my old MacBook. I installed Xcode, Anaconda3, then created pymc\_dev environment according to install instructions. Then, python, \>\>\> import pymc. I then got the same: WARNING (Using NumPy C-API…).

BTW, when I ran the Anaconda installer, I got the message: To open you need to install Rosetta. Do you want to install it now?

I said “install”.

Not sure what to try next. Any further input or suggestions would be appreciated. Thanks

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<div class="post-metadata">

**Author:** ![thomasaarholt](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/thomasaarholt/32/4350_2.png) [@thomasaarholt](https://discourse.pymc.io/u/thomasaarholt)\
**Post date:** [June 19, 2022, 11:52am UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/15 "2022-06-19T11:52:02Z")

</div>

You are almost certainly running Python via Rosetta - Rosetta is an Apple emulation software that let’s you take software that is compiled for intel CPUs and run it on the new M1 CPUs. I’m pretty sure that you’ve somehow installed Anaconda in a way that told your Mac to use Rosetta for installing it.

I suggest you:  
Uninstall anaconda completely  
Install either anaconda or miniconda ([direct miniconda link for the M1 version here](https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.pkg))  
Optionally `conda install mamba` (highly recommend, and then use `mamba` instead of `conda`)  
Install pymc according to install instructions.

---

<div class="post-metadata">

**Author:** ![Mark](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/mark/32/170_2.png) [@Mark](https://discourse.pymc.io/u/Mark)\
**Post date:** [June 19, 2022, 7:05pm UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/16 "2022-06-19T19:05:18Z")

</div>

Hi Thomas, thanks for your suggestion. I followed your directions and used the M1 miniconda. I installed mamba, created a new environment (pymc4), and then used mamba to install pymc. I got some new errors this time, plus the warning. See result:

(pymc4) ➜ ~ python  
Python 3.9.13 | packaged by conda-forge | (main, May 27 2022, 17:01:00)  
[Clang 13.0.1] on darwin  
Type “help”, “copyright”, “credits” or “license” for more information.

> > > import pymc  
> > > ld: library not found for -lSystem  
> > > clang-13: error: linker command failed with exit code 1 (use -v to see invocation)  
> > > WARNING (aesara.tensor.blas): Using NumPy C-API based implementation for BLAS functions.

---

<div class="post-metadata">

**Author:** ![Mark](https://yyz2.discourse-cdn.com/flex036/user_avatar/discourse.pymc.io/mark/32/170_2.png) [@Mark](https://discourse.pymc.io/u/Mark)\
**Post date:** [June 19, 2022, 7:43pm UTC](https://discourse.pymc.io/t/pymc-v4-install-issue-warning-using-numpy-c-api-based-implementation-for-blas-functions/9621/17 "2022-06-19T19:43:56Z")

</div>

Fixed! PyMC is now working without Warnings or other issues! After having the last error, I went to Xcode and installed an update. Then went back to python and everything worked without error!

Thanks to everybody that helped me get this worked out. Your help is greatly appreciated.

Mark