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I installed the distribution using the command: conda create -n idp -c intel python=3.6 intelpython3_full, and everything seems working.
But when I tried to train using unity mlagent using the regular command mlagents-learn config/config.yaml --run-id=project1 --train I receive the following error message : -
ModuleNotFoundError: No module named 'numpy.core._multiarray_umath'
ModuleNotFoundError: No module named 'numpy.core._multiarray_umath'
Traceback (most recent call last):
File "/anaconda3/envs/idp/bin/mlagents-learn", line 11, in <module>
load_entry_point('mlagents', 'console_scripts', 'mlagents-learn')()
File "/anaconda3/envs/idp/lib/python3.6/site-packages/pkg_resources/__init__.py", line 480, in load_entry_point
return get_distribution(dist).load_entry_point(group, name)
File "/anaconda3/envs/idp/lib/python3.6/site-packages/pkg_resources/__init__.py", line 2693, in load_entry_point
return ep.load()
File "/anaconda3/envs/idp/lib/python3.6/site-packages/pkg_resources/__init__.py", line 2324, in load
return self.resolve()
File "/anaconda3/envs/idp/lib/python3.6/site-packages/pkg_resources/__init__.py", line 2330, in resolve
module = __import__(self.module_name, fromlist=['__name__'], level=0)
File "/Users/adam/ml-agents/ml-agents/mlagents/trainers/__init__.py", line 4, in <module>
from .models import *
File "/Users/adam/ml-agents/ml-agents/mlagents/trainers/models.py", line 4, in <module>
import tensorflow as tf
File "/anaconda3/envs/idp/lib/python3.6/site-packages/tensorflow/__init__.py", line 24, in <module>
from tensorflow.python import * # pylint: disable=redefined-builtin
File "/anaconda3/envs/idp/lib/python3.6/site-packages/tensorflow/python/__init__.py", line 82, in <module>
from tensorflow.python.estimator import estimator_lib as estimator
File "/anaconda3/envs/idp/lib/python3.6/site-packages/tensorflow/python/estimator/estimator_lib.py", line 37, in <module>
from tensorflow.python.estimator.inputs import inputs
File "/anaconda3/envs/idp/lib/python3.6/site-packages/tensorflow/python/estimator/inputs/inputs.py", line 22, in <module>
from tensorflow.python.estimator.inputs.numpy_io import numpy_input_fn
File "/anaconda3/envs/idp/lib/python3.6/site-packages/tensorflow/python/estimator/inputs/numpy_io.py", line 26, in <module>
from tensorflow.python.estimator.inputs.queues import feeding_functions
File "/anaconda3/envs/idp/lib/python3.6/site-packages/tensorflow/python/estimator/inputs/queues/feeding_functions.py", line 40, in <module>
import pandas as pd
File "/anaconda3/envs/idp/lib/python3.6/site-packages/pandas/__init__.py", line 26, in <module>
from pandas._libs import (hashtable as _hashtable,
File "/anaconda3/envs/idp/lib/python3.6/site-packages/pandas/_libs/__init__.py", line 4, in <module>
from .tslibs import (
File "/anaconda3/envs/idp/lib/python3.6/site-packages/pandas/_libs/tslibs/__init__.py", line 4, in <module>
from .conversion import normalize_date, localize_pydatetime, tz_convert_single
File "__init__.pxd", line 918, in init pandas._libs.tslibs.conversion
ValueError: numpy.ufunc size changed, may indicate binary incompatibility. Expected 216 from C header, got 192 from PyObject
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5 Replies
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Can you list your conda list and conda info? It is strange that it cannot find core._multiarray_umath as it was introduced in NumPy 1.16.0 (and our latest is 1.16.1).
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my numpy version is 1.14.5
Python 3.6.8 |Intel Corporation| (default, Feb 27 2019, 19:23:40) [GCC 4.2.1 Compatible Apple LLVM 7.3.0 (clang-703.0.31)] on darwin Type "help", "copyright", "credits" or "license" for more information. Intel(R) Distribution for Python is brought to you by Intel Corporation. Please check out: https://software.intel.com/en-us/python-distribution >>> import numpy >>> numpy.__version__ '1.14.5'
Conda list:
# packages in environment at /anaconda3/envs/idp: # # Name Version Build Channel absl-py 0.7.1 pypi_0 pypi appnope 0.1.0 pypi_0 pypi asn1crypto 0.24.0 py36_3 intel astor 0.7.1 pypi_0 pypi atomicwrites 1.3.0 pypi_0 pypi attrs 19.1.0 pypi_0 pypi backcall 0.1.0 pypi_0 pypi bleach 1.5.0 pypi_0 pypi bzip2 1.0.6 17 intel certifi 2018.1.18 py36_2 intel cffi 1.11.5 py36_3 intel chardet 3.0.4 py36_3 intel cryptography 2.3 py36_1 intel cycler 0.10.0 py36_7 intel cython 0.29.3 py36_1 intel daal 2019.3 intel_199 intel daal4py 2019.3 py36h7b7c402_6 intel decorator 4.4.0 pypi_0 pypi defusedxml 0.5.0 pypi_0 pypi docopt 0.6.2 pypi_0 pypi entrypoints 0.3 pypi_0 pypi freetype 2.9 3 intel funcsigs 1.0.2 py36_7 intel gast 0.2.2 pypi_0 pypi grpcio 1.11.1 pypi_0 pypi html5lib 0.9999999 pypi_0 pypi icc_rt 2019.3 intel_199 intel idna 2.6 py36_3 intel intel-openmp 2019.3 intel_199 intel intelpython 2019.3 0 intel intelpython3_core 2019.3 0 intel intelpython3_full 2019.3 0 intel ipykernel 5.1.0 pypi_0 pypi ipython 7.4.0 pypi_0 pypi ipython-genutils 0.2.0 pypi_0 pypi ipywidgets 7.4.2 pypi_0 pypi jedi 0.13.3 pypi_0 pypi jinja2 2.10.1 pypi_0 pypi jsonschema 3.0.1 pypi_0 pypi jupyter 1.0.0 pypi_0 pypi jupyter-client 5.2.4 pypi_0 pypi jupyter-console 6.0.0 pypi_0 pypi jupyter-core 4.4.0 pypi_0 pypi kiwisolver 1.0.1 py36_2 intel libffi 3.2.1 11 intel libpng 1.6.36 2 intel llvmlite 0.27.1 py36_0 intel markdown 3.1 pypi_0 pypi markupsafe 1.1.1 pypi_0 pypi matplotlib 3.0.1 py36_1 intel mistune 0.8.4 pypi_0 pypi mkl 2019.3 intel_199 intel mkl-service 1.0.0 py36_7 intel mkl_fft 1.0.11 py36h7b7c402_0 intel mkl_random 1.0.2 py36h7b7c402_4 intel mlagents 0.8.1 dev_0 <develop> more-itertools 7.0.0 pypi_0 pypi nbconvert 5.4.1 pypi_0 pypi nbformat 4.4.0 pypi_0 pypi notebook 5.7.8 pypi_0 pypi numba 0.42.1 np116py36_0 intel numexpr 2.6.8 py36_2 intel numpy 1.14.5 pypi_0 pypi openssl 1.0.2r 0 intel pandas 0.24.1 py36_3 intel pandocfilters 1.4.2 pypi_0 pypi parso 0.4.0 pypi_0 pypi pexpect 4.7.0 pypi_0 pypi pickleshare 0.7.5 pypi_0 pypi pillow 6.0.0 pypi_0 pypi pip 19.0.3 pypi_0 pypi pluggy 0.9.0 pypi_0 pypi prometheus-client 0.6.0 pypi_0 pypi prompt-toolkit 2.0.9 pypi_0 pypi protobuf 3.6.1 pypi_0 pypi ptyprocess 0.6.0 pypi_0 pypi py 1.8.0 pypi_0 pypi pycosat 0.6.3 py36_3 intel pycparser 2.18 py36_2 intel pygments 2.3.1 pypi_0 pypi pyopenssl 17.5.0 py36_2 intel pyparsing 2.2.0 py36_2 intel pyrsistent 0.14.11 pypi_0 pypi pysocks 1.6.7 py36_1 intel pytest 3.10.1 pypi_0 pypi python 3.6.8 6 intel python-dateutil 2.6.0 py36_12 intel pytz 2018.4 py36_3 intel pyyaml 4.1 py36_3 intel pyzmq 18.0.1 pypi_0 pypi qtconsole 4.4.3 pypi_0 pypi requests 2.20.1 py36_1 intel ruamel_yaml 0.11.14 py36_4 intel scikit-learn 0.20.2 py36h7b7c402_2 intel scipy 1.2.0 py36_3 intel send2trash 1.5.0 pypi_0 pypi setuptools 39.0.1 py36_0 intel six 1.11.0 py36_3 intel sqlite 3.27.2 2 intel tbb 2019.4 intel_199 intel tbb4py 2019.4 py36_intel_0 intel tcl 8.6.4 22 intel tensorboard 1.7.0 pypi_0 pypi tensorflow 1.7.1 pypi_0 pypi termcolor 1.1.0 pypi_0 pypi terminado 0.8.2 pypi_0 pypi testpath 0.4.2 pypi_0 pypi tk 8.6.4 28 intel tornado 6.0.2 pypi_0 pypi traitlets 4.3.2 pypi_0 pypi urllib3 1.24.1 py36_2 intel wcwidth 0.1.7 pypi_0 pypi werkzeug 0.15.2 pypi_0 pypi wheel 0.31.0 py36_3 intel widgetsnbextension 3.4.2 pypi_0 pypi xz 5.2.3 2 intel yaml 0.1.7 2 intel zlib 1.2.11 5 intel
Conda info:
active environment : idp
active env location : /anaconda3/envs/idp
shell level : 3
user config file : /Users/adam/.condarc
populated config files : /Users/adam/.condarc
conda version : 4.6.4
conda-build version : 3.17.6
python version : 3.7.1.final.0
base environment : /anaconda3 (writable)
channel URLs : https://conda.anaconda.org/intel/osx-64
https://conda.anaconda.org/intel/noarch
https://repo.anaconda.com/pkgs/main/osx-64
https://repo.anaconda.com/pkgs/main/noarch
https://repo.anaconda.com/pkgs/free/osx-64
https://repo.anaconda.com/pkgs/free/noarch
https://repo.anaconda.com/pkgs/r/osx-64
https://repo.anaconda.com/pkgs/r/noarch
package cache : /anaconda3/pkgs
/Users/adam/.conda/pkgs
envs directories : /anaconda3/envs
/Users/adam/.conda/envs
platform : osx-64
user-agent : conda/4.6.4 requests/2.21.0 CPython/3.7.1 Darwin/18.5.0 OSX/10.14.4
UID:GID : 501:20
netrc file : None
offline mode : False
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Hello,
From the output of "conda list" it appears that many of the Intel packages were replaced by packages from PyPI, including numpy. The latest version of numpy in the Intel channel on anaconda.org is 1.16.1, and your version is 1.14.5. The pandas package in your environment was built with numpy 1.16 using Intel(R) MKL, while the numpy 1.14.5 in your environment came from PyPI.
My guess is that after creation of your initial environment, you installed Tensorflow from PyPI, and many of the conda-installed packages were overwritten.
My recommendation is to use conda to install tensorflow from the Anaconda default channel using "conda install tensorflow". You will get a much more recent version of Tensorflow (1.13.1 instead of 1.7.1) accelerated with Intel(R) MKL-DNN and your other Intel packages will be preserved.
-Todd
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Thank you. Only that Unity ML Agents does not support above numpy 1.14
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Adham,
If you require specific older versions of packages in order to be compatible with other software such as Unity ML Agents, you will need to be more explicit with versions when you create your environment. It is also more tricky when you are mixing package managers (pip and conda).
My recommendation, then, is to create an environment that specifies all the version requirements that you are aware of. For example:
$ conda create -n unityml -c intel python=3.6 numpy=1.14 scipy pandas Collecting package metadata: done Solving environment: done .... The following NEW packages will be INSTALLED: bzip2 intel/osx-64::bzip2-1.0.6-17 certifi intel/osx-64::certifi-2018.1.18-py36_2 cycler intel/osx-64::cycler-0.10.0-py36_7 freetype intel/osx-64::freetype-2.9-3 icc_rt intel/osx-64::icc_rt-2019.3-intel_199 intel-openmp intel/osx-64::intel-openmp-2019.3-intel_199 intelpython intel/osx-64::intelpython-2019.3-0 kiwisolver intel/osx-64::kiwisolver-1.0.1-py36_2 libpng intel/osx-64::libpng-1.6.36-2 matplotlib intel/osx-64::matplotlib-2.2.2-np114py36_4 mkl intel/osx-64::mkl-2019.3-intel_199 mkl_fft intel/osx-64::mkl_fft-1.0.2-np114py36_6 mkl_random intel/osx-64::mkl_random-1.0.1-np114py36_6 numexpr intel/osx-64::numexpr-2.6.5-np114py36_2 numpy intel/osx-64::numpy-1.14.3-py36_5 openssl intel/osx-64::openssl-1.0.2r-0 pandas intel/osx-64::pandas-0.23.0-np114py36_1 pip intel/osx-64::pip-10.0.1-py36_0 pyparsing intel/osx-64::pyparsing-2.2.0-py36_2 python intel/osx-64::python-3.6.8-6 python-dateutil intel/osx-64::python-dateutil-2.6.0-py36_12 pytz intel/osx-64::pytz-2018.4-py36_3 scipy intel/osx-64::scipy-1.1.0-np114py36_6 setuptools intel/osx-64::setuptools-39.0.1-py36_0 six intel/osx-64::six-1.11.0-py36_3 sqlite intel/osx-64::sqlite-3.27.2-2 tbb intel/osx-64::tbb-2019.4-intel_199 tbb4py intel/osx-64::tbb4py-2019.4-py36_intel_0 tcl intel/osx-64::tcl-8.6.4-22 tk intel/osx-64::tk-8.6.4-28 wheel intel/osx-64::wheel-0.31.0-py36_3 xz intel/osx-64::xz-5.2.3-2 zlib intel/osx-64::zlib-1.2.11-5 Proceed (/n)?
-----------------------------
Then, when installing additional packages from PyPI, ensure that none of your existing packages are overwritten.
Again, mixing packages from pip and conda can be tricky, so it may take some time and a few iterations to get it right.
Hope this helps,
Todd
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