search

microsoft / MLOps_VideoAnomalyDetection

Operationalize a video anomaly detection model with Azure ML
MIT License
129 stars 57 forks source link

trying to build provided Dockerfile results with a failure #1

Closed guybartal closed 4 years ago

guybartal commented 5 years ago 
C:\Users\gubert\Repos\MLOps_VideoAnomalyDetection\config>docker build -f Dockerfile -t wopauli_1.8-gpu:1 .
Sending build context to Docker daemon  8.704kB
Step 1/2 : FROM mcr.microsoft.com/azureml/base-gpu:intelmpi2018.3-cuda9.0-cudnn7-ubuntu16.04
intelmpi2018.3-cuda9.0-cudnn7-ubuntu16.04: Pulling from azureml/base-gpu
7b722c1070cd: Pull complete                                                                                                                                                5fbf74db61f1: Pull complete                                                                                                                                                ed41cb72e5c9: Pull complete                                                                                                                                                7ea47a67709e: Pull complete                                                                                                                                                35400734fa04: Pull complete                                                                                                                                                195acf8a5739: Pull complete                                                                                                                                                127028f911f6: Pull complete                                                                                                                                                84588368cc86: Pull complete                                                                                                                                                decbf3005a1c: Pull complete                                                                                                                                                249412ff35c9: Pull complete                                                                                                                                                3f601dfda46c: Pull complete                                                                                                                                                d481228abde9: Pull complete                                                                                                                                                38567447e6f3: Pull complete                                                                                                                                                1c5715cbc27e: Pull complete                                                                                                                                                9fdb00ca4b90: Pull complete                                                                                                                                                Digest: sha256:fd6c26ca1c5e8aefce47850ebaaea8ae58f2b1516b4530a75fff9d48ffd3a2bb
Status: Downloaded newer image for mcr.microsoft.com/azureml/base-gpu:intelmpi2018.3-cuda9.0-cudnn7-ubuntu16.04
 ---> c0ba45f719a0
Step 2/2 : RUN ldconfig /usr/local/cuda/lib64/stubs &&     conda install -y python=3.6.2 && conda clean -ay &&     pip install --no-cache-dir azureml-defaults &&     pip install --no-cache-dir tensorflow==1.8.0 tensorflow-gpu==1.8.0 keras==2.0.8 matplotlib==3.0.3 seaborn==0.9.0 requests==2.21.0 bs4==0.0.1 imageio==2.5.0 sklearn pandas==0.24.2 numpy==1.16.2 hickle==3.4.3 &&     pip install --no-cache-dir horovod==0.13.5 &&     ldconfig
 ---> Running in 70f2deb6967a
Solving environment: ...working... done

==> WARNING: A newer version of conda exists. <==
  current version: 4.5.11
  latest version: 4.7.5

Please update conda by running

    $ conda update -n base -c defaults conda

ca-certificates-2019 | 133 KB    | ########## | 100%
zlib-1.2.11          | 120 KB    | ########## | 100%
libedit-3.1          | 171 KB    | ########## | 100%
openssl-1.0.2s       | 3.1 MB    | ########## | 100%
setuptools-41.0.1    | 656 KB    | ########## | 100%
sqlite-3.23.1        | 1.5 MB    | ########## | 100%
wheel-0.33.4         | 40 KB     | ########## | 100%
certifi-2019.6.16    | 154 KB    | ########## | 100%
pip-19.1.1           | 1.9 MB    | ########## | 100%
_libgcc_mutex-0.1    | 3 KB      | ########## | 100%
readline-7.0         | 1.1 MB    | ########## | 100%
ncurses-6.0          | 920 KB    | ########## | 100%
python-3.6.2         | 27.0 MB   | ########## | 100%
libgcc-ng-9.1.0      | 8.1 MB    | ########## | 100%
## Package Plan ##

  environment location: /opt/miniconda

  added / updated specs:
    - python=3.6.2

The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    ca-certificates-2019.5.15  |                0         133 KB
    zlib-1.2.11                |       h7b6447c_3         120 KB
    libedit-3.1                |       heed3624_0         171 KB
    openssl-1.0.2s             |       h7b6447c_0         3.1 MB
    setuptools-41.0.1          |           py36_0         656 KB
    sqlite-3.23.1              |       he433501_0         1.5 MB
    wheel-0.33.4               |           py36_0          40 KB
    certifi-2019.6.16          |           py36_0         154 KB
    pip-19.1.1                 |           py36_0         1.9 MB
    _libgcc_mutex-0.1          |             main           3 KB
    readline-7.0               |       ha6073c6_4         1.1 MB
    ncurses-6.0                |       h9df7e31_2         920 KB
    python-3.6.2               |      hca45abc_19        27.0 MB
    libgcc-ng-9.1.0            |       hdf63c60_0         8.1 MB
    ------------------------------------------------------------
                                           Total:        44.9 MB

The following NEW packages will be INSTALLED:

    _libgcc_mutex:   0.1-main

The following packages will be UPDATED:

    ca-certificates: 2018.03.07-0            --> 2019.5.15-0
    certifi:         2018.8.24-py37_1        --> 2019.6.16-py36_0
    libgcc-ng:       8.2.0-hdf63c60_1        --> 9.1.0-hdf63c60_0
    openssl:         1.0.2p-h14c3975_0       --> 1.0.2s-h7b6447c_0
    pip:             10.0.1-py37_0           --> 19.1.1-py36_0
    setuptools:      40.2.0-py37_0           --> 41.0.1-py36_0
    wheel:           0.31.1-py37_0           --> 0.33.4-py36_0
    zlib:            1.2.11-ha838bed_2       --> 1.2.11-h7b6447c_3

The following packages will be DOWNGRADED:

    libedit:         3.1.20170329-h6b74fdf_2 --> 3.1-heed3624_0
    ncurses:         6.1-hf484d3e_0          --> 6.0-h9df7e31_2
    python:          3.7.0-hc3d631a_0        --> 3.6.2-hca45abc_19
    readline:        7.0-h7b6447c_5          --> 7.0-ha6073c6_4
    sqlite:          3.24.0-h84994c4_0       --> 3.23.1-he433501_0

Downloading and Extracting Packages
Preparing transaction: ...working... done
Verifying transaction: ...working... done
Executing transaction: ...working... done

Traceback (most recent call last):
  File "/opt/miniconda/bin/conda", line 7, in <module>
    from conda.cli import main
ModuleNotFoundError: No module named 'conda'
The command '/bin/sh -c ldconfig /usr/local/cuda/lib64/stubs &&     conda install -y python=3.6.2 && conda clean -ay &&     pip install --no-cache-dir azureml-defaults &&     pip install --no-cache-dir tensorflow==1.8.0 tensorflow-gpu==1.8.0 keras==2.0.8 matplotlib==3.0.3 seaborn==0.9.0 requests==2.21.0 bs4==0.0.1 imageio==2.5.0 sklearn pandas==0.24.2 numpy==1.16.2 hickle==3.4.3 &&     pip install --no-cache-dir horovod==0.13.5 &&     ldconfig' returned a non-zero code: 1
guybartal commented 5 years ago

maybe you should remove "conda clean -ay" from the Dockerfile, not sure what is the purpose of that command, but it causing this problem...

wmpauli commented 5 years ago

Have you tried to update your conda base image as suggested in your log? "conda update -n base -c defaults conda"

Besides that, to me it looks like a problem with the conda installation/configuration. Building the docker image works for me.

"conda clean -ay" ensures that we use the newest version of all packages, in case packages have changed without updating release versions. This can be useful if you are using you are including your on pypi packages.