First we'll create a Dockerfile to create a Docker Image to setup environment with all dependencies installs.
Dockerfile looks like this.
FROM python:3.6
WORKDIR /usr/src/app
COPY requirements.txt ./
RUN pip install --no-cache-dir -r requirements.txt
It has all liabraies listed for all environments (Keras, Sci-Kit Learn, Tensorflow)
Dependencies for Keras
absl-py==0.9.0
astunparse==1.6.3
cachetools==4.1.1
certifi==2020.6.20
chardet==3.0.4
gast==0.3.3
google-auth==1.18.0
google-auth-oauthlib==0.4.1
google-pasta==0.2.0
grpcio==1.30.0
h5py==2.10.0
idna==2.10
importlib-metadata==1.7.0
Keras==2.4.3
Keras-Preprocessing==1.1.2
Markdown==3.2.2
numpy==1.19.0
oauthlib==3.1.0
opt-einsum==3.2.1
protobuf==3.12.2
pyasn1==0.4.8
pyasn1-modules==0.2.8
PyYAML==5.3.1
requests==2.24.0
requests-oauthlib==1.3.0
rsa==4.6
scipy==1.4.1
six==1.15.0
tensorboard==2.2.2
tensorboard-plugin-wit==1.7.0
tensorflow==2.2.0
tensorflow-estimator==2.2.0
termcolor==1.1.0
urllib3==1.25.9
Werkzeug==1.0.1
wrapt==1.12.1
zipp==3.1.0
Dependencies for Sci-Kit Learn
joblib==0.16.0
numpy==1.19.0
scikit-learn==0.23.1
scipy==1.5.1
Dependencies for TensorFlow
requests-oauthlib==1.3.0
scipy==1.4.1
six==1.15.0
tensorboard==2.2.2
tensorboard-plugin-wit==1.7.0
tensorflow==2.2.0
tensorflow-estimator==2.2.0
termcolor==1.1.0
urllib3==1.25.9
Werkzeug==1.0.1
wrapt==1.12.1
zipp==3.1.0
Content type
Image
Digest
Size
889.3 MB
Last updated
about 6 years ago
docker pull rajneeshmehta93/mlops:tensorflow