Setting Keras Environment
Prerequisites
For your convenience, you'd better install and use git bash.
Therefore, I will test on git bash or bash terminal integrated within VSCode.
Install Miniconda on Windows
Setting Keras
Install Karas from Yaml
# Make yaml file.
$ vi environment-gpu.yml
name: tf-gpu-1.15
dependencies:
- python=3.6
- tensorflow-gpu=1.15
- keras=2.3.1
- scikit-learn
- scipy
- numpy
- matplotlib
- ipython
- jupyter
- pillow
- opencv
- graphviz
- cython
- pip:
- pydot-ng
# Create conda env
$ conda env create -f environment-gpu.yml
# Enter tf-gpu-1.15 env
$ conda activate tf-gpu-1.15
If not able to activate a certain conda env, add this instruction into .bashrc
. ~/Miniconda3/etc/profile.d/conda.sh
# Check out the installed packages about cuda. $ conda list ... cudatoolkit 10.0.130 0 cudnn 7.6.5 cuda10.0_0 ... keras 2.3.1 0 keras-applications 1.0.8 py_1 keras-base 2.3.1 py36_0 keras-preprocessing 1.1.2 pyhd3eb1b0_0 ... tensorflow 1.15.0 gpu_py36h2b26d6b_0 tensorflow-base 1.15.0 gpu_py36h1afeea4_0 tensorflow-estimator 1.15.1 pyh2649769_0 tensorflow-gpu 1.15.0 h0d30ee6_0 ...
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