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Installation Guide
- Python 3.5
- Linux OS (Minerva is tested only on Linux machines)
When in your working directory (writing permission), clone or download Minerva code. Type:
$ git clone https://github.com/neptune-ml/minerva.git
Setup virtualenv
- Create virtualenv:
$ virtualenv minerva -p python3.5
- Activate newly created environment:
$ source minerva/bin/activate
- Check if your python is in the Minerva environment. Type:
$ which python
You should get answer similar to this:
./minerva/bin/python`
Minerva uses both PyTorch and TensorFlow. These packages comes in two flavors, that is with GPU acceleration and without it. Note, that it is highly recommended to train your solution on GPU.
If you already know your CUDA version go straight to CUDA section
There are several ways to get this information:
- Type:
$ nvcc --version
You should get answer similar to this:
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2016 NVIDIA Corporation
Built on Sun_Sep__4_22:14:01_CDT_2016
Cuda compilation tools, release 8.0, V8.0.44
CUDA version is printed at the end of the last line.
- If previous step didn't work, type:
$ cat /usr/local/cuda/version.txt
You should get answer similar to this:
CUDA Version 8.0.61
- If previous steps didn't work, ask your system administrator for support.
- install TensorFlow
$ pip3 install tensorflow-gpu==1.2.0
- install PyTorch, by following PyTorch Get Started. Make sure that you picked python 3.5 and appropriate CUDA version.
It this case, you will work on your processor. Also, you may want to consider using Neptune to train your models.
- install TensorFlow
$ pip3 install tensorflow==1.2.0
- install PyTorch, by following PyTorch Get Started. Make sure that you picked python 3.5 and None CUDA version.
While your environment is activated (check Setup virtualenv section), install remaining requirements. Type:
$ cd <minerva/code/path>
$ pip3 install -r requirements.txt