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Installation Guide
- Python 3.5
- Linux OS (Minerva is tested on Linux machines only)
Clone or download Minerva code. Type:
$ cd your/working/directory
$ git clone https://github.com/neptune-ml/minerva.git
Note that you must have writing permission in your working directory.
Setup virtualenv
- Create virtualenv:
$ cd your/working/directory
$ virtualenv minerva_venv -p python3.5
Note that you must have writing permission in your working directory.
- Activate newly created environment:
$ source minerva_venv/bin/activate
- Check if your python is in the Minerva environment. Type:
$ which python
You should get answer similar to this:
./minerva_venv/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, CUDA is probably not installed on your computer. If you want to take advantage of it anyway, 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.
- 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 path/to/minerva
$ pip3 install -r requirements.txt
You may want to consider using Neptune to train your models. It gives you an access to powerful external resources and allows you to easily track the progress of your experiments. Minerva is fully integrated with Neptune, however Neptune is not required at any point.
That's all! Now you may want to go to the User Guide to check how to work with Minerva.