Prerequisites

In this section we demonstrate how to set up an environment with PyTorch.

TradeMaster supports different operating systems: Linux, Windows and macOS. It requires Python xx, CUDA xx and PyTorch xx.

Step 0. Download and install Miniconda from the official website.

Installation

Linux Installation

Step 1: Install Anaconda

• Please follow the steps in this blog

Step 2: Install OpenAI

• Open an ubuntu terminal and type:

  sudo apt-get update && sudo apt-get install cmake libopenmpi-dev python3-dev zlib1g-dev libgl1-mesa-glx swig
  

Step 3: Install TradeMaster

• Open a terminal amd type

  conda create --name TradeMaster python=3.7.13
  

  to install a new conda environment for TradeMaster

• Install TradeMaster

  git clone https://github.com/TradeMaster-NTU/TradeMaster.git
  

• Open the folder TradeMaster and open a terminal under the same position

• Install the dependency of TradeMaster, run the command:

  conda activate TradeMaster
  cd ./requirement
  pip install -r requirements.txt
  conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
  

Windows Installation

Step 1: Install WSL

• Please follow the steps in this blog

Step 2: Install Anaconda

• Please follow the steps in this blog

Step 3: Install OpenAI

• Open an ubuntu terminal and type:

  sudo apt-get update && sudo apt-get install cmake libopenmpi-dev python3-dev zlib1g-dev libgl1-mesa-glx swig
  

Step 4: Install TradeMaster

• Open a terminal amd type

  conda create --name TradeMaster python=3.7.13
  

  to install a new conda environment for TradeMaster

• Install TradeMaster

  git clone https://github.com/TradeMaster-NTU/TradeMaster.git
  

• Open the folder TradeMaster and open a terminal under the same position

• Install the dependency of TradeMaster, run the command:

  conda activate TradeMaster
  cd ./requirement
  pip install -r requirements.txt
  conda install pytorch torchvision torchaudio cpuonly -c pytorch
  

MacOS Installation

Step 1: Install Anaconda

• Follow Anaconda’s instruction: macOS graphical install, to install the newest version of Anaconda.

• Open your terminal and type: which python, it should show:

  /Users/your_user_name/opt/anaconda3/bin/python
  

  It means that your Python interpreter path has been pinned to Anaconda’s python version. If it shows something like this:

  /Users/your_user_name/opt/anaconda3/bin/python
  

  It means that you still use the default python path, you either fix it and pin it to the anaconda path (try this blog), or you can use Anaconda Navigator to open a terminal manually.

Step 2: Install Homebrew

• Open a terminal and make sure that you have installed Anaconda.

• Install Homebrew:

  /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
  

Step 3: Install OpenAI

Installation of system packages on Mac requires Homebrew. With Homebrew installed, run the following in your terminal:

brew install cmake openmpi

Step 4: Install TradeMaster

• Open a terminal amd type

  conda create --name TradeMaster python=3.7.13
  

  to install a new conda environment for TradeMaster

• Install TradeMaster

   git clone https://github.com/TradeMaster-NTU/TradeMaster.git
  

• Open the folder TradeMaster and open a terminal under the same position

• Install the dependency of TradeMaster, run the command:

  conda activate TradeMaster
  cd ./requirement
  pip install -r requirements.txt
  conda install pytorch torchvision torchaudio -c pytorch
  

Verify the installation

Customize Installation

Install on Google Colab

Using TradeMaster with Docker

Docker is a set of platform as a service (PaaS) products that use OS-level virtualization to deliver software in packages called containers.

Step 1: Install Docker

• Please follow the steps in this blog

• To check whether the Docker has been installed properly, type docker version, it should show:

  Client:
   Cloud integration: v1.0.29
   Version:           20.10.17
   API version:       1.41
   Go version:        go1.17.11
   Git commit:        100c701
   Built:             Mon Jun  6 23:09:02 2022
   OS/Arch:           windows/amd64
   Context:           default
   Experimental:      true
  
  Server: Docker Desktop 4.12.0 (85629)
   Engine:
    Version:          20.10.17
    API version:      1.41 (minimum version 1.12)
    Go version:       go1.17.11
    Git commit:       a89b842
    Built:            Mon Jun  6 23:01:23 2022
    OS/Arch:          linux/amd64
    Experimental:     false
   containerd:
    Version:          1.6.8
    GitCommit:        9cd3357b7fd7218e4aec3eae239db1f68a5a6ec6
   runc:
    Version:          1.1.4
    GitCommit:        v1.1.4-0-g5fd4c4d
   docker-init:
    Version:          0.19.0
    GitCommit:        de40ad0
  

Step 2: Build the docker image from dockerfile

• Install TradeMaster

   git clone https://github.com/TradeMaster-NTU/TradeMaster.git
  

• Create image from the project docker file.

  If your chip is arm-architectured, open terminal or cmd in the position of the project and type

  cd ./docker/arm
  docker build -t="trademaster:0.1" .
  

  If you chip is x86-architectured, open terminal or cmd in the position of the project and type

  cd ./docker/x86
  docker build -t="trademaster:0.1" .
  

  It will take a while before the image is built.

Step 3: Test whether the image is installed correctly

• Open the terminal in the project position and type

  docker image ls
  

  It should shows

  REPOSITORY    TAG       IMAGE ID       CREATED         SIZE
  trademaster   0.1       02801f755797   4 minutes ago   15GB 
  

• Create a container and run an experiment to see whether the installation is successful

  docker run -it trademaster:0.1
  python experiment/AT/DeepScalper/experiment.py