docs/test/training_test_doc.md

Running Training Scripts

Instructions to run these scripts in the tests folder on Linux, Windows, and macOS:

• tests/training_accelerate_efficientnet_b3.sh
• tests/training_accelerate_efficientnet_v2_s.sh
• tests/training_accelerate_regnet_y_800mf.sh
• tests/training_accelerate_vit_b_16_test.sh

Prerequisites

1. Install Python, PyTorch, Accelerate:

   pip install requirements/requirements.txt
   

2. Create virtual environment:

   python -m venv venv
   source venv/bin/activate  # Linux/macOS
   .\venv\Scripts\activate   # Windows
   

3. Make scripts executable (Linux/macOS):

   chmod +x tests/*.sh
   

Linux

1. Open terminal, go to folder:

   cd tests
   

2. Run scripts:

   ./training_accelerate_efficientnet_b3.sh
   ./training_accelerate_efficientnet_v2_s.sh
   ./training_accelerate_regnet_y_800mf.sh
   ./training_accelerate_vit_b_16_test.sh
   

3. Fix issues:
   • Use bash training_accelerate_efficientnet_b3.sh if ./ fails.
   • Fix line endings:

     sudo apt install dos2unix
     dos2unix training_accelerate_*.sh
     

Windows (using WSL)

1. Install WSL and Ubuntu from Microsoft Store.
2. Install dependencies:

   sudo apt update
   sudo apt install python3 python3-pip
   pip install -r requirements/requirements.txt
   

3. Go to folder:

   cd ./tests
   

4. Make executable:

   chmod +x training_accelerate_*.sh
   

5. Run scripts:

   ./training_accelerate_efficientnet_b3.sh
   

6. Fix issues:
   • Fix line endings:

     sudo apt install dos2unix
     dos2unix training_accelerate_*.sh
     

macOS

1. Open Terminal, go to folder:

   cd tests
   

2. Install dependencies:

   brew install python
   pip install -r requirements/requirements.txt
   

3. Make executable:

   chmod +x training_accelerate_*.sh
   

4. Run scripts:

   ./training_accelerate_efficientnet_b3.sh
   

5. Fix issues:
   • Fix line endings:

     brew install dos2unix
     dos2unix training_accelerate_*.sh
     

Notes

• Ensure GPU support (CUDA for Linux/Windows, MPS for macOS) if needed.
• Check scripts for extra settings (e.g., export CUDA_VISIBLE_DEVICES=0).
• Save output:

  ./training_accelerate_efficientnet_b3.sh > output.log 2>&1