PyTorch Model Conversion to TorchScript 🧠

TorchScript is a compiled form of PyTorch models that allows exporting models for deployment in environments where Python is not available. This guide explains how to convert PyTorch models into TorchScript format.

Key Steps for Conversion

1. Export with torchscript
   Use torch.jit.script() for models defined with Python functions or torch.jit.trace() for models with static computation graphs.

   

2. Save the Model
   After conversion, save it using .save() method:

   model_script.save("model.pt")
   

3. Load and Run
   Load the TorchScript model in a different environment:

   model = torch.jit.load("model.pt")
   output = model(input_tensor)
   

Use Cases

• Mobile Apps 📱
  TorchScript enables model deployment on iOS/Android via PyTorch Mobile.
• Web Services 🌐
  Use TorchScript with frameworks like FastAPI or Flask for production APIs.
• C++ Integration 🧩
  Compile TorchScript models for use in C++ applications using torch::jit::compile().

Tips

• Always test the converted model for accuracy.
• Use torch.jit.script for models with dynamic control flow (e.g., loops, conditionals).
• For static graphs, torch.jit.trace is faster but less flexible.

For deeper insights into TorchScript features, check our PyTorch官方文档 🔗.

Note: TorchScript is ideal for production deployment but may not support all PyTorch features.