TorchSharp.PyBridge 1.2.0

TorchSharp.PyBridge

TorchSharp.PyBridge is an extension library for TorchSharp, providing seamless interoperability between .NET and Python for model serialization. It simplifies the process of saving and loading PyTorch models in a .NET environment, enabling developers to easily develop models in both .NET and Python and transfer models easily.

Features

• module.load_py(...), optim.load_py(...): Extension method for modules and optimizers for easily loading PyTorch models saved in the standard Python format (using torch.save) directly into TorchSharp.

  This only works for when the state_dict was saved and not the whole model, see example below.

• module.save_py(...), optim.save_py(...): Extension method for modules and optimizers for easily saving TorchSharp models in a format that can be directly loaded in PyTorch (using torch.load), offering cross-platform model compatibility.

• module.load_safetensors(...), module.save_safetensors(...): Extension methods for modules for easily saving and loading model weights using the safetensors format.

• module.load_checkpoint(...): Extension method for loading in a checkpoint (both safetensors and regular pytorch, including sharded models) from a directory saved using HuggingFace's PreTrainedModel.save_pretrained() method.

Getting Started

Installation

TorchSharp.PyBridge is available on NuGet. You can install it using the following command:

.NET CLI

dotnet add package TorchSharp.PyBridge

NuGet Package Manager

Install-Package TorchSharp.PyBridge

Prerequisites

• .NET SDK
• TorchSharp library

Usage

Loading a PyTorch Model in .NET

Saving the model in Python:

import torch 

model = ...
torch.save(model.state_dict(), 'path_to_your_model.pth')

Loading it in C#:

using TorchSharp.PyBridge;

var model = ...;
model.load_py("path_to_your_model.pth");

Saving a TorchSharp Model for PyTorch

To save a model in a format compatible with PyTorch:

using TorchSharp.PyBridge;

var model = ...;
model.save_py("path_to_save_model.pth");

And loading it in in Python:

import torch

model = ...
model.load_state_dict(torch.load('path_to_save_model.pth'))

Contributing

Contributions to TorchSharp.PyBridge are welcome.

Acknowledgments

This project makes use of the pickle library, a Java and .NET implementation of Python's pickle serialization protocol, developed by Irmen de Jong. The pickle library plays a vital role in enabling the serialization features within TorchSharp.PyBridge. We extend our thanks to the developer for their significant contributions to the open-source community. For more details about the pickle library, please visit their GitHub repository.

Support and Contact

For support, questions, or feedback, please open an issue in the GitHub repository.