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.
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.
TorchSharp.PyBridge is available on NuGet. You can install it using the following command:
dotnet add package TorchSharp.PyBridge
Install-Package TorchSharp.PyBridge
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");
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'))
Contributions to TorchSharp.PyBridge are welcome.
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.
For support, questions, or feedback, please open an issue in the GitHub repository.