pytorch-deploy 0.0.1

Serving pytorch models on an API in one line.

pytorch-deploy

Usage

from torch_deploy import deploy
deploy(your_model)

deploy Function

deploy(model: nn.Module, pre: Union[List[Callable], Callable] = None, post: Union[List[Callable], Callable] = None, host: str = "0.0.0.0", port: int = 8000, logfile: str = None)

Easily converts a pytorch model to API for production usage.

• model: A PyTorch model which subclasses nn.Module and is callable. Model used for the API.
• pre: A function or list of functions to be applied to the input.
• post: Function or list of functions applied to model output before being sent as a response.
• host: The address for serving the model.
• port: The port for serving the model.
• logfile: filename to create a file that stores date, ip address, and size of input for each access of the API. If None, no file will be created.

Sample Response Format

Sample Code

Testing

Run python test_server.py first and then python test_client.py in another window to test.

Dependencies

torch, torchvision, fastapi[all], requests, numpy, pydantic