Metadata-Version: 2.1
Name: pytorch-deploy
Version: 0.0.1
Summary: Serving pytorch models on an API in one line.
Home-page: https://github.com/mochangheng/pytorch-deploy
Author: Owen Mo, Fiona Xie, Hulbert Zhang
Author-email: mochangheng@gmail.com, fionax@andrew.cmu.edu, hzeng012@ucr.edu
License: UNKNOWN
Description: # 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`
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
