Skip to main content

Inference service package for IAPARC

Project description

iaparc_inference

PyPI version PyPI - License

The IA Parc inference plugin allows developers to easily integrate their inference pipeline into IA Parc's production module.

Installation

pip install iaparc-inference

Usage

  • If your inference pipeline support batching:

    from iaparc_inference import IAPListener
    
    # Define a callback to query your inference pipeline
    # To load your model only once it is recommended to use a class:
    class MyModel:
        def __init__(self, model_path: str):
            ## Load your model in pytorch, tensorflow or any other backend
        
        def batch_query(batch: list, parameters: Optional) -> list:
            ''' execute your pipeline on a batch input
                Note:   "parameters" is an optional argument.
                        It can be used to handle URL's query parameters
                        It's a list of key(string)/value(string) dictionaries
            '''
    
    if __name__ == '__main__':
        # Initiate your model class
        my_model = MyModel("path/to/my/model")
    
        # Initiate IAParc listener
        listener = IAPListener(my_model.batch_query)
        # Start the listener
        listener.run()
    
  • If your inference pipeline do not support batching:

    from iaparc_inference import IAPListener
    
    # Define a callback to query your inference pipeline
    # To load your model only once it is recommended to use a class:
    class MyModel:
        def __init__(self, model_path: str):
            ## Load your model in pytorch, tensorflow or any other backend
        
        def single_query(one_input, parameters: Optional):
            ''' execute your pipeline on a single input
                Note:   "parameters" is an optional argument.
                        It can be used to handle URL's query parameters
                        It's a key(string)/value(string) dictionary
            '''
    
    if __name__ == '__main__':
        # Initiate your model class
        my_model = MyModel("path/to/my/model")
    
        # Initiate IAParc listener
        listener = IAPListener(my_model.single_query, batch=1)  # Note that batch size is forced to 1 here
        # Start the listener
        listener.run()
    

Features

  • Dynamic batching
  • Autoscalling
  • Support both synchronous and asynchronous queries
  • Data agnostic

License

This project is licensed under the Apache License Version 2.0 - see the Apache LICENSE file for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

iaparc_inference-0.5.10.tar.gz (16.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

iaparc_inference-0.5.10-py3-none-any.whl (18.7 kB view details)

Uploaded Python 3

File details

Details for the file iaparc_inference-0.5.10.tar.gz.

File metadata

  • Download URL: iaparc_inference-0.5.10.tar.gz
  • Upload date:
  • Size: 16.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.15

File hashes

Hashes for iaparc_inference-0.5.10.tar.gz
Algorithm Hash digest
SHA256 cb43bd68c5657492119a39ce82804a61f690b4600b6e6d030a001d3e90fb1bd8
MD5 067a8a9e0a8e29c6c3521dfd7dca484c
BLAKE2b-256 848d37c7755a1d9255d06d519d7ff97c26e6bc819336f959ce548c0d74668416

See more details on using hashes here.

File details

Details for the file iaparc_inference-0.5.10-py3-none-any.whl.

File metadata

File hashes

Hashes for iaparc_inference-0.5.10-py3-none-any.whl
Algorithm Hash digest
SHA256 fa004053595fc2b33952e4386ba6e2c3d1da95eb7059870e17203d80e94fbca8
MD5 0a0ba21963e80d32f55e76f1caaba124
BLAKE2b-256 97def387147823e3e272dcec6a54e9cc624ab3e0d6617a15df881bbb597514d6

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page