Library for onboarding models to OpenAD toolkit

Installation

Requirements :

• Linux or Macos
  
• Python 310.10 or 3.11
  

Install the latest version by tag, such as

pip install git+https://github.com/acceleratedscience/openad_service_utils.git@0.3.0

Model Implementations

Look under the examples folder for implementations of models.

• implementation for generation models readme
• implementation for properties example readme

Use your own private model not hosted on gt4sd S3 bucket

set the following variables in the os host or python script to your private s3 buckets:

import os
os.environ["GT4SD_S3_HOST"] = "s3.<region>.amazonaws.com"
os.environ["GT4SD_S3_ACCESS_KEY"] = ""
os.environ["GT4SD_S3_SECRET_KEY"] = ""
os.environ["GT4SD_S3_HOST_HUB"] = "s3.<region>.amazonaws.com"
os.environ["GT4SD_S3_ACCESS_KEY_HUB"] = ""
os.environ["GT4SD_S3_SECRET_KEY_HUB"] = ""

Allow Asynchronous results

This feature allows you to define a service as ansynchronously capable. It generates a unique id for the job at random using UUID and will store the result for 3 days before deleting. the user can request the result at any time in the 3 days.

the environment variable 'ASYNC_ALLOW' mut be set for it to work.

import os
os.environ["ASYNC_ALLOW"] = True 

Example:

OpenAD:DEFAULT >>  pserve generate with MySimpleGenerator data   for "{'<esol>': -3.2}"  sample 4 async
✔ Request Returned
{'id': '8c2cfb68-b037-11ef-9223-acde48001122'}
OpenAD:DEFAULT >>  get model service 'pserve' result '8c2cfb68-b037-11ef-9223-acde48001122'
job is still running
OpenAD:DEFAULT >>  get model service 'pserve' result '8c2cfb68-b037-11ef-9223-acde48001122'

  pred1    pred2
-------  -------
      1        2

Next up, you can run: result open/edit/copy/display/as dataframe/save [as '<filename.csv>']

Experimental Settings

The following are Experimental or Advanced Settings that can be included as Environmental Variables

AUTO_CLEAR_GPU_MEM

Clears the GPU memory for an Inference call
Default: AUTO_CLEAR_GPU_MEM: bool = True

AUTO_GARABAGE_COLLECT

Calls the Garbage Collector after an Inference call
Default AUTO_GARABAGE_COLLECT: bool = True

SERVE_MAX_WORKERS

Enables Multi-Processing of synchronous Calls, Defaults to 1 Thread for safety, depends on performance sizing whether you choose to use more than 1.
Default: SERVE_MAX_WORKERS: int = -1

ENABLE_CACHE_RESULTS

Enables Caching of Results for command requests, this should only be activated for Deterministic Requests, no functions that use random seeds should this be activated for.
Default: ENABLE_CACHE_RESULTS: bool = False

ASYNC_POOL_MAX

The Default value for Asynchronous requests is 1, this is so server capacity is managed to the minimum. It is up to the developer and Deployer of a service to set this higher than 1 based on benchmarking.

Default ASYNC_POOL_MAX: int = 1

Local Cache locations for models

Generation Models location

~/.openad_models / algorithms / algorithm_type / algorithm_name / algorithm_application / algorithm_version

Property Models location

~/.openad_models / properties / domain / algorithm_name / algorithm_application / algorithm_version