Improving Inference Testing with New Features Driven by Artificial Intelligence and Type Compatibility Resolutions #410
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In this update, significant enhancements have been made to the inference testing script to integrate advanced AI-driven features and resolve issues identified by static code analysis tools. The key updates include: 1. Integration of AI Features: - Implemented AI-driven validation mechanisms to enhance the robustness of inference tests, ensuring more accurate and reliable outputs for both text-to-image and image-to-image pipelines. 2. Type Compatibility Fix: - Addressed a type compatibility issue where the return type of the generator function was incompatible with the `SamplingPipeline`. The function's return type was updated to ensure compatibility with `Generator[Any, Any, Any]`, resolving the diagnostic error reported by Pylance. 3. Improved Sampling and Refinement Processes: - Added enhanced sampling and refinement processes, utilizing AI to optimize the quality of generated images, particularly when using the SDXL models. 4. Code Optimization: - Refined the overall code structure to improve readability and maintainability, ensuring that the integration of new features does not compromise the script's performance. These updates collectively elevate the testing framework's capability, making it more adaptable and efficient in handling complex AI-driven generative model pipelines.
AI-Enhanced Inference Testing with Type Compatibility Fixes
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Summary
This update adds more AI features into the SamplingPipeline class of the inference testing script, rectifies type compatibility problems, expands the testing area, optimizes memory usage, and enhances image processing procedures following generation.
Related Issues
Compatibility of Types and Generator[Any, Any] in SamplingPipeline.
The Pylance said that the critical error was the absence of a proper return type.
Discussions
Talked about the main idea of the module that is AI sampling and distinctive type of compatibility.
QA Instructions
Make an attempt at testing sampling using AI, compatibility of generators and extended inference tests.
Merge Plan
Check the AI sampling and memory management optimizations before they are merged.
Motivation and Context
These were done to enhance the computation of the inference performance, have a compliance with the type hints, and free up space in the memory during testing.
Types of Changes
Feature addition: AI sampling.
Bug fix: Type compatibility.
Enhancement: This is in line with our premise that extended testing and memory will be favourable for introducing optimization.