siliconflow / onediff

OneDiff: An out-of-the-box acceleration library for diffusion models.
https://github.com/siliconflow/onediff/wiki
Apache License 2.0
1.71k stars 105 forks source link

add flux example #1126

Open XuZhang99 opened 3 weeks ago

XuZhang99 commented 3 weeks ago
  1. add flux example
  2. change sd3 example
  3. add run benchmark script
  4. add quantization for oneflow

Summary by CodeRabbit

Release Notes

coderabbitai[bot] commented 3 weeks ago

Walkthrough

The pull request introduces several significant changes across multiple scripts related to machine learning model benchmarking and image generation. A new benchmarking script, run_benchmark.sh, has been added to facilitate the testing of various models, including Stable Diffusion and FLUX. Enhancements have been made to text_to_image.py files, incorporating quantization capabilities and improved argument parsing. New functionalities, such as a command-line interface for image generation in text_to_image_flux.py and text_to_image_sd3.py, have also been implemented to allow for more customizable model configurations. Additionally, a new README.md file has been created to guide users in setting up and executing the Flux model.

Changes

File Change Summary
benchmarks/run_benchmark.sh New script added to benchmark machine learning models with environment setup, command-line argument handling, and logging.
benchmarks/text_to_image.py Added quantization capabilities; modified the main function for improved control flow and error handling.
onediff_diffusers_extensions/examples/flux/text_to_image_flux.py New file with command-line interface for image generation, including model loading and performance tracking.
onediff_diffusers_extensions/examples/sd3/text_to_image_sd3.py Significant modifications for argument parsing and structure; introduced new constants and functions for modularity.
onediff_diffusers_extensions/examples/flux/README.md New documentation file added to guide setup and execution of the Flux model with performance benchmarks.

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New scripts hop with joyful flair.
Models run and metrics shine,
With every test, the results align.
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