Add LoRA extraction, verification, and comparison scripts

[ShreejithSG]

This PR adds a set of scripts under scripts/lora_extraction for working with LoRA adapters in FastVideo models based on Wan 2.2 TI2V:

Description:

This PR adds a set of scripts under scripts/lora_extraction for working with LoRA adapters in FastVideo models based on Wan 2.2 TI2V:

1. extract_lora.py – extracts LoRA weights from a fine-tuned model relative to a base model using low-rank decomposition. Supports checkpointing.
2. verify_lora.py – reapplies extracted LoRA to the base model and compares per-layer transformer weights to verify extraction correctness.
3. compare_lora_outputs.py – batch comparison of generated outputs between base, fine-tuned, and base+LoRA models. Outputs image/video metrics (MSE, MAE, LPIPS, SSIM).
4. README.md – explains usage and workflow.

Notes:

Layer-level verification shows near-zero MSE (≈3.6e-08) between original and re-applied weights.

Preliminary perceptual checks show image-level differences (MSE ≈0.19, LPIPS ≈0.62, SSIM ≈0.128). The cause is under investigation.

Scripts are designed to be callable individually rather than a single pipeline, aligning with typical workflows (fused/finetuned checkpoint -> extract -> verify).

[gemini-code-assist]

Summary of Changes

Hello @ShreejithSG, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces a comprehensive set of utility scripts under "scripts/lora_extraction" to facilitate the management and validation of LoRA adapters within FastVideo models, specifically those built on the Wan 2.2 TI2V architecture. The scripts enable users to extract LoRA weights, verify their numerical accuracy, and perform perceptual comparisons of model outputs, providing essential tools for researchers and developers working with fine-tuned diffusion models.

Highlights

• LoRA Extraction Script: Introduces "extract_lora.py" for extracting LoRA weights from fine-tuned models relative to a base model using low-rank decomposition, with checkpointing support for large model runs.
• LoRA Verification Script: Adds "verify_lora.py" to reapply extracted LoRA to the base model and compare per-layer transformer weights to numerically verify extraction correctness, showing near-zero MSE.
• Output Comparison Script: Includes "compare_lora_outputs.py" for batch comparison of generated outputs (images/videos) between base, fine-tuned, and base+LoRA models, providing metrics like MSE, MAE, LPIPS, and SSIM.
• Documentation: A new "README.md" is added to provide a clear overview and usage instructions for the new LoRA utility scripts, explaining the workflow and default configurations.

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[gemini-code-assist]

Code Review

This pull request introduces a valuable set of scripts for LoRA extraction, verification, and comparison. The implementation is generally sound and serves its purpose well. My review focuses on enhancing the scripts' robustness, configurability, and adherence to Python best practices. The main suggestions include wrapping script logic in main functions guarded by if __name__ == "__main__":, using argparse for configuration instead of hardcoded constants, improving error handling with more specific exception catching, and addressing potential runtime errors. I have also noted a discrepancy between the documentation and script behavior for resuming extraction.

[gemini-code-assist]

The script's logic is executed at the module's top level. This is not a good practice as it prevents the script from being imported without running its code, and makes it hard to reuse. All script logic should be encapsulated in a main function, called from an if __name__ == '__main__': block. This would also be a good place to introduce argparse to handle configuration parameters like model names, paths, and rank, instead of using global constants. This would also resolve the discrepancy with the README.md regarding the --resume flag.

[ShreejithSG]

@SolitaryThinker, I’ve raised a PR adding the LoRA extraction, verification, and comparison scripts under scripts/lora_extraction.