docs: Update case study JSON for inference pipeline#1
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Creates a Python script `update_json.py` to generate the corrected `output.json` that aligns the image generation model description with the existing inference-only implementation, removing invalid references to training loops and DDIM sampling. Co-authored-by: priths7 <45918183+priths7@users.noreply.github.com>
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Analyzed the existing codebase to verify its actual behavior, discovering that it is an inference-only pipeline (not a training one) and strictly uses DDPM sampling (not DDIM).
Based on this analysis, I updated the provided JSON structure to correctly reflect these realities. Invalid challenges related to training and DDIM were removed and replaced with appropriate inference-specific challenges, such as memory management and proper tensor dimension alignments. The updated JSON is correctly formatted and available as output.
PR created automatically by Jules for task 16263372137241949836 started by @priths7