Add comprehensive input validation for training hyperparameters in ControlNet Flux training script #11980
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- Add extensive validation for training parameters like learning_rate, batch_size, epochs, etc. - Validate that numeric parameters are within valid ranges (e.g., positive values, betas in [0,1)) - Add reasonable bounds checking for resolution (64-4096 pixels) - Include helpful warnings for potentially problematic parameter combinations - Improve user experience by catching invalid configurations early with clear error messages This prevents runtime errors and training failures caused by invalid hyperparameters, making the training script more robust and user-friendly.
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sayakpaul
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Jan 10, 2026
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sayakpaul
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sayakpaul
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Wow, this is pretty cool! I think this could be applied to other influential scripts as well (such as the Flux LoRA trainer)?
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Summary
This pull request enhances the robustness of the training script by introducing explicit parameter validation, improving error messaging, and aligning the behavior with user expectations and Diffusers' philosophy of educational code examples.
Key Improvements
ValueErrormessages for invalid configurationsChecklist