Migrate hardcoded values to config #21
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- Remove unused imports (base64, TRAINING_DATASET_DICT) from dataset.py - Remove redundant hf_hub_download import from model.py - Remove redundant Image import and unused variables from run_inference.py These changes address F401 and F841 lint errors while maintaining functionality. Co-Authored-By: [email protected] <[email protected]>
…nused-imports Fix lint errors: Remove unused imports and variables
- Add model architecture parameters - Add training parameters - Add image processing settings - Add random seeds configuration - Update all files to use config values Co-Authored-By: [email protected] <[email protected]>
Co-Authored-By: [email protected] <[email protected]>
- Restore torch.set_float32_matmul_precision('high') setting
- Add comments explaining .reshape() usage for CPU compatibility
- Document tensor operation changes for better maintainability
This addresses PR #2 review feedback regarding tensor operations
and MATMUL_PRECISION configuration.
Co-Authored-By: [email protected] <[email protected]>
- Remove comments explaining .reshape() vs .view() implementation details - Keep actual tensor operations and their functional descriptions intact - Maintain code functionality while reducing implementation details This addresses PR #2 review feedback regarding documentation. Co-Authored-By: [email protected] <[email protected]>
- Revert tensor operations from reshape() to view() in train_text_to_image.py - Update finetune_autoencoder.py to use config values for image processing - Remove CPU-specific map_location from model.py - Update run_inference.py to use hardcoded seeds Co-Authored-By: [email protected] <[email protected]>
…actor refactor: move hardcoded values to config
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