Beat nnU-Net #168
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Beat nnU-Net #168
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…onTrainer` to optimize loss computation and simplify overrides. (#133)
…UNetTrainer` and added `DiceBCELossWithLogits` as the loss criterion. (#133)
…ted `num_classes` in `UNetTrainer` to 5. (#133)
…resize256`, `roi`) and introduced `UNetSlidingTrainer` for sliding window training. (#133)
…ction naming. (#133)
…ling, added `infer_validation_case` for efficient case inference, and improved memory efficiency in window reconstruction and loss computation.
…kflow to simplify validation logic.
…ation loops for improved performance.
…r improved performance.
…c `.item()` calls, detaching tensors in window reconstruction, and refining loss computation.
…de new training workflow.
…d exclusion and zero-volume cases.
…t index tracking.
…ion, improved dataset handling with new setter methods, and optimized memory usage during window reconstruction and loss computation.
…ed and redundant.
… to `1` for better numerical stability.
…ogits` for improved stability and consistency.
…to segmentation preset for improved clarity and preparation for inference integration.
…solidated metric recording, and streamlined epoch and batch-level metric handling for better clarity and efficiency.
…or improved clarity in metric logging.
…ctions, as it was unused and redundant.
…elper function for improved clarity and reusability.
…or improved consistency and clarity.
…` with `set_transform` methods for improved clarity and consistency.
…ataset()` for improved consistency and flexibility.
…zer; refactored dataset transform handling with `set_transform`.
…duler, and criterion state into a single file for improved clarity and efficiency.
…data transfer efficiency to GPU.
…ine recovery and resume workflows.
…er compatibility with `dataclasses`.
…int` for improved clarity and consistency.
…iling models for improved consistency.
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See #133.