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feat: neutrophils
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refactor: project_name -> ml
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chore: new mlkit
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feat: labels
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refactor: labels
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feat: types
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feat: tiles dataset
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feat: tiles dataframe to hfdataset
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feat: neutrophils ml
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feat: neutrophil dataset conf
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Experiment/ikem validation (#14)
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fix: update threshold keys in bags, embeddings, and tiles configurations
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fix: remove redundant mode entries from ikem validation configuration…
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fix: add missing mode entry in ikem validation configuration files
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fix: correct target dataset for prediction in bags configuration
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fix: update number of classes in neutrophils configuration to match m…
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fix: add missing checkpoint file extension in nancy_high configuration
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| # Machine Learning Template | ||||||||||||||||||||||||||||||||||||||
| # Automated Grading of Ulcerative Colitis from H&E Whole Slide Images | ||||||||||||||||||||||||||||||||||||||
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| This repository contains the machine learning pipeline developed for automated histological grading of ulcerative colitis (UC) biopsies using the Nancy Histological Index (NHI). The approach frames NHI grading as a hierarchical classification problem: a binary neutrophil-detection task routes each whole-slide image through either a low-grade (NHI 0–2) or a high-grade (NHI 2–4) classifier. All models are based on pretrained pathology foundation models and use attention-based multiple instance learning (MIL) over tile embeddings, making them applicable to gigapixel slides without requiring tile-level annotations. Experiments evaluate multiple foundation models (prov-gigapath, UNI, UNI2, Virchow, Virchow2), MIL against tile-level approaches, ordered regression, and ensembling/confidence strategies over a multi-institution cohort (IKEM, FTN, KNL). | ||||||||||||||||||||||||||||||||||||||
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| > **Note: This code is not runnable as-is.** The underlying H&E whole-slide image data and derived embeddings are sensitive patient data from clinical institutions and are not included in this repository. The code is provided for reference and reproducibility of the methodology only. | ||||||||||||||||||||||||||||||||||||||
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| --- | ||||||||||||||||||||||||||||||||||||||
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| ## Repository Structure | ||||||||||||||||||||||||||||||||||||||
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| ``` | ||||||||||||||||||||||||||||||||||||||
| . | ||||||||||||||||||||||||||||||||||||||
| ├── configs/ # Hydra configuration tree | ||||||||||||||||||||||||||||||||||||||
| │ ├── dataset/ # Dataset split URIs (embeddings, slides, tiles) | ||||||||||||||||||||||||||||||||||||||
| │ ├── checkpoints/ # Checkpoint paths for test/inference runs | ||||||||||||||||||||||||||||||||||||||
| │ ├── predictions/ # MLflow prediction artifact URIs (per institution/fold) | ||||||||||||||||||||||||||||||||||||||
| │ └── experiment/ | ||||||||||||||||||||||||||||||||||||||
| │ ├── ml/ # ML training & test experiment configs (Exp I–VI + final) | ||||||||||||||||||||||||||||||||||||||
| │ └── postprocessing/ # Postprocessing experiment configs (Exp VII–VIII + final) | ||||||||||||||||||||||||||||||||||||||
| ├── ml/ # PyTorch Lightning modules & entry point | ||||||||||||||||||||||||||||||||||||||
| │ ├── __main__.py # Entry point: `python -m ml` | ||||||||||||||||||||||||||||||||||||||
| │ ├── base.py # BaseModule (tile-level training loop) | ||||||||||||||||||||||||||||||||||||||
| │ ├── classification.py # Tile-level softmax classification | ||||||||||||||||||||||||||||||||||||||
| │ ├── ordered_regression.py # Cumulative link ordered regression | ||||||||||||||||||||||||||||||||||||||
| │ ├── mil.py # Attention MIL (bag-level) | ||||||||||||||||||||||||||||||||||||||
| │ ├── neutrophils.py # Binary neutrophil detection (tile-level) | ||||||||||||||||||||||||||||||||||||||
| │ └── modeling/ # Building blocks (heads, normalization) | ||||||||||||||||||||||||||||||||||||||
| ├── preprocessing/ # Data preparation pipeline | ||||||||||||||||||||||||||||||||||||||
| │ ├── tiling.py # Tile extraction from WSIs | ||||||||||||||||||||||||||||||||||||||
| │ ├── tissue_masks.py # Tissue segmentation | ||||||||||||||||||||||||||||||||||||||
| │ ├── quality_control.py # Tile quality filtering | ||||||||||||||||||||||||||||||||||||||
| │ ├── embeddings.py # Foundation model feature extraction | ||||||||||||||||||||||||||||||||||||||
| │ ├── neutrophils.py # Neutrophil pseudo-label extraction | ||||||||||||||||||||||||||||||||||||||
| │ ├── create_dataset.py # Assemble HuggingFace dataset | ||||||||||||||||||||||||||||||||||||||
| │ └── split_dataset.py # Train/val/test split assignment | ||||||||||||||||||||||||||||||||||||||
| ├── postprocessing/ # Slide-level aggregation & confidence | ||||||||||||||||||||||||||||||||||||||
| │ ├── ensembling.py # Soft majority vote + hierarchical ensembling | ||||||||||||||||||||||||||||||||||||||
| │ ├── markov_chain_confidence.py # Markov chain absorption confidence scores | ||||||||||||||||||||||||||||||||||||||
| │ ├── ensembling_predict.py # Ensembling for unlabeled cohorts (no metrics) | ||||||||||||||||||||||||||||||||||||||
| │ └── markov_chain_confidence_predict.py # Confidence scores for unlabeled cohorts | ||||||||||||||||||||||||||||||||||||||
| ├── scripts/ # Kubernetes job submission scripts | ||||||||||||||||||||||||||||||||||||||
| │ ├── ml/ # train.py, test.py, neutrophils.py | ||||||||||||||||||||||||||||||||||||||
| │ ├── preprocessing/ # Preprocessing job scripts | ||||||||||||||||||||||||||||||||||||||
| │ └── postprocessing/ # Postprocessing job scripts | ||||||||||||||||||||||||||||||||||||||
| ├── pyproject.toml | ||||||||||||||||||||||||||||||||||||||
| └── thesis.pdf # Thesis manuscript | ||||||||||||||||||||||||||||||||||||||
| ``` | ||||||||||||||||||||||||||||||||||||||
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| --- | ||||||||||||||||||||||||||||||||||||||
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| ## Setup | ||||||||||||||||||||||||||||||||||||||
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| Requires Python 3.12 and [`uv`](https://github.com/astral-sh/uv). | ||||||||||||||||||||||||||||||||||||||
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| ```bash | ||||||||||||||||||||||||||||||||||||||
| uv sync --frozen | ||||||||||||||||||||||||||||||||||||||
| ``` | ||||||||||||||||||||||||||||||||||||||
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| --- | ||||||||||||||||||||||||||||||||||||||
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| ## Pipeline Overview | ||||||||||||||||||||||||||||||||||||||
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| The full pipeline runs in four stages: | ||||||||||||||||||||||||||||||||||||||
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| ### 1. Preprocessing | ||||||||||||||||||||||||||||||||||||||
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| Tiles are extracted from WSIs, tissue-masked, quality-filtered, and encoded by a foundation model into fixed-dimensional embeddings. Datasets are assembled as HuggingFace Datasets and registered in MLflow. | ||||||||||||||||||||||||||||||||||||||
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| ```bash | ||||||||||||||||||||||||||||||||||||||
| # Tissue segmentation masks | ||||||||||||||||||||||||||||||||||||||
| uv run --active -m preprocessing.tissue_masks +dataset=processed/... | ||||||||||||||||||||||||||||||||||||||
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| # Tile extraction from WSIs | ||||||||||||||||||||||||||||||||||||||
| uv run --active -m preprocessing.tiling +dataset=processed_w_masks/... +experiment=preprocessing/tiling/... | ||||||||||||||||||||||||||||||||||||||
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| # Tile quality filtering | ||||||||||||||||||||||||||||||||||||||
| uv run -m preprocessing.quality_control +dataset=processed/... | ||||||||||||||||||||||||||||||||||||||
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| # Foundation model feature extraction | ||||||||||||||||||||||||||||||||||||||
| uv run --active -m preprocessing.embeddings +dataset=tiled/... | ||||||||||||||||||||||||||||||||||||||
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| # Assemble HuggingFace dataset | ||||||||||||||||||||||||||||||||||||||
| uv run -m preprocessing.create_dataset +dataset=raw/... | ||||||||||||||||||||||||||||||||||||||
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| # Train/val/test split assignment | ||||||||||||||||||||||||||||||||||||||
| uv run -m preprocessing.split_dataset +experiment=preprocessing/split_dataset/... | ||||||||||||||||||||||||||||||||||||||
| ``` | ||||||||||||||||||||||||||||||||||||||
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| ### 2. ML Training | ||||||||||||||||||||||||||||||||||||||
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| Models are trained via Hydra experiment configs. The entry point is `python -m ml` and an experiment config must be selected: | ||||||||||||||||||||||||||||||||||||||
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| ```bash | ||||||||||||||||||||||||||||||||||||||
| # Example: train Experiment IV (MIL) fold 1 | ||||||||||||||||||||||||||||||||||||||
| uv run -m ml +experiment=ml/experiment_iv_mil_and_hierarchical_modeling/nancy_high/train/fold_1 | ||||||||||||||||||||||||||||||||||||||
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| # Example: train final model (all institutions combined) | ||||||||||||||||||||||||||||||||||||||
| uv run -m ml +experiment=ml/final/nancy_high/train | ||||||||||||||||||||||||||||||||||||||
| ``` | ||||||||||||||||||||||||||||||||||||||
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| ### 3. ML Testing / Inference | ||||||||||||||||||||||||||||||||||||||
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| ```bash | ||||||||||||||||||||||||||||||||||||||
| # Example: test Experiment IV fold 1 | ||||||||||||||||||||||||||||||||||||||
| uv run -m ml +experiment=ml/experiment_iv_mil_and_hierarchical_modeling/nancy_high/test/fold_1 | ||||||||||||||||||||||||||||||||||||||
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| # Neutrophil detection (produces binary slide-level predictions) | ||||||||||||||||||||||||||||||||||||||
| uv run -m ml.neutrophils +experiment=ml/experiment_vi_neutrophil_detection/run | ||||||||||||||||||||||||||||||||||||||
| ``` | ||||||||||||||||||||||||||||||||||||||
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| ### 4. Postprocessing | ||||||||||||||||||||||||||||||||||||||
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| Slide-level predictions from the three hierarchical tasks are combined into final NHI grades and confidence scores: | ||||||||||||||||||||||||||||||||||||||
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| ```bash | ||||||||||||||||||||||||||||||||||||||
| # Ensembling (soft majority vote + hierarchical routing) | ||||||||||||||||||||||||||||||||||||||
| uv run -m postprocessing.ensembling +postprocessing=ensembling | ||||||||||||||||||||||||||||||||||||||
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| # Markov chain absorption confidence | ||||||||||||||||||||||||||||||||||||||
| uv run -m postprocessing.markov_chain_confidence +postprocessing=markov_chain_confidence | ||||||||||||||||||||||||||||||||||||||
| ``` | ||||||||||||||||||||||||||||||||||||||
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| For unlabeled cohorts (no ground-truth NHI grades, e.g. external validation), use the | ||||||||||||||||||||||||||||||||||||||
| `_predict` variants, which skip label loading and metric computation and only emit | ||||||||||||||||||||||||||||||||||||||
| predictions / confidence scores: | ||||||||||||||||||||||||||||||||||||||
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| ```bash | ||||||||||||||||||||||||||||||||||||||
| uv run -m postprocessing.ensembling_predict +postprocessing=ensembling_predict | ||||||||||||||||||||||||||||||||||||||
| uv run -m postprocessing.markov_chain_confidence_predict +postprocessing=markov_chain_confidence_predict | ||||||||||||||||||||||||||||||||||||||
| ``` | ||||||||||||||||||||||||||||||||||||||
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| --- | ||||||||||||||||||||||||||||||||||||||
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| ## Experiments | ||||||||||||||||||||||||||||||||||||||
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| | # | Name | Config path | Description | | ||||||||||||||||||||||||||||||||||||||
| |---|------|-------------|-------------| | ||||||||||||||||||||||||||||||||||||||
| | I | Baseline Classification | `experiment/ml/experiment_i_baseline_classification` | VGG16 tile-level classifier trained on raw pixel tiles | | ||||||||||||||||||||||||||||||||||||||
| | II | Ordered Regression | `experiment/ml/experiment_ii_ordered_regression` | Cumulative link loss for NHI ordinal structure | | ||||||||||||||||||||||||||||||||||||||
| | III | Pathology Foundation Models | `experiment/ml/experiment_iii_pathology_foundation_model` | Linear probe on frozen prov-gigapath embeddings | | ||||||||||||||||||||||||||||||||||||||
| | IV | MIL & Hierarchical Modeling | `experiment/ml/experiment_iv_mil_and_hierarchical_modeling` | Attention MIL; three-task hierarchical decomposition | | ||||||||||||||||||||||||||||||||||||||
| | V | More Foundation Models | `experiment/ml/experiment_v_more_foundation_models` | MIL sweep over all foundation models | | ||||||||||||||||||||||||||||||||||||||
| | VI | Neutrophil Detection | `experiment/ml/experiment_vi_neutrophil_detection` | Binary tile-level neutrophil classifier | | ||||||||||||||||||||||||||||||||||||||
| | VII | Ensembling | `experiment/postprocessing/experiment_vii_ensembling` | Soft majority vote vs. hierarchical routing | | ||||||||||||||||||||||||||||||||||||||
| | VIII | Markov Chain Confidence | `experiment/postprocessing/experiment_viii_markov_chain_model_aggregation` | Absorption distribution confidence (entropy / herfindahl / std) | | ||||||||||||||||||||||||||||||||||||||
| | — | Final Model | `experiment/ml/final` | Attention MIL (virchow2) trained on all three institutions | | ||||||||||||||||||||||||||||||||||||||
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| All cross-validation experiments run 5 folds over the IKEM institution. Final evaluation uses the held-out test split across IKEM, FTN, and KNL. | ||||||||||||||||||||||||||||||||||||||
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configs/checkpoints/experiment_ii_ordered_regression/fold_5.yaml
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configs/checkpoints/experiment_iii_pathology_foundation_model/fold_1.yaml
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configs/checkpoints/experiment_iii_pathology_foundation_model/fold_2.yaml
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configs/checkpoints/experiment_iii_pathology_foundation_model/fold_3.yaml
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configs/checkpoints/experiment_iii_pathology_foundation_model/fold_4.yaml
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configs/checkpoints/experiment_iii_pathology_foundation_model/fold_5.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/nancy_high/fold_1.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/nancy_high/fold_2.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/nancy_high/fold_3.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/nancy_high/fold_4.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/nancy_high/fold_5.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/nancy_low/fold_1.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/nancy_low/fold_2.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/nancy_low/fold_3.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/nancy_low/fold_4.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/nancy_low/fold_5.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/neutrophils/fold_1.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/neutrophils/fold_2.yaml
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| checkpoint: ??? |
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/neutrophils/fold_3.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/neutrophils/fold_4.yaml
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configs/checkpoints/experiment_iv_mil_and_hierarchical_modeling/neutrophils/fold_5.yaml
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...gs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_prov-gigapath/fold_1.yaml
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| checkpoint: ??? |
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...gs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_prov-gigapath/fold_2.yaml
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| Original file line number | Diff line number | Diff line change |
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| checkpoint: ??? |
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...gs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_prov-gigapath/fold_3.yaml
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| checkpoint: ??? |
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...gs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_prov-gigapath/fold_4.yaml
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| checkpoint: ??? |
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...gs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_prov-gigapath/fold_5.yaml
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| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_uni2/fold_1.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_uni2/fold_2.yaml
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| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_uni2/fold_3.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_uni2/fold_4.yaml
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| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_uni2/fold_5.yaml
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| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_virchow2/fold_1.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_virchow2/fold_2.yaml
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| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_virchow2/fold_3.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_virchow2/fold_4.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/1_virchow2/fold_5.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/2_virchow2/fold_1.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/2_virchow2/fold_2.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/2_virchow2/fold_3.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/2_virchow2/fold_4.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_high/2_virchow2/fold_5.yaml
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...igs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_prov-gigapath/fold_1.yaml
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...igs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_prov-gigapath/fold_2.yaml
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| checkpoint: ??? |
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...igs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_prov-gigapath/fold_3.yaml
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...igs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_prov-gigapath/fold_4.yaml
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...igs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_prov-gigapath/fold_5.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_uni2/fold_1.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_uni2/fold_2.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_uni2/fold_3.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_uni2/fold_4.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_uni2/fold_5.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_virchow2/fold_1.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_virchow2/fold_2.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_virchow2/fold_3.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_virchow2/fold_4.yaml
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| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/1_virchow2/fold_5.yaml
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| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/2_virchow2/fold_1.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/2_virchow2/fold_2.yaml
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| Original file line number | Diff line number | Diff line change |
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| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/2_virchow2/fold_3.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/2_virchow2/fold_4.yaml
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configs/checkpoints/experiment_v_more_foundation_models/nancy_low/2_virchow2/fold_5.yaml
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| checkpoint: ??? |
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...s/checkpoints/experiment_v_more_foundation_models/neutrophils/1_prov-gigapath/fold_1.yaml
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| checkpoint: ??? |
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...s/checkpoints/experiment_v_more_foundation_models/neutrophils/1_prov-gigapath/fold_2.yaml
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| checkpoint: ??? |
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...s/checkpoints/experiment_v_more_foundation_models/neutrophils/1_prov-gigapath/fold_3.yaml
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| checkpoint: ??? |
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...s/checkpoints/experiment_v_more_foundation_models/neutrophils/1_prov-gigapath/fold_4.yaml
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...s/checkpoints/experiment_v_more_foundation_models/neutrophils/1_prov-gigapath/fold_5.yaml
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/1_uni2/fold_1.yaml
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/1_uni2/fold_2.yaml
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/1_uni2/fold_3.yaml
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| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/1_uni2/fold_4.yaml
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/1_uni2/fold_5.yaml
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/1_virchow2/fold_1.yaml
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| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/1_virchow2/fold_2.yaml
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/1_virchow2/fold_3.yaml
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/1_virchow2/fold_4.yaml
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| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/1_virchow2/fold_5.yaml
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/2_virchow2/fold_1.yaml
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| @@ -0,0 +1 @@ | ||
| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/2_virchow2/fold_2.yaml
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1 @@ | ||
| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/2_virchow2/fold_3.yaml
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1 @@ | ||
| checkpoint: ??? |
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configs/checkpoints/experiment_v_more_foundation_models/neutrophils/2_virchow2/fold_4.yaml
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1 @@ | ||
| checkpoint: ??? |
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1
configs/checkpoints/experiment_v_more_foundation_models/neutrophils/2_virchow2/fold_5.yaml
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1 @@ | ||
| checkpoint: ??? |
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| # @package _global_ | ||
|
|
||
| checkpoint: mlflow-artifacts:/86/ac693e2ee17e4254a30786c0668e7af4/artifacts/checkpoints/epoch=299-step=176100/checkpoint.ckpt |
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| # @package _global_ | ||
|
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| checkpoint: mlflow-artifacts:/86/452e6f1bf18c45d3bc1d2ae9b44154ae/artifacts/checkpoints/epoch=299-step=176100/checkpoint.ckpt |
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| # @package _global_ | ||
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| checkpoint: mlflow-artifacts:/86/5f9d50d8dccf45e6b8a80d8d3b0f773c/artifacts/checkpoints/epoch=70-step=41677/checkpoint.ckpt |
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| defaults: | ||
| - /dataset/tiled/ftn/1_224@_here_ | ||
| - _self_ | ||
|
|
||
| mlflow_uris: | ||
| embeddings: | ||
| train: ??? | ||
| test_preliminary: ??? | ||
| test_final: ??? |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,9 @@ | ||
| defaults: | ||
| - /dataset/tiled/ftn/1_224@_here_ | ||
| - _self_ | ||
|
|
||
| mlflow_uris: | ||
| embeddings: | ||
| train: ??? | ||
| test_preliminary: ??? | ||
| test_final: ??? |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,9 @@ | ||
| defaults: | ||
| - /dataset/tiled/ftn/1_224@_here_ | ||
| - _self_ | ||
|
|
||
| mlflow_uris: | ||
| embeddings: | ||
| train: ??? | ||
| test_preliminary: ??? | ||
| test_final: ??? |
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The rule code
TC002is invalid in Ruff. The correct rule code for ignoring third-party imports in type-checking blocks isTCH002(as part of theTCH/flake8-type-checkingruleset). Changing this toTC002will cause Ruff to fail with a configuration parsing error.