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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,107 @@ | ||
| --- | ||
| trainer: | ||
| class_path: eva.Trainer | ||
| init_args: | ||
| n_runs: 5 | ||
| default_root_dir: &OUTPUT_ROOT ${oc.env:OUTPUT_ROOT, logs/${oc.env:DINO_BACKBONE, owkin/phikon}/offline/bach} | ||
| max_steps: &MAX_STEPS 12500 | ||
| callbacks: | ||
| - class_path: pytorch_lightning.callbacks.LearningRateMonitor | ||
| init_args: | ||
| logging_interval: epoch | ||
| - class_path: pytorch_lightning.callbacks.ModelCheckpoint | ||
| init_args: | ||
| filename: best | ||
| save_last: true | ||
| save_top_k: 1 | ||
| monitor: &MONITOR_METRIC ${oc.env:MONITOR_METRIC, val/MulticlassAccuracy} | ||
| mode: &MONITOR_METRIC_MODE ${oc.env:MONITOR_METRIC_MODE, max} | ||
| - class_path: pytorch_lightning.callbacks.EarlyStopping | ||
| init_args: | ||
| min_delta: 0 | ||
| patience: 800 | ||
| monitor: *MONITOR_METRIC | ||
| mode: *MONITOR_METRIC_MODE | ||
| - class_path: eva.callbacks.EmbeddingsWriter | ||
| init_args: | ||
| output_dir: &EMBEDDINGS_DIR ${oc.env:EMBEDDINGS_ROOT, ./data/embeddings}/${oc.env:DINO_BACKBONE, owkin/phikon}/bach | ||
| dataloader_idx_map: | ||
| 0: train | ||
| 1: val | ||
| backbone: | ||
| class_path: eva.models.wrappers.HuggingFaceModel | ||
| init_args: | ||
| model_name_or_path: owkin/phikon | ||
| tensor_transforms: | ||
| class_path: eva.vision.data.transforms.model_output.ExtractCLSFeatures | ||
| logger: | ||
| - class_path: pytorch_lightning.loggers.TensorBoardLogger | ||
| init_args: | ||
| save_dir: *OUTPUT_ROOT | ||
| name: "" | ||
| model: | ||
| class_path: eva.HeadModule | ||
| init_args: | ||
| head: | ||
| class_path: torch.nn.Linear | ||
| init_args: | ||
| in_features: ${oc.env:IN_FEATURES, 768} | ||
| out_features: &NUM_CLASSES 4 | ||
| criterion: torch.nn.CrossEntropyLoss | ||
| optimizer: | ||
| class_path: torch.optim.SGD | ||
| init_args: | ||
| lr: &LR_VALUE 0.00064 | ||
| momentum: 0.9 | ||
| weight_decay: 0.0 | ||
| lr_scheduler: | ||
| class_path: torch.optim.lr_scheduler.CosineAnnealingLR | ||
| init_args: | ||
| T_max: *MAX_STEPS | ||
| eta_min: 0.0 | ||
| metrics: | ||
| common: | ||
| - class_path: eva.metrics.AverageLoss | ||
| - class_path: eva.metrics.MulticlassClassificationMetrics | ||
| init_args: | ||
| num_classes: *NUM_CLASSES | ||
| data: | ||
| class_path: eva.DataModule | ||
| init_args: | ||
| datasets: | ||
| train: | ||
| class_path: eva.vision.data.datasets.embeddings.PatchEmbeddingDataset | ||
| init_args: &DATASET_ARGS | ||
| root: *EMBEDDINGS_DIR | ||
| split: train | ||
| column_mapping: | ||
| path: embedding | ||
| val: | ||
| class_path: eva.vision.data.datasets.embeddings.PatchEmbeddingDataset | ||
| init_args: | ||
| <<: *DATASET_ARGS | ||
| split: val | ||
| predict: | ||
| - class_path: eva.vision.datasets.BACH | ||
| init_args: &PREDICT_DATASET_ARGS | ||
| root: ${oc.env:DATA_ROOT, ./data}/bach | ||
| split: train | ||
| download: ${oc.env:DOWNLOAD_DATA, true} | ||
| image_transforms: | ||
| class_path: eva.vision.data.transforms.common.ResizeAndCrop | ||
| init_args: | ||
| size: ${oc.env:RESIZE_DIM, 224} | ||
| mean: ${oc.env:NORMALIZE_MEAN, [0.485, 0.456, 0.406]} | ||
| std: ${oc.env:NORMALIZE_STD, [0.229, 0.224, 0.225]} | ||
| - class_path: eva.vision.datasets.BACH | ||
| init_args: | ||
| <<: *PREDICT_DATASET_ARGS | ||
| split: val | ||
| dataloaders: | ||
| train: | ||
| batch_size: &BATCH_SIZE 256 | ||
| shuffle: true | ||
| val: | ||
| batch_size: *BATCH_SIZE | ||
| predict: | ||
| batch_size: &PREDICT_BATCH_SIZE ${oc.env:PREDICT_BATCH_SIZE, 128} |
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