Comments (1)
Raise an error. If you have dirty data it's your problem, bro.
from deep_pipe.
Related Issues (20)
- Decouple commands from BatchPredict
- Model needs rafactoring HOT 1
- Batch predictors HOT 1
- Batch predictors for DM HOT 1
- Fix dicoms orientation
- Replace snakefiles
- Remove `dataset_preprocessing`
- Rename LearningRatePolicy to something more general
- Probably should copy `resources.config` directly into `experiment_i`
- Potential challenges for a backup system HOT 7
- Checkpoint naming HOT 1
- PyramidalPooling layer warning
- map_ids_to_disk uses .npy extension HOT 2
- ExpirationPool doesn't work with non hashable objects
- the load_model_state function does not return nn.Module as stated in its prototype HOT 1
- Loky backend sometimes randomly mixes items
- Gradient scaler throws `AssertionError: No inf checks were recorded for this optimizer` in case of empty mask in `dpipe.torch.functional.masked_loss` HOT 4
- ModuleNotFoundError: No module named 'dpipe.medim' HOT 4
- PyramidPooling layer speed
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