Silenced exception makes it harder to debug custom Transforms about torchio HOT 5 CLOSED

import numpy as np
import torch
from torch.utils.data import DataLoader
from torchio.data.sampler.label import LabelSampler
from torchio import DATA, TYPE, LABEL, INTENSITY, IntensityTransform

class SimulateLowResolutionTransform(IntensityTransform):
    def __init__(self):
        super().__init__(1)

    def apply_transform(self, subject):
        keys = sorted(subject.keys())
        for key in keys:
                subject[key][DATA] = subject[key][DATA].unsqueeze(0)
        return subject

if __name__ == "__main__":
    import torchio as tio
    st = SimulateLowResolutionTransform()
    colin_dataset = tio.datasets.mni.Colin27()
    ds_train = tio.SubjectsDataset([colin_dataset], transform=st)
    sampler = LabelSampler((120, 120, 80))
    patches_queue_train = tio.Queue(ds_train, max_length=32, samples_per_volume=4, sampler=sampler,
                                    shuffle_patches=True, shuffle_subjects=True, num_workers=8)

    training_loader = DataLoader(patches_queue_train, batch_size=2, shuffle=True)
    for batch in training_loader:
        print(batch["t1"][DATA].shape)