eurosat multiband classification problem

i have a problem running torchgeo on eurosat MS tif images i wrote a simple code :

eurosat = EuroSAT(euro_root, split="train", download=False)
# sampler = RandomGeoSampler(eurosat, size=64, length=10000)
# dataloader = DataLoader(eurosat, batch_size=128, sampler=sampler, collate_fn=stack_samples)
dataloader = DataLoader(eurosat, batch_size=128, collate_fn=stack_samples)
num_classes = 10
channels = 13
num_workers = 4
batch_size = 4
backbone = "resnet50"
weights = "imagenet"
lr = 0.01
lr_schedule_patience = 5
epochs = 50
datamodule = EuroSATDataModule(
     root_dir=euro_root,
     batch_size=batch_size,
     num_workers=num_workers,
)
task = ClassificationTask(
    classification_model=backbone,
    weights=weights,
    num_classes=num_classes,
    in_channels=channels,
    loss="ce",
    learning_rate=lr,
    learning_rate_schedule_patience=lr_schedule_patience
)
checkpoint_callback = pl.callbacks.ModelCheckpoint(
    monitor="val_loss",
    save_top_k=1,
    save_last=True,
)
early_stopping_callback = pl.callbacks.EarlyStopping(
    monitor="val_loss",
    min_delta=0.00,
    patience=10,
)

# Train
trainer = pl.Trainer(
    callbacks=[checkpoint_callback, early_stopping_callback],
    max_epochs=epochs
)
trainer.fit(model=task, datamodule=datamodule)

but i get this error on fit line :

.........
_pickle.PicklingError: Can't pickle <class 'nn.BatchNorm2d.BatchNorm2d'>: import of module 'nn.BatchNorm2d' failed
..........
OSError: [Errno 22] Invalid argument: 'C:\\Users\\mohsc\\PycharmProjects\\pythonProject\\<input>'

am i missing a preparing step or something ? help would be appreciated, by the way tutorials are still lacking essential sample codes and documentations like this issue on MS images. thanks

[mohscorpion]

This is likely a multiprocessing issue. The reason @calebrob6 can’t reproduce this is because multiprocessing uses a different start method on macOS/Windows vs. Linux: https://docs.python.org/3/library/multiprocessing.html#contexts-and-start-methods

If I’m correct, I should be able to reproduce this on macOS. Let me give it a shot.

i will try on linux and report back

[adamjstewart]

This is likely a multiprocessing issue. The reason @calebrob6 can’t reproduce this is because multiprocessing uses a different start method on macOS/Windows vs. Linux: https://docs.python.org/3/library/multiprocessing.html#contexts-and-start-methods

If I’m correct, I should be able to reproduce this on macOS. Let me give it a shot.