model.train()
for epoch in range(num_epoch):
loss_hist.reset()
for i, (images, targets, ImageIDs) in enumerate(train_loader):
images = list(image.to(device) for image in images)
targets = [{k: v.to(device) for k, v in t.items()} for t in targets]
loss_dict = model(images, targets)
losses = sum(loss for loss in loss_dict.values())
loss_value = losses.item()
loss_hist.send(loss_value)
optimizer.zero_grad()
losses.backward()
optimizer.step()
if itr % 500 == 0:
print(f"Iteration #{itr} loss: {loss_value}")
itr += 1
if lr_scheduler is not None:
lr_scheduler.step()
print(f"Epoch #{epoch} loss: {loss_hist.value}")
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22/06/22 15:00:54 WARN WindowExec: No Partition Defined for Window operation! Moving all data to a single partition, this can cause serious performance degradation.