Hi can I have some help with this problem.
I defined two data loaders which has the same length
and with
trainer.fit(model,
[loader1, loader2]
...)
int the
def training_step(self, batch, batch_idx): # type: ignore
if some_condition:
out_1 = forward(batch[0])
out_2 = forward(batch[1])
loss = my_loss_function(out_1, out_2)
return loss
then I see there are two problems compared with using only one loader:
1, the training speed is about 5 times slower than before
2. the training is stuck in the epoch 1 and never get out
Training -> Epoch 1, batch 71120: running loss = 0.003,
(there are very small training examples in there actually. With one data loader, it finish within 10 batches.)
Thanks