Ah, thanks for catching that silly error. It should be idx+i, then. Doing so should hopefully give me the correct shape. I must have a fundamental misunderstanding of what’s actually happening here. After making the change in the getitem method of the custom dataset to:

def getitem(self, idx):
data = torch.zeros(100, 2)
for i in range(0, 100):
data[i] = torch.tensor(self.oudataframe.iloc[idx+i,0:])
return data

and subsequently attempting to check shape via:

dataloader = DataLoader(dataSet, batch_size=20, shuffle=False)
data, target = next(iter(dataloader))
print(data.shape)
print(target.shape)

I get:

data, target = next(iter(dataloader))
ValueError: too many values to unpack (expected 2)

It seems that I am not actually returning what I think I am, or my syntax is incorrect.
Edit:
After setting a test variable to dataSet[0], the shape of the test variable is indeed [100,2].
However, I don’t seem to be understanding how to iterate properly through the newly created dataloader object. Any insights?