Hi, I’m dealing with a weird problem which i cannot understand: to be short, i don’t understand why some lines of the minimal example below throws an `IndexError: too many indices for tensor of dimension 2`

:

```
N = 1000
D = 42
t = torch.randn(N, D) # the dataset (time series data)
W = 10
# these indices create windows to feed to e.g. an LSTM
indices = [ range(i, i + W) for i in range(0, N - W) ]
windowed_data = t[indices] # this works
windowed_data = t[indices[:100] ] # this works too
windowed_data = t[indices[:10] ] # IndexError, wtf?
windowed_data = t[indices[:32] ] # this works
windowed_data = t[indices[:31] ] # IndexError
```

The above code shows that this list indexing i’m doing works well if the `indices`

list is “long enough”, which seems to be above 32 of length, and throws an `IndexError`

below 31.

Context: I am storing a time series dataset composed of N instances of dimensionality D, as a tensor of shape (N,D), and i wrote code to “windowize” it into overlapping windows of W instances, to get it to a shape of (N,W,D).

I was doing some debugging in other parts of the code and stumbled upon this problem, which made me think that maybe i don’t understand tensor list indexing too wee.

Can someone with more experience explain why this behavior appears?