Hi, I usually index tensors with lists of indices, like
x = torch.as_tensor([[1,2,3,4,5], [6,7,8,9,0]])
index = [[0, 1, 1], [1, 1, 2]]
# tensor([2, 7, 8])
x[index]

Now I need index to be a tensor object, but doing this, I get an error:
x = torch.as_tensor([[1,2,3,4,5], [6,7,8,9,0]])
index = torch.as_tensor( [[0, 1, 1], [1, 1, 2]])
# IndexError: index 2 is out of bounds for dimension 0 with size 2
x[index]

I don’t know if it is expected to work differently, but a numpy array behaves like the list:
x = torch.as_tensor([[1,2,3,4,5], [6,7,8,9,0]])
index = [[0, 1, 1], [1, 1, 2]]
index_n = numpy.asarray(index)
index_t = torch.as_tensor(index)

# tensor([2, 7, 8])
x[index]
# tensor([2, 7, 8])
x[index_n]
# IndexError: index 2 is out of bounds for dimension 0 with size 2
x[index_t]

How can I get the same output using a tensor instead of a list?