# How to generate following tensor?

Whats the most efficient way to generate a tensor like below?

[[0, 0],
[0, 1],
[0, 2],

[0, X],
[1, 0],

[1, X],

[X, X]]

Not at my computer to test, but maybe something like this?

``````tens_list = list()
for x in range(10):
for y in range(100):
tens_list.append((x, y))
tens = torch.tensor(tens_list, [data types if needed])
``````

I was trying to avoid for-loops if possible.

For aesthetic or functional reasons? If aesthetics, the following is equivalent to the for loop implementation above:

``````tens_list = [(x, y) for x in range(10) for y in range(100)]
``````

If functional, I’m not sure what the fastest method would be. I’d guess that creating a “template” object with something like the above and then generating a new tensor from it as needed elsewhere in your code would be a contender for “fastest”. Unfortunately, I’m pretty new at all this stuff, so I could be way off…

I mean I was thinking if I can use some builtin pytorch functions rather than looping myself.

Maybe something like this ?

``````l = torch.arange(X+1)
r = torch.arange(X+1)

l = l.view(X+1, 1).repeat(1, X+1).view((X+1) * (X+1))
r = r.view(1, X+1).repeat(X+1, 1).view((X+1) * (X+1))

m = torch.stack([l, r], 1)
``````
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