I have two tensors

```
t1 = torch.tensor([ 1, 9, 12, 5, 24])
t2 = torch.tensor([ 1, 24])
```

Now, I want to extend the tensor `t2`

to the same size as `t1`

.

How can I do this without using loops?

I have two tensors

```
t1 = torch.tensor([ 1, 9, 12, 5, 24])
t2 = torch.tensor([ 1, 24])
```

Now, I want to extend the tensor `t2`

to the same size as `t1`

.

How can I do this without using loops?

hmmm you can do this:

`t2.data.resize_(t1.size()).copy_(t1)`

or this

`t2.data.resize_(t1.size()).copy_(t2)`

but im not sure what do you mean by extending, because when the size change the values need to change too. so what do you want the elements of t2 to be?

Maybe you can use the `repeat`

function.

Sorry for not being completely clear about my requirement.

I want to extend the tensor `t2`

to be the same size as `t1`

where the “extra values that need to be filled in t2” can be some unique number that is currently not in `t2`

. For instance,

`t2 = torch.tensor([ 1, 24, 0, 0, 0])`

I tried it with

`t2.data.resize_as_(t1)`

That sort of works but it doesn’t give the flexibility to fill in using our own values.