Given a matrix `A`

, say:

```
A = torch.randn(5,5)
```

What is the difference between `A.T`

and `A.t()`

?

Given a matrix `A`

, say:

```
A = torch.randn(5,5)
```

What is the difference between `A.T`

and `A.t()`

?

From the docs:

`tensor.t`

:

Expects

`input`

to be <= 2-D tensor and transposes dimensions 0 and 1.

0-D and 1-D tensors are returned as is. When input is a 2-D tensor this is equivalent to`transpose(input, 0, 1)`

.

Returns a view of this tensor with its dimensions reversed.

If`n`

is the number of dimensions in`x`

,`x.T`

is equivalent to`x.permute(n-1, n-2, ..., 0)`

.

In your use case both will yield the same result.

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