Hello,

Please can someone explain the two arguements in torch.randn(). Refer to the example is below:

```
a = torch.randn(1, 3)
a
tensor([[0.0146, 0.4258, 0.2211]])
```

Hello,

Please can someone explain the two arguements in torch.randn(). Refer to the example is below:

```
a = torch.randn(1, 3)
a
tensor([[0.0146, 0.4258, 0.2211]])
```

Hey,

The arguments your **randn** function specify the shape of the Tensor you want to populate with random values.

So, (1,3) would be Tensor shaped as such -

[

[a, b, c ]

]

Similarly, a tensor with shape (2,3) would be -

[

[a, b, c],

[x, y, z]

]

And a tensor with a shape (1,2) -

[

[a, b]

]

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They are the dimensions of the tensor. rows x columns

1 Like

```
a = torch.randn(Rows, Columns)
```

The first argument defines the number of rows and the second defines the number of columns in your tensor.

1 Like

Row, Column. torch.randn() generate random numbers

1 Like