Hi,

Let’s say I have a tensor with shape (32,), e.g.

```
X = [ 0.0379, -0.0372, 0.0277, -0.1918, -0.0679, 0.0858, 0.0655, 0.2807,
-0.1375, -0.0066, 0.1309, 0.0893, 0.0757, 0.1891, 0.2998, -0.1810,
-0.0809, 0.1543, -0.0852, -0.1351, 0.0900, -0.1985, -0.0525, 0.0582,
0.0410, 0.3986, 0.3757, 0.2447, -0.3319, -0.2319, -0.0495, -0.0034]
```

I’m seeking how to convert X into a (32, 100) tensor where 100 is the dimension of a one-hot encoding.

I know that values range between [-1, 1].

I would like to discretise this interval in 100 bins and place a 1 in the bin the value corresponds to, and 0 elsewhere.

Is it possible to do this efficiently with pytorch?

Thanks