I have a custom Python function, which has several parameters and performs some logic. It only uses native Python functions or Numpy functions:

```
def my_function(param_1, param_2, ..., param_N):
# Logic
...
return output
```

I want to speed up my function execution by using GPUs and passing a torch batch to this function instead of individual parameters. I could pass a numpy array to this function instead of individual parameters and `ravel()`

the entries into variables inside the function. But I dont know how to go from here to passing a whole batch of data and process it as a batch.

Is this possible? Do I need to use only `torch`

functions instead of numpy?