Unify metrics output type

🚀 Feature

The idea is to verify the output type for all metrics (output of compute function) and update the docs accordingly.

In general, metric’s output should be a float number. In some particular cases, like Recall/Precision with average=False, the output is a torch tensor. So, let’s see and decide if the output of compute() method can be :

• def compute() -> float
• def compute() -> Union[float, torch.Tensor] and tensor is on CPU
• def compute() -> torch.Tensor with tensor on CPU

To address this FR, we have to make sure for each metric what kind of type it supposes to return and update the docs accordingly.

[sdesrozis]

IMHO handle an unique type could simplify the underlying code. If no issue about performance occurs, I would prefer have torch.tensor (compatible with float) rather than union of types.

But maybe it’s because I’m too lazy 😊

[liebkne]

I think as a workaround you can omit this argument and by default it will be cpu.

Didn’t know this, thanks. Since the day I switched to idist, I turned everything related to idist.xxx. 😅