code: def fbeta(y_pred:Tensor, y_true:Tensor, thresh:float=0.2, beta:float=2, eps:float=1e-9, sigmoid:bool=True)->Rank0Tensor:
      "Computes the f_beta between `preds` and `targets`"
      beta2 = beta ** 2
      if sigmoid: y_pred = y_pred.sigmoid()
      y_pred = (y_pred>thresh).float()
      y_true = y_true.float()
      TP = (y_pred*y_true).sum(dim=1)
      prec = TP/(y_pred.sum(dim=1)+eps)
      rec = TP/(y_true.sum(dim=1)+eps)
      res = (prec*rec)/(prec*beta2+rec+eps)*(1+beta2)
      return res.mean(f fbeta(y_pred:Tensor, y_true:Tensor, thresh:float=0.2, beta:float=2, eps:float=1e-9, sigmoid:bool=True)->Rank0Tensor:
      "Computes the f_beta between `preds` and `targets`"
      beta2 = beta ** 2
      if sigmoid: y_pred = y_pred.sigmoid()
      y_pred = (y_pred>thresh).float()
      y_true = y_true.float()
      TP = (y_pred*y_true).sum(dim=1)
      prec = TP/(y_pred.sum(dim=1)+eps)
      rec = TP/(y_true.sum(dim=1)+eps)
      res = (prec*rec)/(prec*beta2+rec+eps)*(1+beta2)
      return res.mean()
docs: Computes the f_beta between `preds` and `targets`