def _sk_cohen_kappa_multidim_multiclass(preds, target, weights=None):
sk_preds = preds.view(-1).numpy()
sk_target = target.view(-1).numpy()
return sk_cohen_kappa(y1=sk_target, y2=sk_preds, weights=weights)
def _sk_cohen_kappa_multilabel_prob(preds, target, weights=None):
sk_preds = (preds.view(-1).numpy() >= THRESHOLD).astype(np.uint8)
sk_target = target.view(-1).numpy()
return sk_cohen_kappa(y1=sk_target, y2=sk_preds, weights=weights)
def _sk_cohen_kappa_multidim_multiclass_prob(preds, target, weights=None):
sk_preds = torch.argmax(preds, dim=len(preds.shape) - 2).view(-1).numpy()
sk_target = target.view(-1).numpy()
return sk_cohen_kappa(y1=sk_target, y2=sk_preds, weights=weights)
def _sk_cohen_kappa_binary(preds, target, weights=None):
sk_preds = preds.view(-1).numpy()
sk_target = target.view(-1).numpy()
return sk_cohen_kappa(y1=sk_target, y2=sk_preds, weights=weights)
