How to use 'keras confusion matrix' in Python
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16 @property 17 def numpy(self): 18 return self._matrix.numpy()
4 def th_confusion_matrix(y_true: torch.Tensor, y_pred: torch.Tensor, num_classes=None): 5 """ 6 7 Args: 8 y_true: 1-D tensor of shape [n_samples] 9 y_pred: 1-D tensor of shape [n_samples] 10 num_classes: scalar 11 Returns: 12 13 """ 14 size = [num_classes + 1, num_classes + 1] if num_classes is not None else None 15 y_true = y_true.float() 16 y_pred = y_pred.float() 17 if size is None: 18 cm = torch.sparse_coo_tensor(indices=torch.stack([y_true, y_pred], dim=0), values=torch.ones_like(y_pred)) 19 else: 20 cm = torch.sparse_coo_tensor(indices=torch.stack([y_true, y_pred], dim=0), values=torch.ones_like(y_pred), 21 size=size) 22 return cm.to_dense()[1:, 1:]