How to use 'keras confusion matrix' in Python

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17def numpy(self):
18 return self._matrix.numpy()

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4def th_confusion_matrix(y_true: torch.Tensor, y_pred: torch.Tensor, num_classes=None):
5 """
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:
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:]

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