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When I ran the example in MONAI, I encountered this error. MONAI version 1.3.2 MetricsReloaded version 0.1.0 The example code is as follows:
import torch from monai.metrics import MetricsReloadedBinary metric_name = "Cohens Kappa" metric = MetricsReloadedBinary(metric_name=metric_name) y_pred = torch.tensor([[[[1.0, 0.0], [0.0, 1.0]]]]) y = torch.tensor([[[[1.0, 0.0], [1.0, 1.0]]]]) print(metric(y_pred, y)) y_pred = torch.tensor([[[[1.0, 0.0], [0.0, 0.0]]]]) y = torch.tensor([[[[1.0, 0.0], [1.0, 1.0]]]]) print(metric(y_pred, y)) print(metric.aggregate(reduction="none")) metric.reset()
The errors are as follows:
{ "name": "TypeError", "message": "BinaryPairwiseMeasures.__init__() got an unexpected keyword argument 'axis'", "stack": "--------------------------------------------------------------------------- TypeError Traceback (most recent call last) File /home/bowen/git/prostate/practice.py:13 11 y_pred = torch.tensor([[[[1.0, 0.0], [0.0, 1.0]]]]) 12 y = torch.tensor([[[[1.0, 0.0], [1.0, 1.0]]]]) ---> 13 print(metric(y_pred, y)) 15 # second iteration 16 # shape [batch=1, channel=1, 2, 2] 17 y_pred = torch.tensor([[[[1.0, 0.0], [0.0, 0.0]]]]) File ~/.conda/envs/pytorch/lib/python3.11/site-packages/monai/metrics/metric.py:347, in CumulativeIterationMetric.__call__(self, y_pred, y, **kwargs) 327 def __call__( 328 self, y_pred: TensorOrList, y: TensorOrList | None = None, **kwargs: Any 329 ) -> torch.Tensor | Sequence[torch.Tensor | Sequence[torch.Tensor]]: 330 \"\"\" 331 Execute basic computation for model prediction and ground truth. 332 It can support both `list of channel-first Tensor` and `batch-first Tensor`. (...) 345 a `batch-first` tensor (BC[HWD]) or a list of `batch-first` tensors. 346 \"\"\" --> 347 ret = super().__call__(y_pred=y_pred, y=y, **kwargs) 348 if isinstance(ret, (tuple, list)): 349 self.extend(*ret) File ~/.conda/envs/pytorch/lib/python3.11/site-packages/monai/metrics/metric.py:80, in IterationMetric.__call__(self, y_pred, y, **kwargs) 78 if isinstance(y_pred, torch.Tensor): 79 y_ = y.detach() if isinstance(y, torch.Tensor) else None ---> 80 return self._compute_tensor(y_pred.detach(), y_, **kwargs) 81 raise ValueError(\"y_pred or y must be a list/tuple of `channel-first` Tensors or a `batch-first` Tensor.\") File ~/.conda/envs/pytorch/lib/python3.11/site-packages/monai/metrics/wrapper.py:169, in MetricsReloadedBinary._compute_tensor(self, y_pred, y) 166 y = convert_to_numpy(y) 168 # Create binary pairwise metric object --> 169 bpm = BinaryPairwiseMeasures(y_pred, y, axis=tuple(range(2, dims)), smooth_dr=1e-5) 171 # Is requested metric available? 172 if self.metric_name not in bpm.metrics: TypeError: BinaryPairwiseMeasures.__init__() got an unexpected keyword argument 'axis'" }
The text was updated successfully, but these errors were encountered:
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When I ran the example in MONAI, I encountered this error.
MONAI version 1.3.2
MetricsReloaded version 0.1.0
The example code is as follows:
The errors are as follows:
The text was updated successfully, but these errors were encountered: