Hello, I have this problem, how can I solve it?
File "/usr/local/bin/nnUNet_train", line 33, in
sys.exit(load_entry_point('nnunet', 'console_scripts', 'nnUNet_train')())
File "/content/drive/MyDrive/nnUNetframe/nnUNet/nnunet/run/run_training.py", line 179, in main
trainer.run_training()
File "/content/drive/MyDrive/nnUNetframe/nnUNet/nnunet/training/network_training/nnUNetTrainerV2.py", line 440, in run_training
ret = super().run_training()
File "/content/drive/MyDrive/nnUNetframe/nnUNet/nnunet/training/network_training/nnUNetTrainer.py", line 317, in run_training
super(nnUNetTrainer, self).run_training()
File "/content/drive/MyDrive/nnUNetframe/nnUNet/nnunet/training/network_training/network_trainer.py", line 456, in run_training
l = self.run_iteration(self.tr_gen, True)
File "/content/drive/MyDrive/nnUNetframe/nnUNet/nnunet/training/network_training/nnUNetTrainerV2.py", line 247, in run_iteration
output = self.network(data)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/content/drive/MyDrive/nnUNetframe/nnUNet/nnunet/network_architecture/generic_UNet.py", line 441, in forward
tempXX=GaussianMixture(n_components, tempX.size()[1]).fit(tempX)
File "/content/drive/MyDrive/nnUNetframe/nnUNet/nnunet/network_architecture/gmm.py", line 150, in fit
self.log_likelihood = self.__score(x)
File "/content/drive/MyDrive/nnUNetframe/nnUNet/nnunet/network_architecture/gmm.py", line 396, in __score
weighted_log_prob = self._estimate_log_prob(x) + torch.log(self.pi)
File "/content/drive/MyDrive/nnUNetframe/nnUNet/nnunet/network_architecture/gmm.py", line 270, in _estimate_log_prob
log_det = self._calculate_log_det(precision)
File "/content/drive/MyDrive/nnUNetframe/nnUNet/nnunet/network_architecture/gmm.py", line 309, in _calculate_log_det
log_det[k] = 2 * torch.log(torch.diagonal(torch.linalg.cholesky(var[0, k]))).sum()
RuntimeError: "cholesky_cusolver" not implemented for 'Half'
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ldeecke
