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When I test my own model, some datasets work fine, but the univ dataset reports errors. The specific error message is as follows. #68

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@Jasmine302

Traceback (most recent call last):
File "test.py", line 195, in
ad,fd,raw_data_dic_= test()
File "test.py", line 69, in test
mvnormal = torchdist.MultivariateNormal(mean,cov)
File "/home/jnu/anaconda3/envs/xxq/lib/python3.7/site-packages/torch/distributions/multivariate_normal.py", line 146, in init
super(MultivariateNormal, self).init(batch_shape, event_shape, validate_args=validate_args)
File "/home/jnu/anaconda3/envs/xxq/lib/python3.7/site-packages/torch/distributions/distribution.py", line 56, in init
f"Expected parameter {param} "
ValueError: Expected parameter covariance_matrix (Tensor of shape (12, 57, 2, 2)) of distribution MultivariateNormal(loc: torch.Size([12, 57, 2]), covariance_matrix: torch.Size([12, 57, 2, 2])) to satisfy the constraint PositiveDefinite(), but found invalid values:
tensor([[[[ 1.2511e-11, 2.6965e-10],
[ 2.6965e-10, 5.8116e-09]],

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