def METHOD_NAME():
    with pytest.raises(ValueError, match=r"Argument num_features must be greater to zero, got:"):
        InceptionScore(num_features=-1, feature_extractor=torch.nn.Identity()).update(torch.rand(2, 0))
    with pytest.raises(ValueError, match=r"feature_extractor output must be a tensor of dim 2, got: 1"):
        InceptionScore(num_features=1000, feature_extractor=torch.nn.Identity()).update(torch.rand(3))
    with pytest.raises(ValueError, match=r"Batch size should be greater than one, got: 0"):
        InceptionScore(num_features=1000, feature_extractor=torch.nn.Identity()).update(torch.rand(0, 0))
    with pytest.raises(ValueError, match=r"num_features returned by feature_extractor should be 1000, got: 0"):
        InceptionScore(num_features=1000, feature_extractor=torch.nn.Identity()).update(torch.rand(2, 0))
    with pytest.raises(
        NotComputableError, match=r"InceptionScore must have at least one example before it can be computed."
    ):
        InceptionScore(num_features=1000, feature_extractor=torch.nn.Identity()).compute()
    with pytest.raises(ValueError, match=r"Argument num_features must be provided, if feature_extractor is specified."):
        InceptionScore(feature_extractor=torch.nn.Identity())