We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Hi I am using pystruct to call opengm alpha-expansion module to train a graph crf. However, the program brokes with an error as following:
opengm/include/opengm/inference/auxiliary/minstcutkolmogorov.hxx:70: void opengm::external::MinSTCutKolmogorov<NType, VType>::addEdge(opengm::external::MinSTCutKolmogorov<NType, VType>::node_type, opengm::external::MinSTCutKolmogorov<NType, VType>::node_type, opengm::external::MinSTCutKolmogorov<NType, VType>::ValueType) [with NType = long unsigned int; VType = double; opengm::external::MinSTCutKolmogorov<NType, VType>::node_type = long unsigned int; opengm::external::MinSTCutKolmogorov<NType, VType>::ValueType = double]: Assertion `cost >= 0' failed.
However, if I switch to alpha-expansionfusion the program trains properly with same input. Is there a bug here?
The text was updated successfully, but these errors were encountered:
No branches or pull requests
Hi I am using pystruct to call opengm alpha-expansion module to train a graph crf. However, the program brokes with an error as following:
opengm/include/opengm/inference/auxiliary/minstcutkolmogorov.hxx:70: void opengm::external::MinSTCutKolmogorov<NType, VType>::addEdge(opengm::external::MinSTCutKolmogorov<NType, VType>::node_type, opengm::external::MinSTCutKolmogorov<NType, VType>::node_type, opengm::external::MinSTCutKolmogorov<NType, VType>::ValueType) [with NType = long unsigned int; VType = double; opengm::external::MinSTCutKolmogorov<NType, VType>::node_type = long unsigned int; opengm::external::MinSTCutKolmogorov<NType, VType>::ValueType = double]: Assertion `cost >= 0' failed.
However, if I switch to alpha-expansionfusion the program trains properly with same input. Is there a bug here?
The text was updated successfully, but these errors were encountered: