Network Tagging is ignored (PyTorch Backend)
Problem
Multiple instances of the same network are trained separately instead of only once, even though a tagging file is present. While the tagging file is parsed and used to download the dataset, it is not used to determine, which network instances have to be trained (see method de.monticore.mlpipelines.workflow.AbstractWorkflow.getNetworkInstanceConfigs
). This requires the provision of one training and one pipeline configuration file per network instance.
Steps to reproduce
Note: Getting far enough to trigger this problem requires implementing the workaround presented in issue #123, given that it is not yet solved.
Execute the EMADL2CPP generator on the MNISTCalculator example application located in src/main/resources/calculator_experiment
.
For this purpose, use the following Run Configuration:
- Main class:
de.monticore.lang.monticar.emadl.generator.MontiAnnaCli
- Program arguments:
-m src/main/resources/calculator_experiment/emadl -r calculator.Connector -o target -b PYTORCH