Added data conversion scripts.

[frobnitzem]

These scripts outline the general format for working will all csv file types.

I will add to this PR as I test these general scripts on multiple data sources.

[frobnitzem]

yaml_to_config.py needs checking to ensure that it's selecting the right variables for compatibility with other datasets used to train the foundational model, and also to check the indexing it uses for graph output properties.

Specifically, it now contains:

      "input_node_feature_names": [
        "atomC",
        "atomF",
        "atomH",
        "atomN",
        "atomO",
        "atomS",
        "atomHg",
        "atomCl",
        "atomicnumber",
        "IsAromatic",
        "HSP",
        "HSP2",
        "HSP3",
        "Hprop"
      ],

But likely we can't use all these. How should yaml_to_config be modified?

[frobnitzem]

Several steps need to be done before this is ready to merge:

• implement config.json reader according to data.md
  • check that these files are correctly generated by the present PR (utils/yaml_to_config.py)
  • update the output head configuration (see below)
  • test data loading from AdiosDataset with new feature selectors
• add classification loss head type to HydraGNN
  use sigmoid as activation function at the last layer (only needed if we end with an activation, since torch's cross-entropy converts (-inf, inf) to logits.
  use binary cross entropy as loss function for training, validation, and testing
• update data loading (from AdiosDataset) so that metadata is used to target which features go into x and y (need to select only some columns when going from data file to in-memory format)