"cache": cache,
"cache_valid": cache_valid,
"cache_test": cache_test,
"value_model": value_model,
"value_model_valid": value_model_valid,
"value_model_test": value_model_test,
"attribute": attribute,
"selection_criterion": args.selection_criterion,
}
if args.log_wandb:
runner_config["wandb_run"] = run
total_dims = reader.get_dimensionality()
runner = Runner(runner_config)
selected_results = runner.main_loop(max_iter=args.max_iter)
# Draw graphs
graphs = runner.draw_graphs(selected_results)
mi_fig = graphs["mi"]
normalized_mi_fig = graphs["normalized_mi"]
accuracy_fig = graphs["accuracy"]
scatter_fig = runner.plot_dims(
selected_results[0]["candidate_dim"],
selected_results[1]["candidate_dim"],
test_data=True,
log_prob_dim_pool=list(selected_results[-1]["candidate_dim_pool"]))
# You can uncomment these lines to output scatter plots for any pair of dimensions you need.
#
# scatter_fig = runner.plot_dims(477, 179, test_data=True)
