tenset
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graph embedding
Add back the graph embedding script that was removed from the last PR. To generate workload embeddings for the tasks, run
python3 graph_embedding.py
and in mlp_model.py or xgb_model.py, replace
tmp_task_embedding = get_workload_embedding(task.workload_key)
with
tmp_task_embeddings = pickle.load(open("task_embeddings.pkl", 'rb'))
tmp_task_embedding = tmp_task_embeddings[json.loads(task.workload_key)[0]]
and modify the dimensions accordingly. Note that I include two different embedding models in this script, but they are not super useful for improving the model performance. Including here to provide some food for thought.