Fix: Validation of merged table for training data

If you consider all the duplicates, of course it doesn't work.

train_model.py

@@ -470,7 +470,7 @@ def prepare_long_form_data(jmh_data, features_data):
     merged_table = pd.merge(jmh_with_best, features_data_wide, on="benchmark_id")
 
     # I think there should be one row for each iteration of each benchmark
-    assert len(merged_table) == len(features_data.get(["benchmark_id", "iteration"])
+    assert len(merged_table) == len(features_data.get(["benchmark_id", "iteration"]).drop_duplicates())
 
     # Return data that should replace the original data.
     return { "data" : merged_table,