Refactor logprobs computation

Author: Marcin Kardas

sota_extractor2/models/linking/context_search.py

@@ -110,17 +110,12 @@ def compute_logprobs(taxonomy, reverse_merged_p, reverse_metrics_p, reverse_task
     for i, (task, dataset, metric) in enumerate(taxonomy):
         logprob = 0.0
         short_probs = reverse_merged_p.get(dataset, empty)
-        met_probs = reverse_metrics_p.get(metric, empty)
-        task_probs = reverse_task_p.get(task, empty)
         for ds in dss:
-            #                 for abbrv, long_form in abbrvs.items():
-            #                     if ds == abbrv:
-            #                         ds = long_form
-            #                         break
-            # if merged_p[ds].get('NOMATCH', 0.0) < 0.5:
             logprob += np.log(noise * ds_pb + (1 - noise) * short_probs.get(ds, 0.0))
+        met_probs = reverse_metrics_p.get(metric, empty)
         for ms in mss:
             logprob += np.log(ms_noise * ms_pb + (1 - ms_noise) * met_probs.get(ms, 0.0))
+        task_probs = reverse_task_p.get(task, empty)
         for ts in tss:
             logprob += np.log(ts_noise * ts_pb + (1 - ts_noise) * task_probs.get(ts, 0.0))
         logprobs[i] += logprob