From 3b0092f8fb3e0d79d1f328f91a251e9db8f6d1be Mon Sep 17 00:00:00 2001
From: Hsien-Chin Lin <linh@hhu.de>
Date: Fri, 14 Apr 2023 14:03:34 +0200
Subject: [PATCH] fix bug
---
convlab/policy/emoUS/evaluate.py | 25 ++++++-------------------
1 file changed, 6 insertions(+), 19 deletions(-)
diff --git a/convlab/policy/emoUS/evaluate.py b/convlab/policy/emoUS/evaluate.py
index 1e75e58f..df3f64de 100644
--- a/convlab/policy/emoUS/evaluate.py
+++ b/convlab/policy/emoUS/evaluate.py
@@ -195,21 +195,10 @@ class Evaluator:
acts.append([intent, domain])
return acts
- def dialog_result(self, dialog):
- x = {"gen_acts": [], "golden_acts": [],
- "gen_emotion": [], "golden_emotion": []}
-
- for d in dialog:
- x["gen_acts"].append(d["gen_acts"])
- x["golden_acts"].append(d["golden_acts"])
- x["gen_emotion"].append(d["gen_emotion"])
- x["golden_emotion"].append(d["golden_emotion"])
- return x
-
- def semantic_evaluation(self, x):
+ def semantic_evaluation(self, gen_acts, golden_acts):
scores = {"full action": {"precision": [], "recall": [], "f1": [], "turn_acc": []},
"intent-domain": {"precision": [], "recall": [], "f1": [], "turn_acc": []}}
- for gen_act, golden_act in zip(x["gen_acts"], x["golden_acts"]):
+ for gen_act, golden_act in zip(gen_acts, golden_acts):
s = f1_measure(preds=gen_act, labels=golden_act)
for metric in scores["full action"]:
scores["full action"][metric].append(s[metric])
@@ -234,22 +223,20 @@ class Evaluator:
else:
print("You must specify the input_file or the generated_file")
- gen_file = json.load(open(generated_file))
-
r = self.nlg_evaluation(
self.r["golden_utts"], self.r["gen_utts"], self.r["gen_acts"])
for metric, score in r.items():
self.evaluation_result["natural language generation"][metric] = score
- x = self.dialog_result(gen_file['dialog'])
if not golden_action:
- r = self.semantic_evaluation(x)
+ r = self.semantic_evaluation(
+ self.r["gen_acts"], self.r["golden_acts"])
for metric, score in r.items():
self.evaluation_result["semantic action prediction"][metric] = score
if not golden_emotion and not golden_action:
- r = emotion_score(x["golden_emotion"],
- x["gen_emotion"],
+ r = emotion_score(self.r["golden_emotion"],
+ self.r["gen_emotion"],
self.result_dir)
self.evaluation_result["emotion prediction"]["emotion"] = {}
self.evaluation_result["emotion prediction"]["emotion"]["macro_f1"] = r["macro_f1"]
--
GitLab