From 77e39f4eec98671ccdfd044823b86030cbfc7508 Mon Sep 17 00:00:00 2001
From: Hsien-Chin Lin <linh@hhu.de>
Date: Fri, 14 Apr 2023 11:37:49 +0200
Subject: [PATCH] fix typo
---
convlab/policy/emoUS/evaluate.py | 17 +++++++++--------
1 file changed, 9 insertions(+), 8 deletions(-)
diff --git a/convlab/policy/emoUS/evaluate.py b/convlab/policy/emoUS/evaluate.py
index bd97ab2b..a516f874 100644
--- a/convlab/policy/emoUS/evaluate.py
+++ b/convlab/policy/emoUS/evaluate.py
@@ -9,6 +9,7 @@ import torch
from datasets import load_metric
from sklearn import metrics
from tqdm import tqdm
+from pprint import pprint
from convlab.nlg.evaluate import fine_SER
from convlab.policy.emoUS.emoUS import UserActionPolicy
@@ -194,13 +195,13 @@ class Evaluator:
def dialog_result(self, dialog):
x = {"gen_acts": [], "golden_acts": [],
- "gen_emotions": [], "golden_emotions": []}
+ "gen_emotion": [], "golden_emotion": []}
for d in dialog:
x["gen_acts"].append(d["gen_acts"])
x["golden_acts"].append(d["golden_acts"])
- x["gen_emotions"].append(d["gen_emotion"])
- x["golden_emotions"].append(d["golden_emotion"])
+ x["gen_emotion"].append(d["gen_emotion"])
+ x["golden_emotion"].append(d["golden_emotion"])
return x
def semantic_evaluation(self, x):
@@ -246,8 +247,8 @@ class Evaluator:
self.evaluation_result["semantic action prediction"][metric] = score
if not golden_emotion and not golden_action:
- r = emotion_score(x["golden_emotions"],
- x["gen_emotions"],
+ r = emotion_score(x["golden_emotion"],
+ x["gen_emotion"],
self.model_checkpoint)
self.evaluation_result["emotion prediction"]["emotion"] = {}
self.evaluation_result["emotion prediction"]["emotion"]["macro_f1"] = r["macro_f1"]
@@ -260,9 +261,9 @@ class Evaluator:
else:
# transfer emotions to sentiment if the model do not generate sentiment
golden_sentiment = [self.emo2sent[emo]
- for emo in self.r["golden_emotions"]]
+ for emo in self.r["golden_emotion"]]
gen_sentiment = [self.emo2sent[emo]
- for emo in self.r["gen_emotions"]]
+ for emo in self.r["gen_emotion"]]
r = sentiment_score(
golden_sentiment,
gen_sentiment,
@@ -273,7 +274,7 @@ class Evaluator:
self.evaluation_result["emotion prediction"]["sentiment"]["sep_f1"] = {
emo: f1 for emo, f1 in zip(r["label"], r["sep_f1"])}
- print(self.evaluation_result)
+ pprint(self.evaluation_result)
# def save_results(self):
--
GitLab