From c4105a1e6f436a53fc66ee11a1e61419ab1be36e Mon Sep 17 00:00:00 2001
From: Fanyou Wu <fanyou.wu@outlook.com>
Date: Mon, 17 Jun 2024 00:26:34 -0400
Subject: [PATCH] Text simple qa
---
models/v4.py | 61 +++++++++++++++++++++++++---------------------------
1 file changed, 29 insertions(+), 32 deletions(-)
diff --git a/models/v4.py b/models/v4.py
index 1c9770b..1f737f5 100644
--- a/models/v4.py
+++ b/models/v4.py
@@ -142,11 +142,12 @@ class V4(Base):
def batch_generate_answer(self, batch: Dict, return_dict: bool = False):
if not return_dict:
- queries = [str(x) for x in batch["query"]]
+ queries = batch["query"]
+ print(queries)
+
final_answers_flag = [False] * len(queries)
final_answers = [""] * len(queries)
- # Check if the question type is other or not.
question_type = self.query_type_by_llm(queries, final_answers_flag)
is_not_other = [x != "other" for x in question_type]
final_answers_flag, final_answers = self.fillin_answer_with_flag(
@@ -212,12 +213,6 @@ class V4(Base):
]
output = [x.lower() for x in output]
-
- # print("after final_answers")
- # print("final_answers_flag", final_answers_flag)
- # print("final_answers", final_answers)
- # print("-----")
-
return output
else:
@@ -332,34 +327,36 @@ class V4(Base):
def simple_qa(
self, queries: List[str], domains: List[str], skip_flag: List[bool]
) -> List[str]:
- try:
- not_skip = [(d == "movie") and (not s) for d, s in zip(domains, skip_flag)]
- contain_keywords = [
- check_keywords(x, ["oscar", "academy", "award"]) for x in queries
- ]
- skip = [(not x) or (not y) for x, y in zip(not_skip, contain_keywords)]
+
+ # not_skip = [(d == "movie") and (not s) for d, s in zip(domains, skip_flag)]
+ # contain_keywords = [
+ # check_keywords(x, ["oscar", "academy", "award"]) for x in queries
+ # ]
+ # skip = [(not x) or (not y) for x, y in zip(not_skip, contain_keywords)]
- inputs = [
- self.template.format(context={"query": query}, template="simple_qa")
- for query in queries
- ]
+ skip = [False] * len(queries)
- responses = self.llm_inference_with_skip_flag(
- inputs,
- skip,
- max_tokens=96,
- stop=["<|eot_id|>"],
- include_stop_str_in_output=False,
- )
+ inputs = [
+ self.template.format(context={"query": query}, template="simple_qa")
+ for query in queries
+ ]
- answers = [
- response.outputs[0].text if response else "" for response in responses
- ]
+ responses = self.llm_inference_with_skip_flag(
+ inputs,
+ skip,
+ max_tokens=64,
+ stop=["<|eot_id|>"],
+ include_stop_str_in_output=False,
+ )
- answers = [x.lower().strip() for x in answers]
- return answers
- except:
- return [""] * len(queries)
+ answers = [
+ response.outputs[0].text if response else "" for response in responses
+ ]
+
+ answers = [x.lower().strip() for x in answers]
+ print(answers)
+ exit()
+ return answers
def query_type_by_llm(self, queries: List[str], skip_flag: List[bool]) -> List[str]:
inputs = [
--
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