From 73258344b861da8a0111e408327b7dfd82825797 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CDaniel=20Griffiths=E2=80=9D?=
<Danielgriffiths1790@gmail.com>
Date: Thu, 4 Jan 2024 10:48:08 +0000
Subject: [PATCH] removed none types for mypy
---
semantic_router/encoders/tfidf.py | 14 +++++++++-----
1 file changed, 9 insertions(+), 5 deletions(-)
diff --git a/semantic_router/encoders/tfidf.py b/semantic_router/encoders/tfidf.py
index 394f32fb..68baceaa 100644
--- a/semantic_router/encoders/tfidf.py
+++ b/semantic_router/encoders/tfidf.py
@@ -7,16 +7,16 @@ import string
class TfidfEncoder(BaseEncoder):
- idf: dict | None = None
- word_index: dict | None = None
+ idf: np.ndarray
+ word_index: dict
def __init__(self, name: str = "tfidf"):
super().__init__(name=name)
- self.word_index = None
- self.idf = None
+ self.word_index = {}
+ self.idf = np.array([])
def __call__(self, docs: list[str]) -> list[list[float]]:
- if self.word_index is None or self.idf is None:
+ if len(self.word_index) == 0 or self.idf.size == 0:
raise ValueError("Vectorizer is not initialized.")
if len(docs) == 0:
raise ValueError("No documents to encode.")
@@ -43,6 +43,8 @@ class TfidfEncoder(BaseEncoder):
return word_index
def _compute_tf(self, docs: list[str]) -> np.ndarray:
+ if len(self.word_index) == 0:
+ raise ValueError("Word index is not initialized.")
tf = np.zeros((len(docs), len(self.word_index)))
for i, doc in enumerate(docs):
word_counts = Counter(doc.split())
@@ -54,6 +56,8 @@ class TfidfEncoder(BaseEncoder):
return tf
def _compute_idf(self, docs: list[str]) -> np.ndarray:
+ if len(self.word_index) == 0:
+ raise ValueError("Word index is not initialized.")
idf = np.zeros(len(self.word_index))
for doc in docs:
words = set(doc.split())
--
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