From 98abc0e5ac1a1da0fe1802d9ffb623802fbf0b2f Mon Sep 17 00:00:00 2001
From: jmwang66 <wangjiaming.wjm@alibaba-inc.com>
Date: 星期四, 29 六月 2023 16:30:39 +0800
Subject: [PATCH] update setup (#686)

---
 funasr/datasets/small_datasets/preprocessor.py |   11 -----------
 1 files changed, 0 insertions(+), 11 deletions(-)

diff --git a/funasr/datasets/small_datasets/preprocessor.py b/funasr/datasets/small_datasets/preprocessor.py
index d80f48a..0ebf325 100644
--- a/funasr/datasets/small_datasets/preprocessor.py
+++ b/funasr/datasets/small_datasets/preprocessor.py
@@ -10,8 +10,6 @@
 import numpy as np
 import scipy.signal
 import soundfile
-from typeguard import check_argument_types
-from typeguard import check_return_type
 
 from funasr.text.build_tokenizer import build_tokenizer
 from funasr.text.cleaner import TextCleaner
@@ -260,7 +258,6 @@
     def _speech_process(
             self, data: Dict[str, Union[str, np.ndarray]]
     ) -> Dict[str, Union[str, np.ndarray]]:
-        assert check_argument_types()
         if self.speech_name in data:
             if self.train and (self.rirs is not None or self.noises is not None):
                 speech = data[self.speech_name]
@@ -347,7 +344,6 @@
                 speech = data[self.speech_name]
                 ma = np.max(np.abs(speech))
                 data[self.speech_name] = speech * self.speech_volume_normalize / ma
-        assert check_return_type(data)
         return data
 
     def _text_process(
@@ -365,13 +361,11 @@
                 tokens = self.tokenizer.text2tokens(text)
             text_ints = self.token_id_converter.tokens2ids(tokens)
             data[self.text_name] = np.array(text_ints, dtype=np.int64)
-        assert check_return_type(data)
         return data
 
     def __call__(
             self, uid: str, data: Dict[str, Union[str, np.ndarray]]
     ) -> Dict[str, np.ndarray]:
-        assert check_argument_types()
 
         data = self._speech_process(data)
         data = self._text_process(data)
@@ -439,7 +433,6 @@
                 tokens = self.tokenizer.text2tokens(text)
             text_ints = self.token_id_converter.tokens2ids(tokens)
             data[self.text_name] = np.array(text_ints, dtype=np.int64)
-        assert check_return_type(data)
         return data
 
 
@@ -496,13 +489,11 @@
                 tokens = self.tokenizer.text2tokens(text)
                 text_ints = self.token_id_converter.tokens2ids(tokens)
                 data[text_n] = np.array(text_ints, dtype=np.int64)
-        assert check_return_type(data)
         return data
 
     def __call__(
             self, uid: str, data: Dict[str, Union[str, np.ndarray]]
     ) -> Dict[str, np.ndarray]:
-        assert check_argument_types()
 
         if self.speech_name in data:
             # Nothing now: candidates:
@@ -606,7 +597,6 @@
                 tokens = self.tokenizer[i].text2tokens(text)
                 text_ints = self.token_id_converter[i].tokens2ids(tokens)
                 data[text_name] = np.array(text_ints, dtype=np.int64)
-        assert check_return_type(data)
         return data
 
 
@@ -685,7 +675,6 @@
     def __call__(
             self, uid: str, data: Dict[str, Union[list, str, np.ndarray]]
     ) -> Dict[str, Union[list, np.ndarray]]:
-        assert check_argument_types()
         # Split words.
         if isinstance(data[self.text_name], str):
             split_text = self.split_words(data[self.text_name])

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