Fix code style

.flake8

@@ -5,6 +5,7 @@ max-line-length = 80
 per-file-ignores =
     # line too long
     egs/librispeech/ASR/*/conformer.py: E501,
+    egs/aishell/ASR/*/conformer.py: E501,
 
 exclude =
   .git,

docs/source/recipes/aishell/conformer_ctc.rst

@@ -107,7 +107,7 @@ The following options are used quite often:
     It is the number of epochs to train. For instance,
     ``./conformer_ctc/train.py --num-epochs 30`` trains for 30 epochs
     and generates ``epoch-0.pt``, ``epoch-1.pt``, ..., ``epoch-29.pt``
-    in the folder set with ``--exp-dir``.
+    in the folder set by ``--exp-dir``.
 
   - ``--start-epoch``
 

egs/aishell/ASR/conformer_ctc/conformer.py

@@ -453,7 +453,6 @@ class RelPositionMultiheadAttention(nn.Module):
 
         self._reset_parameters()
 
-
     def _reset_parameters(self) -> None:
         nn.init.xavier_uniform_(self.in_proj.weight)
         nn.init.constant_(self.in_proj.bias, 0.0)
@@ -683,7 +682,6 @@ class RelPositionMultiheadAttention(nn.Module):
                 _b = _b[_start:]
             v = nn.functional.linear(value, _w, _b)
 
-
         if attn_mask is not None:
             assert (
                 attn_mask.dtype == torch.float32

egs/aishell/ASR/local/prepare_char.py

@@ -33,10 +33,9 @@ and generates the following files in the directory `lang_dir`:
     - tokens.txt
 """
 
-import argparse
 import re
 from pathlib import Path
-from typing import Dict, List, Tuple
+from typing import Dict, List
 
 import k2
 import torch
@@ -87,7 +86,9 @@ def lexicon_to_fst_no_sil(
         cur_state = loop_state
 
         word = word2id[word]
-        pieces = [token2id[i] if i in token2id else token2id['<unk>'] for i in pieces]
+        pieces = [
+            token2id[i] if i in token2id else token2id["<unk>"] for i in pieces
+        ]
 
         for i in range(len(pieces) - 1):
             w = word if i == 0 else eps
@@ -136,7 +137,7 @@ def contain_oov(token_sym_table: Dict[str, int], tokens: List[str]) -> bool:
       otherwise False.
     """
     for tok in tokens:
-        if not tok in token_sym_table:
+        if tok not in token_sym_table:
             return True
     return False
 
@@ -178,18 +179,18 @@ def generate_tokens(text_file: str) -> Dict[str, int]:
       from 0 to len(keys) - 1.
     """
     tokens: Dict[str, int] = dict()
-    tokens['<blk>'] = 0
+    tokens["<blk>"] = 0
-    tokens['<sos/eos>'] = 1
+    tokens["<sos/eos>"] = 1
-    tokens['<unk>'] = 2
+    tokens["<unk>"] = 2
     whitespace = re.compile(r"([ \t\r\n]+)")
     with open(text_file, "r", encoding="utf-8") as f:
         for line in f:
             line = re.sub(whitespace, "", line)
             chars = list(line)
             for char in chars:
-                if not char in tokens:
+                if char not in tokens:
                     tokens[char] = len(tokens)
-    return tokens 
+    return tokens
 
 
 def main():

icefall/char_graph_compiler.py

@@ -54,7 +54,6 @@ class CharCtcTrainingGraphCompiler(object):
         self.sos_id = self.token_table[sos_token]
         self.eos_id = self.token_table[eos_token]
 
-
     def texts_to_ids(self, texts: List[str]) -> List[List[int]]:
         """Convert a list of texts to a list-of-list of token IDs.
 
@@ -71,12 +70,15 @@ class CharCtcTrainingGraphCompiler(object):
         whitespace = re.compile(r"([ \t])")
         for text in texts:
             text = re.sub(whitespace, "", text)
-            sub_ids = [self.token_table[txt] if txt in self.token_table \
+            sub_ids = [
-                else self.oov_id for txt in text]
+                self.token_table[txt]
+                if txt in self.token_table
+                else self.oov_id
+                for txt in text
+            ]
             ids.append(sub_ids)
         return ids
 
-
     def compile(
         self,
         token_ids: List[List[int]],
@@ -95,4 +97,3 @@ class CharCtcTrainingGraphCompiler(object):
           piece IDs.
         """
         return k2.ctc_graph(token_ids, modified=modified, device=self.device)
-