fix typo.

tools/make_list.py

@@ -15,8 +15,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import argparse, logging
+import argparse
-import json, re
+import logging
+import json
+import re
 
 symbol_str = '[’!"#$%&\'()*+,-./:;<>=?@，。?★、…【】《》？“”‘’！[\\]^_`{|}~]+'
 
@@ -189,7 +191,7 @@ if __name__ == '__main__':
             arr = line.strip().split(maxsplit=1)
             key = arr[0]
             tokens = None
-            if token_table!=None and lexicon_table!=None :
+            if token_table is not None and lexicon_table is not None :
                 if len(arr) < 2:  # for some utterence, no text
                     txt = [1]  # the <blank>/sil is indexed by 1
                     tokens = ["sil"]
@@ -201,7 +203,7 @@ if __name__ == '__main__':
             wav = wav_table[key]
             assert key in duration_table
             duration = duration_table[key]
-            if tokens == None:
+            if tokens is None:
                 line = dict(key=key, txt=txt, duration=duration, wav=wav)
             else:
                 line = dict(key=key, tok=tokens, txt=txt, duration=duration, wav=wav)

wekws/bin/compute_det_ctc.py

@@ -14,8 +14,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import argparse, logging, glob
+import argparse
-import json, re, os, numpy as np
+import logging
+import glob
+import json
+import re
+import os
+import numpy as np
 import matplotlib.pyplot as plt
 import pypinyin  # for Chinese Character
 
@@ -205,8 +210,7 @@ if __name__ == '__main__':
                 num_false_reject = 0
                 num_true_detect = 0
                 # transverse the all keyword_table
-                for key, confi in keyword_filler_table[keyword][
+                for key, confi in keyword_filler_table[keyword]['keyword_table'].items():
-                    'keyword_table'].items():
                     if confi < threshold:
                         num_false_reject += 1
                     else:

wekws/bin/score_ctc.py

@@ -19,7 +19,9 @@ from __future__ import print_function
 import argparse
 import copy
 import logging
-import os, sys, math
+import os
+import sys
+import math
 
 import torch
 import yaml
@@ -165,11 +167,11 @@ def main():
             for i in range(len(keys)):
                 key = keys[i]
                 score = logits[i][:lengths[i]]
-                hyps = ctc_prefix_beam_search(score, lengths[i],
+                hyps = ctc_prefix_beam_search(score, lengths[i], keywords_idxset)
-                                              keywords_idxset)
                 hit_keyword = None
                 hit_score = 1.0
-                start = 0; end = 0
+                start = 0
+                end = 0
                 for one_hyp in hyps:
                     prefix_ids = one_hyp[0]
                     # path_score = one_hyp[1]

wekws/bin/stream_kws_ctc.py

@@ -15,9 +15,11 @@
 from __future__ import print_function
 
 import argparse
-import struct, wave
+import struct
+import wave
 import logging
-import os, math
+import os
+import math
 import numpy as np
 import torchaudio.compliance.kaldi as kaldi
 
@@ -284,6 +286,7 @@ class KeyWordSpotter(torch.nn.Module):
         for i in range(0, len(wave), 2):
             value = struct.unpack('<h', wave[i:i + 2])[0]
             data.append(value)  # here we don't divide 32768.0, because kaldi.fbank accept original input
+
         wave = np.array(data)
         wave = np.append(self.wave_remained, wave)
         wave_tensor = torch.from_numpy(wave).float().to(self.device)
@@ -303,7 +306,7 @@ class KeyWordSpotter(torch.nn.Module):
         if self.context_expansion:
             assert feat_len > self.right_context, "make sure each chunk feat length is large than right context."
             # pad feats with remained feature from last chunk
-            if self.feature_remained == None: # first chunk
+            if self.feature_remained is None:  # first chunk
                 # pad first frame at the beginning, replicate just support last dimension, so we do transpose.
                 feats_pad = F.pad(feats.T, (self.left_context, 0), mode='replicate').T
             else:
@@ -340,7 +343,8 @@ class KeyWordSpotter(torch.nn.Module):
     def execute_detection(self, t):
         absolute_time = t + self.total_frames
         hit_keyword = None
-        start = 0; end = 0
+        start = 0
+        end = 0
 
         # hyps for detection
         hyps = [(y[0], y[1][0] + y[1][1], y[1][2]) for y in self.cur_hyps]

wekws/bin/stream_score_ctc.py

@@ -19,7 +19,9 @@ from __future__ import print_function
 import argparse
 import copy
 import logging
-import os, sys, math
+import os
+import sys
+import math
 
 import torch
 import yaml
@@ -197,7 +199,8 @@ def main():
                 hit_keyword = None
                 activated = False
                 hit_score = 1.0
-                start = 0;  end = 0
+                start = 0
+                end = 0
 
                 # 2. CTC beam search step by step
                 for t in range(0, maxlen):

wekws/model/fsmn.py

@@ -221,7 +221,7 @@ class FSMNBlock(nn.Module):
         x = torch.unsqueeze(input, 1)
         x_per = x.permute(0, 3, 2, 1)
 
-        if in_cache is None  or len(in_cache)==0 or in_cache[0]==None:
+        if in_cache is None or len(in_cache) == 0 or in_cache[0] is None:
             x_pad = F.pad(x_per, [0, 0, (self.lorder - 1) * self.lstride + self.rorder * self.rstride, 0])
         else:
             in_cache = in_cache.to(x_per.device)
@@ -233,7 +233,6 @@ class FSMNBlock(nn.Module):
         y_left = self.dequant(y_left)
         out = x_pad[:, :, (self.lorder - 1) * self.lstride:-self.rorder * self.rstride, :] + y_left
 
-        #out = out[:, :, :-self.rorder*self.rstride, :]
         if self.conv_right is not None:
             # y_right = F.pad(x_per, [0, 0, 0, (self.rorder) * self.rstride])
             y_right = x_pad[:, :, -(x_per.size(2)+self.rorder*self.rstride):, :]

wekws/model/kws_model.py

@@ -64,7 +64,7 @@ class KWSModel(nn.Module):
     def forward(
         self,
         x: torch.Tensor,
-        in_cache=None #: torch.Tensor = torch.zeros(0, 0, 0, dtype=torch.float)
+        in_cache: torch.Tensor = torch.zeros(0, 0, 0, dtype=torch.float)
     ) -> Tuple[torch.Tensor, torch.Tensor]:
         if self.global_cmvn is not None:
             x = self.global_cmvn(x)

wekws/model/loss.py

@@ -13,10 +13,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import torch, math, sys
+import torch
+import math
+import sys
 import torch.nn.functional as F
 from collections import defaultdict
-from typing import List, Optional, Tuple
+from typing import List, Tuple
 
 from wekws.utils.mask import padding_mask
 

wekws/utils/cmvn.py

@@ -14,7 +14,8 @@
 # limitations under the License.
 
 import json
-import math,re
+import math
+import re
 
 import numpy as np