Lint bert gen & remove unused vars

bert_gen.py

@@ -1,23 +1,21 @@
 import torch
-from torch.utils.data import DataLoader
 from multiprocessing import Pool
 import commons
 import utils
-from data_utils import TextAudioSpeakerLoader, TextAudioSpeakerCollate
 from tqdm import tqdm
-import warnings
 
 from text import cleaned_text_to_sequence, get_bert
 
-config_path = 'configs/config.json'
+config_path = "configs/config.json"
 hps = utils.get_hparams_from_file(config_path)
+total_gpus = torch.cuda.device_count()
+
 
 def process_line(line):
-    _id, spk, language_str, text, phones, tone, word2ph = line.strip().split("|")
+    wav_path, _, language_str, text, phones, tone, word2ph = line.strip().split("|")
     phone = phones.split(" ")
     tone = [int(i) for i in tone.split(" ")]
     word2ph = [int(i) for i in word2ph.split(" ")]
-    w2pho = [i for i in word2ph]
     word2ph = [i for i in word2ph]
     phone, tone, language = cleaned_text_to_sequence(phone, tone, language_str)
 
@@ -28,26 +26,27 @@ def process_line(line):
         for i in range(len(word2ph)):
             word2ph[i] = word2ph[i] * 2
         word2ph[0] += 1
-    wav_path = f'{_id}'
 
     bert_path = wav_path.replace(".wav", ".bert.pt")
+
     try:
         bert = torch.load(bert_path)
         assert bert.shape[-1] == len(phone)
-    except:
+    except Exception:
         bert = get_bert(text, word2ph, language_str)
         assert bert.shape[-1] == len(phone)
         torch.save(bert, bert_path)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     lines = []
-    with open(hps.data.training_files, encoding='utf-8' ) as f:
+    with open(hps.data.training_files, encoding="utf-8") as f:
         lines.extend(f.readlines())
 
-    with open(hps.data.validation_files, encoding='utf-8' ) as f:
+    with open(hps.data.validation_files, encoding="utf-8") as f:
         lines.extend(f.readlines())
 
-    with Pool(processes=12) as pool: #A100 40GB suitable config,if coom,please decrease the processess number.
-        for _ in tqdm(pool.imap_unordered(process_line, lines)):
+    # A100 40GB suitable config, if coom, please decrease the processes number.
+    with Pool(processes=6) as pool:
+        for _ in tqdm(pool.imap_unordered(process_line, lines), total=len(lines)):
             pass