Format & polish training and webui

data_utils.py

@@ -1,13 +1,11 @@
-import time
 import os
 import random
-import numpy as np
 import torch
 import torch.utils.data
 from tqdm import tqdm
 from loguru import logger
 import commons
-from mel_processing import spectrogram_torch, mel_spectrogram_torch, spec_to_mel_torch
+from mel_processing import spectrogram_torch, mel_spectrogram_torch
 from utils import load_wav_to_torch, load_filepaths_and_text
 from text import cleaned_text_to_sequence, get_bert
 
@@ -100,7 +98,7 @@ class TextAudioSpeakerLoader(torch.utils.data.Dataset):
         if sampling_rate != self.sampling_rate:
             raise ValueError(
                 "{} {} SR doesn't match target {} SR".format(
-                    sampling_rate, self.sampling_rate
+                    filename, sampling_rate, self.sampling_rate
                 )
             )
         audio_norm = audio / self.max_wav_value