deleting loss and out references to prevent OOMs, fixed duration chec…

…king for files with space in the path

data/merge_manifests.py

@@ -37,7 +37,7 @@
  file_path = files[x]
  file_path = file_path.split(',')[0]
  output = subprocess.check_output(
- ['soxi -D %s' % file_path.strip()],
+ ['soxi -D \"%s\"' % file_path.strip()],
  shell=True
  )
  duration = float(output)

data/utils.py

@@ -43,7 +43,7 @@ def _order_files(file_paths):
 
  def func(element):
  output = subprocess.check_output(
- ['soxi -D %s' % element.strip()],
+ ['soxi -D \"%s\"' % element.strip()],
  shell=True
  )
  return float(output)

train.py

@@ -125,7 +125,6 @@ def main():
 
  with open(args.labels_path) as label_file:
  labels = str(''.join(json.load(label_file)))
-
  audio_conf = dict(sample_rate=args.sample_rate,
  window_size=args.window_size,
  window_stride=args.window_stride,
@@ -269,6 +268,8 @@ def main():
  torch.save(DeepSpeech.serialize(model, optimizer=optimizer, epoch=epoch, iteration=i, loss_results=loss_results,
  wer_results=wer_results, cer_results=cer_results, avg_loss=avg_loss),
  file_path)
+ del loss
+ del out
  avg_loss /= len(train_loader)
 
  print('Training Summary Epoch: [{0}]\t'
@@ -309,6 +310,7 @@ def main():
 
  if args.cuda:
  torch.cuda.synchronize()
+ del out
  wer = total_wer / len(test_loader.dataset)
  cer = total_cer / len(test_loader.dataset)
  wer *= 100