add more comments and update train.py

Author: qingqing01

deep_speech_2/audio_data_utils.py

@@ -247,25 +247,34 @@ def __padding_batch__(self, batch, padding_to=-1, flatten=False):
  new_batch.append((padded_audio, text))
  return new_batch
 
- def __batch_shuffle__(self, manifest, batch_shuffle_size):
+ def __batch_shuffle__(self, manifest, batch_size):
  """
+ The instances have different lengths and they cannot be
+ combined into a single matrix multiplication. It usually
+ sorts the training examples by length and combines only
+ similarly-sized instances into minibatches, pads with
+ silence when necessary so that all instances in a batch
+ have the same length. This batch shuffle fuction is used
+ to make similarly-sized instances into minibatches and
+ make a batch-wise shuffle.
+
  1. Sort the audio clips by duration.
- 2. Generate a random number `k`, k in [0, batch_shuffle_size).
+ 2. Generate a random number `k`, k in [0, batch_size).
  3. Randomly remove `k` instances in order to make different mini-batches,
- then make minibatches and each minibatch size is batch_shuffle_size.
+ then make minibatches and each minibatch size is batch_size.
  4. Shuffle the minibatches.
 
  :param manifest: manifest file.
  :type manifest: list
- :param batch_shuffle_size: This size is uesed to generate a random number,
-  it usually equals to batch size.
- :type batch_shuffle_size: int
+ :param batch_size: Batch size. This size is also used for generate
+ a random number for batch shuffle.
+ :type batch_size: int
  :return: batch shuffled mainifest.
  :rtype: list
  """
  manifest.sort(key=lambda x: x["duration"])
- shift_len = self.__random__.randint(0, batch_shuffle_size - 1)
- batch_manifest = zip(*[iter(manifest[shift_len:])] * batch_shuffle_size)
+ shift_len = self.__random__.randint(0, batch_size - 1)
+ batch_manifest = zip(*[iter(manifest[shift_len:])] * batch_size)
  self.__random__.shuffle(batch_manifest)
  batch_manifest = list(sum(batch_manifest, ()))
  res_len = len(manifest) - shift_len - len(batch_manifest)
@@ -327,8 +336,9 @@ def batch_reader_creator(self,
  if set True.
  :type sortagrad: bool
  :param batch_shuffle: Shuffle the audio clips if set True. It is
- not a thorough instance-wise shuffle,
- but a specific batch-wise shuffle.
+ not a thorough instance-wise shuffle, but a
+ specific batch-wise shuffle. For more details,
+ please see `__batch_shuffle__` function.
  :type batch_shuffle: bool
  :return: Batch reader function, producing batches of data when called.
  :rtype: callable

deep_speech_2/train.py

@@ -143,12 +143,12 @@ def data_generator():
  train_batch_reader = train_generator.batch_reader_creator(
  manifest_path=args.train_manifest_path,
  batch_size=args.batch_size,
- sortagrad=True,
- shuffle=True)
+ sortagrad=True if args.init_model_path is None else False,
+ batch_shuffle=True)
  test_batch_reader = test_generator.batch_reader_creator(
  manifest_path=args.dev_manifest_path,
  batch_size=args.batch_size,
- shuffle=False)
+ batch_shuffle=False)
  feeding = train_generator.data_name_feeding()
 
  # create event handler