Merge pull request #640 from zhxfl/fix-639

Augmentation should compute frame_dim

Author: zhxfl

fluid/DeepASR/data_utils/data_reader.py

@@ -121,8 +121,6 @@ class DataReader(object):
  corresponding description file.
  label_file_list (str): File containing paths of label data file and 
  corresponding description file.
- frame_dim (int): The final feature dimension of one frame after all 
- augmentation applied.
  drop_frame_len (int): Samples whose label length above the value will be
  dropped.
  process_num (int): Number of processes for processing data.
@@ -137,21 +135,18 @@ class DataReader(object):
  random_seed (int): Random seed.
  """
 
- def __init__(
- self,
- feature_file_list,
- label_file_list,
- frame_dim=120 * 11, # @TODO augmentor is responsible for the value
- drop_frame_len=512,
- process_num=10,
- sample_buffer_size=1024,
- sample_info_buffer_size=1024,
- batch_buffer_size=1024,
- shuffle_block_num=1,
- random_seed=0):
+ def __init__(self,
+ feature_file_list,
+ label_file_list,
+ drop_frame_len=512,
+ process_num=10,
+ sample_buffer_size=1024,
+ sample_info_buffer_size=1024,
+ batch_buffer_size=1024,
+ shuffle_block_num=1,
+ random_seed=0):
  self._feature_file_list = feature_file_list
  self._label_file_list = label_file_list
- self._frame_dim = frame_dim
  self._drop_frame_len = drop_frame_len
  self._shuffle_block_num = shuffle_block_num
  self._block_info_list = None
@@ -300,8 +295,9 @@ def read_bytes(fpath, start, size):
 
  def batch_iterator(self, batch_size, minimum_batch_size):
  def batch_to_ndarray(batch_samples, lod):
- batch_feature = np.zeros(
- (lod[-1], self._frame_dim), dtype="float32")
+ assert len(batch_samples)
+ frame_dim = batch_samples[0][0].shape[1]
+ batch_feature = np.zeros((lod[-1], frame_dim), dtype="float32")
  batch_label = np.zeros((lod[-1], 1), dtype="int64")
  start = 0
  for sample in batch_samples: