audioutils.py 文件源码

def fit(self, x, augment=False, rounds=1, seed=None):
    x = np.asarray(x, dtype=K.floatx())

    if x.ndim != 2:
      raise ValueError('Input to `.fit()` should have rank 2. '
        'Got array with shape: ' + str(x.shape))

    if seed is not None:
      np.random.seed(seed)

    x = np.copy(x)
    if augment:
      ax = np.zeros(tuple([rounds * x.shape[0]] + list(x.shape)[1:]), dtype=K.floatx())
      for r in range(rounds):
        for i in range(x.shape[0]):
          ax[i + r * x.shape[0]] = self.random_transform(x[i])
      x = ax

# @Class: Iterator
# @Description:
#   Abstract base class for Music data iterators.
#   n: Integer, total number of samples in the dataset to loop over.
#   batch_size: Integer, size of a batch.
#   shuffle: Boolean, whether to shuffle the data between epochs.
#   seed: Random seeding for data shuffling.