message: Data feeder should handle int and Dimension shape
diff: @@ -363,8 +363,13 @@ class DataFeeder(object):
  num_samples = list(self._x.values())[0].shape[
  0] if x_is_dict else self._x.shape[0]
  +
  + # In case a Tensor is passed num_samples will be a Dimension
  + if hasattr(num_samples, 'value'):
  + num_samples = num_samples.value
  +
  if self._shuffle:
  - self.indices = self.random_state.permutation(num_samples.value)
  + self.indices = self.random_state.permutation(num_samples)
  else:
  self.indices = np.array(range(num_samples))
  self.offset = 0
  