(self, net)
return tf.unstack(net, axis=1)
Splits an input tensor into a list of tensors (features).

    Args:
      net: A feature map of shape [batch_size, num_features, feature_size].

    Raises:
      AssertionError: if num_features is less than seq_length.

    Returns:
      A list with seq_length tensors of shape [batch_size, feature_size]
Splits an input tensor into a list of tensors (features).
Splits an input tensor into a list of tensors ( features ) .
def _create_lstm_inputs(self, net):
    """Splits an input tensor into a list of tensors (features).

    Args:
      net: A feature map of shape [batch_size, num_features, feature_size].

    Raises:
      AssertionError: if num_features is less than seq_length.

    Returns:
      A list with seq_length tensors of shape [batch_size, feature_size]
    """
    num_features = net.get_shape().dims[1].value
    if num_features < self._params.seq_length:
      raise AssertionError('Incorrect dimension #1 of input tensor'
                           ' %d should be bigger than %d (shape=%s)' %
                           (num_features, self._params.seq_length,
                            net.get_shape()))
    elif num_features > self._params.seq_length:
      logging.warning('Ignoring some features: use %d of %d (shape=%s)',
                      self._params.seq_length, num_features, net.get_shape())
      net = tf.slice(net, [0, 0, 0], [-1, self._params.seq_length, -1])

    return tf.unstack(net, axis=1)
def _create_lstm_inputs ( self , net ) : num_features = net . get_shape ( ) . dims [ 1 ] . value if num_features < self . _params . seq_length : raise AssertionError ( 'Incorrect dimension #1 of input tensor' ' %d should be bigger than %d (shape=%s)' % ( num_features , self . _params . seq_length , net . get_shape ( ) ) ) elif num_features > self . _params . seq_length : logging . warning ( 'Ignoring some features: use %d of %d (shape=%s)' , self . _params . seq_length , num_features , net . get_shape ( ) ) net = tf . slice ( net , [ 0 , 0 , 0 ] , [ - 1 , self . _params . seq_length , - 1 ] ) return tf . unstack ( net , axis = 1 )