convLSTM.py 文件源码

def __call__(self, inputs, state, scope=None):
    """Convolutional Long short-term memory cell (ConvLSTM)."""
    with vs.variable_scope(scope or type(self).__name__): # "ConvLSTMCell"
      if self._state_is_tuple:
        c, h = state
      else:
        c, h = array_ops.split(3, 2, state)
      s1 = vs.get_variable("s1", initializer=tf.ones([self._height, self._width, 4 * self._num_units]), dtype=tf.float32)
      s2 = vs.get_variable("s2", initializer=tf.ones([self._height, self._width, 4 * self._num_units]), dtype=tf.float32)
      # s3 = vs.get_variable("s3", initializer=tf.ones([self._batch_size, self._num_units]), dtype=tf.float32)

      b1 = vs.get_variable("b1", initializer=tf.zeros([self._height, self._width, 4 * self._num_units]), dtype=tf.float32)
      b2 = vs.get_variable("b2", initializer=tf.zeros([self._height, self._width, 4 * self._num_units]), dtype=tf.float32)
      # b3 = vs.get_variable("b3", initializer=tf.zeros([self._batch_size, self._num_units]), dtype=tf.float32)
      input_below_ = _conv([inputs], 4 * self._num_units, self._k_size, False, initializer=self._initializer, scope="out_1")
      input_below_ = ln(input_below_, s1, b1)
      state_below_ = _conv([h], 4 * self._num_units, self._k_size, False, initializer=self._initializer, scope="out_2")
      state_below_ = ln(state_below_, s2, b2)
      lstm_matrix = tf.add(input_below_, state_below_)

      i, j, f, o = array_ops.split(3, 4, lstm_matrix)

      # batch_size * height * width * channel
      # concat = _conv([inputs, h], 4 * self._num_units, self._k_size, True, initializer=self._initializer)

      # i = input_gate, j = new_input, f = forget_gate, o = output_gate
      # i, j, f, o = array_ops.split(3, 4, lstm_matrix)

      new_c = (c * sigmoid(f + self._forget_bias) + sigmoid(i) *
               self._activation(j))
      new_h = self._activation(new_c) * sigmoid(o)

      if self._state_is_tuple:
        new_state = LSTMStateTuple(new_c, new_h)
      else:
        new_state = array_ops.concat(3, [new_c, new_h])
      return new_h, new_state