多层RNN Tensorflow

Question

我有两层LSTM网络。(config.n_input为3，config.n_steps为5)

我认为这可能与输入的形状有关，但我不确定如何修复它，我尝试更改LSTM的投影，使它们具有相同的输入大小，但这不起作用。

      self.input_data = tf.placeholder(tf.float32, [None, config.n_steps, config.n_input], name='input')

       # Tensorflow LSTM cell requires 2x n_hidden length (state & cell)
       self.initial_state = tf.placeholder(tf.float32, [None, 2*config.n_hidden], name='state')
       self.targets = tf.placeholder(tf.float32, [None, config.n_classes], name='target')

       _X = tf.transpose(self.input_data, [1, 0, 2])  # permute n_steps and batch_size
       _X = tf.reshape(_X, [-1, config.n_input]) # (n_steps*batch_size, n_input)

       input_cell = rnn_cell.LSTMCell(num_units=config.n_hidden, input_size=3, num_proj=300, forget_bias=1.0)
       print(input_cell.output_size)
       inner_cell = rnn_cell.LSTMCell(num_units=config.n_hidden, input_size=300)
       cells = [input_cell, inner_cell]
       cell = rnn.rnn_cell.MultiRNNCell(cells)

当尝试运行它时，它返回以下错误。

tensorflow.python.pywrap_tensorflow.StatusNotOK: Invalid argument: Expected size[1] in [0, 0], but got 600
 [[Node: RNN/MultiRNNCell/Cell1/Slice = Slice[Index=DT_INT32, T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/gpu:0"](_recv_state_0/_3, RNN/MultiRNNCell/Cell1/Slice/begin, RNN/MultiRNNCell/Cell1/Slice/size)]]

对错误消息有什么更好的解释吗？或者有什么方法可以很容易地解决这个问题？

Answer 1

# Tensorflow LSTM cell requires 2x n_hidden length (state & cell)
self.initial_state = tf.placeholder(tf.float32, [None, 2*config.n_hidden + 300], name='state')

这是一个相当不透明的错误，您最好在TF GitHub问题页面上提出它！