Question

使用MultiRNNCell初始化birdirectional_dynamic_rnn时出错 - 形状不匹配。

我的代码是：

def __init__(self, args):
    self.args = args
    self.input_data = tf.placeholder(tf.float32, [None, args.sentence_length, args.word_dim])
    self.output_data = tf.placeholder(tf.float32, [None, args.sentence_length, args.class_size])
    with tf.variable_scope('forward'):
        fw_cell = tf.contrib.rnn.LSTMCell(args.rnn_size, state_is_tuple=True)
        fw_cell = tf.contrib.rnn.DropoutWrapper(fw_cell, output_keep_prob=0.5)
        #print("ff", fw_cell.get_shape())
        fw_cell = tf.contrib.rnn.MultiRNNCell([fw_cell] * args.num_layers, state_is_tuple=True)
        #print("fw", fw_cell.get_shape())
    with tf.variable_scope('backward'):    
        bw_cell = tf.contrib.rnn.LSTMCell(args.rnn_size, state_is_tuple=True)
        bw_cell = tf.contrib.rnn.DropoutWrapper(bw_cell, output_keep_prob=0.5)
        bw_cell = tf.contrib.rnn.MultiRNNCell([bw_cell] * args.num_layers, state_is_tuple=True)
    words_used_in_sent = tf.sign(tf.reduce_max(tf.abs(self.input_data), reduction_indices=2))
    self.length = tf.cast(tf.reduce_sum(words_used_in_sent, reduction_indices=1), tf.int32)
    output, _= tf.nn.bidirectional_dynamic_rnn(fw_cell_1, bw_cell_1,
                                           self.input_data, dtype=tf.float32)

其中word_dim为311，class_size为5，rnn_size为256，num_layers为2，sentence_length为25

这是错误：

error is ValueError: Trying to share variable bidirectional_rnn/fw/multi_rnn_cell/cell_0/lstm_cell/kernel, but specified shape (512, 1024) and found shape (567, 1024).

Answer 1

fw_cell和bw_cell的rnn_size必须与input_data的word_dim相同，但你word_dim是311，rnn_size是256

使用MultiRNNCell初始化birdirectional_dynamic_rn时出错 - 形状不匹配

1 个答案: