ValueError:尝试共享变量rnn/multi_rnn_cell/cell_0/basic_lstm_cell/kernel [英] ValueError: Trying to share variable rnn/multi_rnn_cell/cell_0/basic_lstm_cell/kernel

问题描述

这是代码:

X = tf.placeholder(tf.float32, [batch_size, seq_len_1, 1], name='X')
labels = tf.placeholder(tf.float32, [None, alpha_size], name='labels')

rnn_cell = tf.contrib.rnn.BasicLSTMCell(512)
m_rnn_cell = tf.contrib.rnn.MultiRNNCell([rnn_cell] * 3, state_is_tuple=True)
pre_prediction, state = tf.nn.dynamic_rnn(m_rnn_cell, X, dtype=tf.float32)

这是完全错误:

ValueError::尝试共享变量rnn/multi_rnn_cell/cell_0/basic_lstm_cell/kernel，但指定了形状(1024、2048)并找到了形状(513、2048).

ValueError: Trying to share variable rnn/multi_rnn_cell/cell_0/basic_lstm_cell/kernel, but specified shape (1024, 2048) and found shape (513, 2048).

我正在使用GPU版本的tensorflow.

I'm using a GPU version of tensorflow.

推荐答案

升级到v1.2(tensorflow-gpu)时，我遇到了类似的问题. 我没有使用[rnn_cell]*3，而是通过循环创建了3个rnn_cells(stacked_rnn)(以便它们不共享变量)，并为MultiRNNCell提供了stacked_rnn，问题就消失了.我不确定这是正确的方法.

I encountered a similar problem when I upgraded to v1.2 (tensorflow-gpu). Instead of using [rnn_cell]*3, I created 3 rnn_cells (stacked_rnn) by a loop (so that they don't share variables) and fed MultiRNNCell with stacked_rnn and the problem goes away. I'm not sure it is the right way to do it.

stacked_rnn = []
for iiLyr in range(3):
    stacked_rnn.append(tf.nn.rnn_cell.LSTMCell(num_units=512, state_is_tuple=True))
MultiLyr_cell = tf.nn.rnn_cell.MultiRNNCell(cells=stacked_rnn, state_is_tuple=True)

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