小编Gi *_*hin的帖子

编译“make”时收到错误消息

$ make
g++ -fopenmp  -o lang.test main.o -I../../../include/Lheader -I../../../include -L../../../lib/ -llmi -lblas -lboost_regex -lpthread -lleveldb
/usr/bin/ld: ../../../lib//liblmi.a(LMInterface.o): unrecognized relocation (0x2a) in section `.text'
/usr/bin/ld: final link failed: Bad value
collect2: error: ld returned 1 exit status

我找不到上述问题的任何解决方案。

GCC 版本和 ld 版本是这样的：

$ gcc --version
gcc (Ubuntu 5.4.1-2ubuntu1~14.04) 5.4.1 20160904
Copyright (C) 2015 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR …

我想知道如何在Tensorflow中使用多层双向LSTM.

我已经实现了双向LSTM的内容,但我想将此模型与添加的多层模型进行比较.

我该如何在这部分中添加一些代码？

x = tf.unstack(tf.transpose(x, perm=[1, 0, 2]))
#print(x[0].get_shape())

# Define lstm cells with tensorflow
# Forward direction cell
lstm_fw_cell = rnn.BasicLSTMCell(n_hidden, forget_bias=1.0)
# Backward direction cell
lstm_bw_cell = rnn.BasicLSTMCell(n_hidden, forget_bias=1.0)

# Get lstm cell output
try:
    outputs, _, _ = rnn.static_bidirectional_rnn(lstm_fw_cell, lstm_bw_cell, x,
                                          dtype=tf.float32)
except Exception: # Old TensorFlow version only returns outputs not states
    outputs = rnn.static_bidirectional_rnn(lstm_fw_cell, lstm_bw_cell, x,
                                    dtype=tf.float32)

# Linear activation, using rnn inner loop last output
outputs = tf.stack(outputs, axis=1)
outputs = tf.reshape(outputs, (batch_size*n_steps, …