tf.nn.rnn_cell.BasicRNNCell函数的用法

tf.nn.rnn_cell.BasicRNNCell（n_hidden）这个参数就是隐藏神经元的个数。

例如：

import tensorflow as tfbatch_size = 4 input = tf.random_normal(shape=[3, batch_size, 6], dtype=tf.float32)cell = tf.nn.rnn_cell.BasicRNNCell(10)init_state = cell.zero_state(batch_size, dtype=tf.float32)output, final_state = tf.nn.dynamic_rnn(cell, input, initial_state=init_state, time_major=True)with tf.Session() as sess:    sess.run(tf.global_variables_initializer())    print(sess.run(output).shape)    print(sess.run(final_state))

输出：

[[[-0.36194739 -0.5664643   0.71341908 -0.56548703 -0.6058557   0.15607478
   -0.10932037 -0.76532066 -0.15569483  0.5749777 ]
  [-0.47865775 -0.85153252  0.11955925 -0.47678211 -0.26779744 -0.16315795
   -0.85670316 -0.29747197 -0.74362296 -0.11782304]
  [-0.35551894 -0.22971147  0.87532502 -0.07564095 -0.3109358   0.40605015
    0.42417526 -0.73830104  0.63733381  0.29208559]
  [ 0.17648573  0.90195322 -0.66908085  0.62597507  0.36367226 -0.41078696
    0.82797366  0.7970643   0.48825309 -0.09092989]]


 [[-0.07066768 -0.58495802 -0.83810818 -0.22170046  0.28530884 -0.48797613
   -0.86179078  0.53488874 -0.30063036 -0.19637674]
  [-0.24391828  0.08400524 -0.89338982 -0.31769255 -0.80121225 -0.66595536
   -0.6133672  -0.19677906  0.30365667  0.23569871]
  [ 0.55269027  0.57405007 -0.66748625  0.11129615  0.4685905  -0.31985056
    0.37982267  0.60275972 -0.28347531  0.81068254]
  [-0.30811819 -0.46662089 -0.5317077  -0.44609445  0.11240361 -0.48326215
   -0.68652773 -0.73142618  0.45866293 -0.50407058]]


 [[-0.6940583   0.51343572 -0.54493487 -0.73246908 -0.96255547 -0.51650691
    0.32794529 -0.7064063  -0.6840449   0.40109596]
  [-0.48864028 -0.63549376 -0.30771643 -0.30445376  0.278009   -0.08625165
   -0.59299129  0.2232109  -0.85149229 -0.77802432]
  [-0.34051719 -0.16116273 -0.69728005 -0.46142533  0.28736579 -0.46011281
   -0.35864782  0.17567375  0.26353961 -0.81816453]
  [-0.05024701 -0.38233131  0.31979072 -0.36023989 -0.56383204  0.55900681
    0.13344656 -0.35502923 -0.88185179  0.06796031]]]
[[ 0.05491487  0.58953148  0.73639983 -0.67890507  0.37539703 -0.17965442
   0.85910887  0.02395871  0.24805558  0.41260818]
 [ 0.08956354  0.80021787 -0.77623397  0.11130377  0.04178546 -0.36267385
   0.40600157  0.84655112  0.14686334  0.24669757]
 [ 0.51759291  0.67971212  0.16224268  0.77545607  0.12878148  0.77131855
  -0.35831013 -0.73500431  0.53704679 -0.18410714]
 [ 0.11651993  0.4543218  -0.51284182  0.72710162  0.24540463 -0.30895576
  -0.4665778  -0.0014685   0.91048062 -0.22179691]]
另外函数的用法可以参考这个：http://blog.csdn.net/uestc_c2_403/article/details/73353145