Question

我对tensorflow很陌生。使用多个CudnnLSTM()单元格时如何获得特定的输出形状。我得到了不同的形状（即，我在最后一层使用tf.contrib.cudnn_rnn.CudnnLSTM(10,1)来获取单个值作为输出）。下面给出了代码和输出，我想从最终的LSTM单元格中获取一个值：

import tensorflow as tf
import numpy as np
import InitRand as inr
tf.reset_default_graph()
rand_init = inr.RandomInit()
# rand_init.rnn_reward_rnd_init() returns a single integer value
re = rand_init.rnn_reward_rnd_init()
print("----",re,"----")
"""rand_init.neuro_rnd_init() returns a list of tf.get_variable()[la] and a list of shape of the tf.get_variable()[ne]"""
la,ne = rand_init.neuro_rnd_init(np.random.randint(10,20))
ne.append(re)
ne = np.array(ne)
#tf.set_random_seed(10)
shp = ne.shape[0]
print(shp)
x = tf.placeholder(dtype = tf.float32,shape=[None,1,shp])
Culstm = tf.contrib.cudnn_rnn.CudnnLSTM(20,30)
output1, state1 = Culstm(x,initial_state = None,training = True)
Culstm1 = tf.contrib.cudnn_rnn.CudnnLSTM(15,10)
output2,state2 = Culstm1(output1,initial_state = state1,training = True)
Culstm2 = tf.contrib.cudnn_rnn.CudnnLSTM(10,1)
output3,state3 = Culstm2(output2,initial_state = state2, training = True)
with tf.Session() as sess:
    sess.run(init)
    writer = tf.summary.FileWriter('./graphs1',sess.graph)
    xi,i = sess.run([output3,state3],feed_dict={x : [[ne]]})
    print(xi[-1])
    print(np.shape(xi))
    print("##########################################")

我得到的结果是：

---- 2.2 ----
15
2019-03-27 11:21:35.755673: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1484] Adding visible gpu devices: 0
2019-03-27 11:21:35.939004: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:965] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-03-27 11:21:35.939217: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:971]      0 
2019-03-27 11:21:35.939354: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:984] 0:   N 
2019-03-27 11:21:35.939590: I T:\src\github\tensorflow\tensorflow\core\common_runtime\gpu\gpu_device.cc:1097] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3073 MB memory) -> physical GPU (device: 0, name: GeForce 940MX, pci bus id: 0000:01:00.0, compute capability: 5.0)
[[-0.03285285 -0.13111939  0.05034531 -0.0148275   0.01240168  0.19128764
  -0.24743158 -0.09602346 -0.23931934 -0.19925891  0.08083354 -0.19639972
  -0.2063862  -0.15950726 -0.16337153  0.05836788  0.14596528  0.08547601
   0.0222337   0.0812543   0.11112089  0.13615175 -0.03676694  0.10695431
  -0.01627629  0.01623598  0.05504112  0.07749368  0.2750034  -0.0225246 ]]
(1, 1, 30)

##########################################

我希望输出为：

[[some_value]]

tf.contrib.cudnn_rnn.CudnnLSTM（）输出形状？

0 个答案: