我使用最简单RNN进行mnist手写数字的识别,为什么交叉商总是无法降低呢。完整代码如下。
import tensorflow as tf
from tensorflow.contrib.layers import fully_connected
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('/home/as/mnist_dataset', one_hot=True)
n_steps = 28
n_inputs = 28
n_neurons = 100
x = tf.placeholder(tf.float32,[None,n_steps,n_inputs])
action_one_hot = tf.placeholder(tf.float32,[None,10])
basic_cell = tf.contrib.rnn.BasicRNNCell(num_units=n_neurons)
output_seqs, states = tf.nn.dynamic_rnn(basic_cell,x,dtype=tf.float32)
y0 = fully_connected(states,100,activation_fn=tf.nn.relu)
y = fully_connected(y0,10)
cross_entropy = tf.nn.softmax_cross_entropy_with_logits(labels=action_one_hot, logits=y)
mean_loss = tf.reduce_mean(cross_entropy)
trian_op = tf.train.AdamOptimizer(0.001).minimize(mean_loss)
with tf.Session() as sess:
for i in range(10000):
sess.run(tf.global_variables_initializer())
x1,y1 = mnist.train.next_batch(1000)
x1 = x1.reshape((-1,n_steps,n_inputs))
sess.run(trian_op,feed_dict={x:x1,action_one_hot:y1})
if i%200==0:
print(sess.run(mean_loss,feed_dict={x:x1,action_one_hot:y1}))
就是在每200步输出一下交叉商,但是这个交叉商总是无法下降。