问题记录

win10-anaconda3-py3.5-tensorflow1.0.1-keras2.0.5
运行代码：
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt

def add_layer(inputs, in_size, out_size, n_layer, activation_function=None):
layer_name = ‘layer%s’ % n_layer
with tf.name_scope(‘layer’):
with tf.name_scope(‘weights’):
Weights = tf.Variable(tf.random_normal([in_size, out_size]), name=’W’)
tf.summary.histogram(layer_name + ‘/weights’, Weights)
with tf.name_scope(‘biases’):
biases = tf.Variable(tf.zeros([1, out_size]) + 0.1, name=’b’)
tf.summary.histogram(layer_name + ‘/biases’, biases)
with tf.name_scope(‘Wx_plus_b’):
Wx_plus_b = tf.add(tf.matmul(inputs, Weights), biases, name=’Wpb’)
if activation_function is None:
outputs = Wx_plus_b

else:
outputs = activation_function(Wx_plus_b)
tf.summary.histogram(layer_name + '/outputs', outputs)
return outputs

with tf.name_scope(‘inputs’):
xs = tf.placeholder(tf.float32, [None, 1], name=’x_input’)
ys = tf.placeholder(tf.float32, [None, 1], name=’y_input’)

x_data = np.linspace(-1.0, 1.0, 300, dtype=np.float32)[:, np.newaxis]
noise = np.random.normal(0.0, 0.05, x_data.shape)
y_data = np.square(x_data) + 0.5 + noise

l1 = add_layer(xs, 1, 10, n_layer=1, activation_function=tf.nn.relu)
prediction = add_layer(l1, 10, 1, n_layer=2, activation_function=None)

with tf.name_scope(‘loss’):
loss = tf.reduce_mean(tf.reduce_sum(tf.square(ys - prediction), reduction_indices=[1]), name=’L’)
tf.summary.scalar(‘loss’, loss)

with tf.name_scope(‘train’):
train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)

init = tf.initialize_all_variables()

init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.scatter(x_data, y_data)
plt.show(block=False)
merged = tf.summary.merge_all()
writer = tf.summary.FileWriter(‘I:/CASIA/deeplearning/tensorBoard/tmp/TB_Graph/1’, sess.graph)
”’tensorboard –logdir=I:/CASIA/deeplearning/tensorBoard/tmp/TB_Graph/1”’
for i in range(10):
sess.run(train_step, feed_dict={xs:x_data, ys : y_data})
if i % 50 == 0:
try:
ax.lines.remove(lines[0])
except Exception:
pass
result, prediction_value = sess.run([merged, prediction], feed_dict={xs:x_data, ys:y_data})
lines = ax.plot(x_data, prediction_value, ‘r-‘, lw=5)
plt.pause(0.1)
writer.add_summary(result, i)

结果：
D:\software\Anconda_python\A3\python.exe I:/CASIA/deeplearning/LSTM/selfAlgorithm/TB_Graph.py
E c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel (‘op: “BestSplits” device_type: “CPU”’) for unknown op: BestSplits
E c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel (‘op: “CountExtremelyRandomStats” device_type: “CPU”’) for unknown op: CountExtremelyRandomStats
E c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel (‘op: “FinishedNodes” device_type: “CPU”’) for unknown op: FinishedNodes
E c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel (‘op: “GrowTree” device_type: “CPU”’) for unknown op: GrowTree
E c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel (‘op: “ReinterpretStringToFloat” device_type: “CPU”’) for unknown op: ReinterpretStringToFloat
E c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel (‘op: “SampleInputs” device_type: “CPU”’) for unknown op: SampleInputs
E c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel (‘op: “ScatterAddNdim” device_type: “CPU”’) for unknown op: ScatterAddNdim
E c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel (‘op: “TopNInsert” device_type: “CPU”’) for unknown op: TopNInsert
E c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel (‘op: “TopNRemove” device_type: “CPU”’) for unknown op: TopNRemove
E c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel (‘op: “TreePredictions” device_type: “CPU”’) for unknown op: TreePredictions
E c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\framework\op_kernel.cc:943] OpKernel (‘op: “UpdateFertileSlots” device_type: “CPU”’) for unknown op: UpdateFertileSlots
D:\software\Anconda_python\A3\lib\site-packages\matplotlib\backend_bases.py:2453: MatplotlibDeprecationWarning: Using default event loop until function specific to this GUI is implemented
warnings.warn(str, mplDeprecation)

Process finished with exit code 0

绘制的结果图会闪退，tensorboard极不稳定，原因未知