我尝试使用Tensorflow构建卷积神经网络，但出了点问题。
以下是代码：
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
x = mpimg.imread('data.jpg')
y = 1
x = (x-np.mean(x))/np.std(x)
epochs = 10
weights = [tf.Variable(tf.random_normal([5,5,3,32])),
tf.Variable(tf.random_normal([5,5,32,64])),
tf.Variable(tf.random_normal([5,5,64,128])),
tf.Variable(tf.random_normal([19*25*128, 1064])),
tf.Variable(tf.random_normal([1064, 19*25*128])),
tf.Variable(tf.random_normal([19*25*128, 1064])),
tf.Variable(tf.random_normal([1064, 1]))]
def CNN(x, weights):
output = tf.nn.conv2d([x], weights[0], [1,2,2,1], 'SAME')
output = tf.nn.relu(output)
output = tf.nn.conv2d(output, weights[1], [1,2,2,1], 'SAME')
output = tf.nn.relu(output)
output = tf.nn.conv2d(output, weights[2], [1,2,2,1], 'SAME')
output = tf.nn.relu(output)
output = tf.reshape(output, [-1,19*25*128])
output = tf.matmul(output, weights[3])
output = tf.nn.relu(output)
output = tf.matmul(output, weights[4])
output = tf.nn.relu(output)
output = tf.matmul(output, weights[5])
output = tf.nn.relu(output)
output = tf.matmul(output, weights[6])
output = tf.reduce_sum(output)
return output
init = tf.global_variables_initializer()
sess = tf.Session()
prediction = CNN(tf.cast(x,tf.float32), weights)
cost = tf.reduce_mean(tf.square(prediction-y))
train = tf.train.AdamOptimizer().minimize(cost)
sess.run(init)
for e in range(epochs):
print('epoch:',e+1)
sess.run([cost, train])
print(cost.eval())
print('optimization finished!')
CNN(x, weights)
print(output.eval())
这是我收到的错误：
Traceback (most recent call last):
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1021, in _do_call
return fn(*args)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1003, in _run_fn
status, run_metadata)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\contextlib.py", line 66, in __exit__
next(self.gen)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 469, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value beta1_power
[[Node: beta1_power/read = Identity[T=DT_FLOAT, _class=["loc:@Variable"], _device="/job:localhost/replica:0/task:0/cpu:0"](beta1_power)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "D:\Kay\Tensorflow\Session 3\CNN.py", line 49, in <module>
sess.run([cost, train])
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 766, in run
run_metadata_ptr)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 964, in _run
feed_dict_string, options, run_metadata)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1014, in _do_run
target_list, options, run_metadata)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1034, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value beta1_power
[[Node: beta1_power/read = Identity[T=DT_FLOAT, _class=["loc:@Variable"], _device="/job:localhost/replica:0/task:0/cpu:0"](beta1_power)]]
Caused by op 'beta1_power/read', defined at:
File "<string>", line 1, in <module>
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\idlelib\run.py", line 124, in main
ret = method(*args, **kwargs)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\idlelib\run.py", line 351, in runcode
exec(code, self.locals)
File "D:\Kay\Tensorflow\Session 3\CNN.py", line 44, in <module>
train = tf.train.AdamOptimizer().minimize(cost)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\training\optimizer.py", line 279, in minimize
name=name)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\training\optimizer.py", line 393, in apply_gradients
self._create_slots(var_list)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\training\adam.py", line 113, in _create_slots
trainable=False)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\ops\variables.py", line 224, in __init__
expected_shape=expected_shape)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\ops\variables.py", line 370, in _init_from_args
self._snapshot = array_ops.identity(self._variable, name="read")
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 1424, in identity
result = _op_def_lib.apply_op("Identity", input=input, name=name)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 759, in apply_op
op_def=op_def)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 2240, in create_op
original_op=self._default_original_op, op_def=op_def)
File "C:\Users\Katharina\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 1128, in __init__
self._traceback = _extract_stack()
FailedPreconditionError (see above for traceback): Attempting to use uninitialized value beta1_power
[[Node: beta1_power/read = Identity[T=DT_FLOAT, _class=["loc:@Variable"], _device="/job:localhost/replica:0/task:0/cpu:0"](beta1_power)]]
我希望你能帮我修改我的代码。
PS。如果我的代码对您来说效率低下，那是因为我只有14岁。如果我收到反馈，我会很高兴。