python - Tensorflow FailedPreconditionError:尝试使用未初始化的值 beta1_power
问题描述
我正在尝试在 Tensorflow 中建立一个简单的卷积网络。我会尽量将代码量保持在最低水平。这是课程:
class ConvNet(object):
def __init__(self, input, labels, dataset):
self.input = input
self.true_labels = labels
#'dataset' is an instance of a class that
#I am using to read the training images
self.data = dataset
self.build()
self._optimize = None
self.sess = tf.Session()
self.sess.run(tf.global_variables_initializer())
def build(self):
self.conv_layers = []
# create 3 conv layers using tf.nn.conv2d
# and append them to self.conv_layers
# create flattening layer using tf.nn.reshape
self.fc_layers = []
# create 2 fully connected layers using tf.matmul
# and append them to self.fc_layers
@property
def optimize(self):
"""Return the optimize operation."""
if not self._optimize:
cross_entropy = tf.nn.softmax_cross_entropy_with_logits(logits = self.fc_layers[-1],
labels = self.true_labels)
cost = tf.reduce_mean(cross_entropy)
self._optimize = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(cost)
return self._optimize
def train(self, num_epochs=1, batch_size=16):
epochs_done = 0
while not epochs_done == num_epochs:
# get next batch from training data
x_batch, y_true_batch, _, _ = self.data.train.next_batch(batch_size)
feed_dict_train = {self.input: x_batch, self.true_labels: y_true_batch}
#even if I initialize variables here, same error occurs
#self.sess.run(tf.global_variables_initializer())
self.sess.run(self.optimize, feed_dict=feed_dict_train)
if self.data.train.epochs_done > epochs_done:
#print stuff...
epochs_done += 1
self.sess.close()
我试图运行该optimize
操作以在一个简单的数据集(例如猫与狗的图像)上训练网络。这是主要的:
if __name__ == "__main__":
classes = ['dogs', 'cats']
num_classes = len(classes)
batch_size = 16
img_size = 128
num_channels = 3
#read training data and resize images to 128 x 128 pixels
data = dataset.read_train_sets(img_size, classes)
x = tf.placeholder(tf.float32, shape = [None, img_size, img_size, num_channels], name='x')
y_true = tf.placeholder(tf.float32, shape = [None, num_classes], name = 'y_true')
net = ConvNet(x, y_true, data)
net.train()
但是我不断收到以下错误(它实际上比这长得多,如有必要我可以发布它):
Caused by op 'beta1_power/read', defined at:
File "<string>", line 1, in <module>
File "/usr/lib/python3.5/idlelib/run.py", line 124, in main
ret = method(*args, **kwargs)
File "/usr/lib/python3.5/idlelib/run.py", line 351, in runcode
exec(code, self.locals)
File "/home/gian/face_recognition/model.py", line 366, in <module>
net.train()
File "/home/gian/face_recognition/model.py", line 309, in train
self.sess.run(self.optimize, feed_dict=feed_dict_train)
File "/home/gian/face_recognition/model.py", line 269, in optimize
self._optimize = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(cost)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/optimizer.py", line 409, in minimize
name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/optimizer.py", line 552, in apply_gradients
self._create_slots([_get_variable_for(v) for v in var_list])
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/adam.py", line 124, in _create_slots
colocate_with=first_var)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/optimizer.py", line 665, in _create_non_slot_variable
v = variable_scope.variable(initial_value, name=name, trainable=False)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/variable_scope.py", line 2157, in variable
use_resource=use_resource)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/variable_scope.py", line 2147, in <lambda>
previous_getter = lambda **kwargs: default_variable_creator(None, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/variable_scope.py", line 2130, in default_variable_creator
constraint=constraint)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/variables.py", line 235, in __init__
constraint=constraint)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/variables.py", line 391, in _init_from_args
self._snapshot = array_ops.identity(self._variable, name="read")
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/array_ops.py", line 142, in identity
return gen_array_ops.identity(input, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 3053, in identity
"Identity", input=input, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 3290, in create_op
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1654, in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
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/device:GPU:0"](beta1_power)]]
有人可以帮我找出问题所在吗?非常感谢
解决方案
此错误通常发生在您尚未初始化优化器时。因此,只需在初始化所有全局变量之前添加 self.optimize 即可。
您的代码应如下所示。
def __init__(self, input, labels, dataset):
self.input = input
self.true_labels = labels
#'dataset' is an instance of a class that
#I am using to read the training images
self.data = dataset
self.build()
self._optimize = None
self.sess = tf.Session()
self.optimize()
self.sess.run(tf.global_variables_initializer())
推荐阅读
- javascript - 如何更改 matautocomplete 选项的字体颜色
- javascript - 包含 HTML 登录表单响应的 HTTP 响应(paypal express 样式)
- javascript - Javascript 中的原型类型
- android-studio - 无法在片段内创建对话框
- python - 基于另一个数据帧中的索引为一个数据帧中的新列分配值的for循环
- node.js - 如何获取发布者的nats用户id
- python-3.x - ModuleNotFoundError:没有名为“simplejson”的模块
- java - 代号一 - Eclipse 中的 Maven 项目无法生成新类
- java - 为什么我不能使用2.5.2的springboot版本?
- c++ - 为什么我可以在 constexpr 函数中修改 const_cast-ed 对象?