FailedPreconditionError:尝试在Tensorflow中使用未初始化的 [英] FailedPreconditionError: Attempting to use uninitialized in Tensorflow
问题描述
我正在研究 TensorFlow教程，该教程使用了格式"上传数据.我想对数据使用NumPy或pandas格式，以便将其与scikit学习结果进行比较.
I am working through the TensorFlow tutorial, which uses a "weird" format to upload the data. I would like to use the NumPy or pandas format for the data, so that I can compare it with scikit-learn results.
我从Kaggle获得了数字识别数据: https://www.kaggle.com /c/digit-recognizer/data .
I get the digit recognition data from Kaggle: https://www.kaggle.com/c/digit-recognizer/data.
这里是TensorFlow教程中的代码(效果很好):
Here the code from the TensorFlow tutorial (which works fine):
# Stuff from tensorflow tutorial
import tensorflow as tf
sess = tf.InteractiveSession()
x = tf.placeholder("float", shape=[None, 784])
y_ = tf.placeholder("float", shape=[None, 10])
W = tf.Variable(tf.zeros([784, 10]))
b = tf.Variable(tf.zeros([10]))
y = tf.nn.softmax(tf.matmul(x, W) + b)
cross_entropy = -tf.reduce_sum(y_ * tf.log(y))
train_step = tf.train.GradientDescentOptimizer(0.01).minimize(cross_entropy)
我在这里读取数据，去除目标变量，然后将数据拆分为测试和训练数据集(一切正常):
Here I read the data, strip out the target variables and split the data into testing and training datasets (this all works fine):
# Read dataframe from training data
csvfile='train.csv'
from pandas import DataFrame, read_csv
df = read_csv(csvfile)
# Strip off the target data and make it a separate dataframe.
Target = df.label
del df["label"]
# Split data into training and testing sets
msk = np.random.rand(len(df)) < 0.8
dfTest = df[~msk]
TargetTest = Target[~msk]
df = df[msk]
Target = Target[msk]
# One hot encode the target
OHTarget=pd.get_dummies(Target)
OHTargetTest=pd.get_dummies(TargetTest)
现在，当我尝试执行训练步骤时，我得到一个FailedPreconditionError:
Now, when I try to run the training step, I get a FailedPreconditionError:
for i in range(100):
batch = np.array(df[i*50:i*50+50].values)
batch = np.multiply(batch, 1.0 / 255.0)
Target_batch = np.array(OHTarget[i*50:i*50+50].values)
Target_batch = np.multiply(Target_batch, 1.0 / 255.0)
train_step.run(feed_dict={x: batch, y_: Target_batch})
这是完整的错误:
---------------------------------------------------------------------------
FailedPreconditionError Traceback (most recent call last)
<ipython-input-82-967faab7d494> in <module>()
4 Target_batch = np.array(OHTarget[i*50:i*50+50].values)
5 Target_batch = np.multiply(Target_batch, 1.0 / 255.0)
----> 6 train_step.run(feed_dict={x: batch, y_: Target_batch})
/Users/user32/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.pyc in run(self, feed_dict, session)
1265 none, the default session will be used.
1266 """
-> 1267 _run_using_default_session(self, feed_dict, self.graph, session)
1268
1269
/Users/user32/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.pyc in _run_using_default_session(operation, feed_dict, graph, session)
2761 "the operation's graph is different from the session's "
2762 "graph.")
-> 2763 session.run(operation, feed_dict)
2764
2765
/Users/user32/anaconda/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in run(self, fetches, feed_dict)
343
344 # Run request and get response.
--> 345 results = self._do_run(target_list, unique_fetch_targets, feed_dict_string)
346
347 # User may have fetched the same tensor multiple times, but we
/Users/user32/anaconda/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _do_run(self, target_list, fetch_list, feed_dict)
417 # pylint: disable=protected-access
418 raise errors._make_specific_exception(node_def, op, e.error_message,
--> 419 e.code)
420 # pylint: enable=protected-access
421 raise e_type, e_value, e_traceback
FailedPreconditionError: Attempting to use uninitialized value Variable_1
[[Node: gradients/add_grad/Shape_1 = Shape[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](Variable_1)]]
Caused by op u'gradients/add_grad/Shape_1', defined at:
File "/Users/user32/anaconda/lib/python2.7/runpy.py", line 162, in _run_module_as_main
...........
...which was originally created as op u'add', defined at:
File "/Users/user32/anaconda/lib/python2.7/runpy.py", line 162, in _run_module_as_main
"__main__", fname, loader, pkg_name)
[elided 17 identical lines from previous traceback]
File "/Users/user32/anaconda/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 3066, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-45-59183d86e462>", line 1, in <module>
y = tf.nn.softmax(tf.matmul(x,W) + b)
File "/Users/user32/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 403, in binary_op_wrapper
return func(x, y, name=name)
File "/Users/user32/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/gen_math_ops.py", line 44, in add
return _op_def_lib.apply_op("Add", x=x, y=y, name=name)
File "/Users/user32/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/op_def_library.py", line 633, in apply_op
op_def=op_def)
File "/Users/user32/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1710, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/Users/user32/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 988, in __init__
self._traceback = _extract_stack()
关于如何解决此问题的任何想法?
Any ideas as to how I can fix this?
推荐答案
之所以出现FailedPreconditionError是因为程序在初始化之前试图读取变量(名为"Variable_1").在TensorFlow中，必须通过运行它们的初始化程序"操作来显式初始化所有变量.为了方便起见，您可以通过在训练循环之前执行以下语句来在当前会话中运行所有变量初始化器:
The FailedPreconditionError arises because the program is attempting to read a variable (named "Variable_1") before it has been initialized. In TensorFlow, all variables must be explicitly initialized, by running their "initializer" operations. For convenience, you can run all of the variable initializers in the current session by executing the following statement before your training loop:
tf.initialize_all_variables().run()
请注意，此答案假定与问题一样，您使用的是tf.InteractiveSession，它允许您在不指定会话的情况下运行操作.对于非交互式用途，更常见的是使用tf.Session，并按如下所示进行初始化:
Note that this answer assumes that, as in the question, you are using tf.InteractiveSession, which allows you to run operations without specifying a session. For non-interactive uses, it is more common to use tf.Session, and initialize as follows:
init_op = tf.initialize_all_variables()
sess = tf.Session()
sess.run(init_op)
这篇关于FailedPreconditionError:尝试在Tensorflow中使用未初始化的的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
