Prettytensor:尝试使用未初始化的值 [英] Prettytensor: Attempting to use uninitialized value

问题描述

我正在关注这些教程: https://www.youtube.com/watch?v=wuo4JdG3SvU&list= PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ
在教程4中介绍了prettytensor.
在学习完本教程之后，我编写了以下代码来运行一个小型神经网络:

I'm following these tutorials: https://www.youtube.com/watch?v=wuo4JdG3SvU&list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ
and prettytensor is introduced in tutorial 4.
Following the tutorial, i wrote this code to run a small neural network:

import tensorflow as tf
# Use PrettyTensor to simplify Neural Network construction.
import prettytensor as pt

from tensorflow.examples.tutorials.mnist import input_data
data = input_data.read_data_sets('../data/MNIST/', one_hot=True)

# We know that MNIST images are 28 pixels in each dimension.
img_size = 28
# Images are stored in one-dimensional arrays of this length.
img_size_flat = img_size * img_size
# Tuple with height and width of images used to reshape arrays.
img_shape = (img_size, img_size)
# Number of colour channels for the images: 1 channel for gray-scale.
num_channels = 1
# Number of classes, one class for each of 10 digits.
num_classes = 10

# the placeholders
x = tf.placeholder(tf.float32, shape=[None, img_size_flat], name='x')
x_image = tf.reshape(x, [-1, img_size, img_size, num_channels])
y_true = tf.placeholder(tf.float32, shape=[None, 10], name='y_true')

# use prettyTensor to build the model
# this will give us the predictions and the loss functions
x_pretty = pt.wrap(x_image)
with pt.defaults_scope(activation_fn=tf.nn.relu):
    y_pred, loss = x_pretty.\
        conv2d(kernel=5, depth=16, name='layer_conv1').\
        max_pool(kernel=2, stride=2).\
        conv2d(kernel=5, depth=36, name='layer_conv2').\
        max_pool(kernel=2, stride=2).\
        flatten().\
        fully_connected(size=128, name='layer_fc1').\
        softmax_classifier(class_count=10, labels=y_true)

# the model optimizer
optimizer = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(loss)

# the model testing 
correct_prediction = tf.equal(tf.argmax(y_pred,1), tf.argmax(y_true,1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))

# start the session
session = tf.InteractiveSession()

# Start the training
tf.global_variables_initializer().run(session = session)
train_batch_size = 64    
for i in range(1000):
    print("training batch ",i)
    x_batch, y_true_batch = data.train.next_batch(train_batch_size)
    session.run(optimizer, feed_dict={x:x_batch, y_true:y_true_batch})

当我尝试运行它时，出现以下错误:

When i tried to run it, I got the following error:

tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value layer_conv1/bias
     [[Node: layer_conv1/bias/read = Identity[T=DT_FLOAT, _class=["loc:@layer_conv1/bias"], _device="/job:localhost/replica:0/task:0/cpu:0"](layer_conv1/bias)]]

Caused by op u'layer_conv1/bias/read', defined at:
  File "/home/gal/Documents/Workspace/EclipseWorkspace/Melanoma Classification!/tutorial4/tutorial4Test.py", line 31, in <module>

完整的错误跟踪:

Traceback (most recent call last):
  File "/home/gal/Documents/Workspace/EclipseWorkspace/Melanoma Classification!/tutorial4/tutorial4Test.py", line 55, in <module>
    session.run(optimizer, feed_dict={x:x_batch, y_true:y_true_batch})
  File "/home/gal/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 766, in run
    run_metadata_ptr)
  File "/home/gal/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 964, in _run
    feed_dict_string, options, run_metadata)
  File "/home/gal/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1014, in _do_run
    target_list, options, run_metadata)
  File "/home/gal/anaconda2/lib/python2.7/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 layer_conv1/bias
     [[Node: layer_conv1/bias/read = Identity[T=DT_FLOAT, _class=["loc:@layer_conv1/bias"], _device="/job:localhost/replica:0/task:0/cpu:0"](layer_conv1/bias)]]

Caused by op u'layer_conv1/bias/read', defined at:
  File "/home/gal/Documents/Workspace/EclipseWorkspace/Melanoma Classification!/tutorial4/tutorial4Test.py", line 31, in <module>
    conv2d(kernel=5, depth=16, name='layer_conv1').\
  File "/home/gal/anaconda2/lib/python2.7/site-packages/prettytensor/pretty_tensor_class.py", line 1981, in method
    result = func(non_seq_layer, *args, **kwargs)
  File "/home/gal/anaconda2/lib/python2.7/site-packages/prettytensor/pretty_tensor_image_methods.py", line 163, in __call__
    y += self.variable('bias', [size[-1]], bias_init, dt=dtype)
  File "/home/gal/anaconda2/lib/python2.7/site-packages/prettytensor/pretty_tensor_class.py", line 1695, in variable
    collections=variable_collections)
  File "/home/gal/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 1024, in get_variable
    custom_getter=custom_getter)
  File "/home/gal/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 850, in get_variable
    custom_getter=custom_getter)
  File "/home/gal/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 346, in get_variable
    validate_shape=validate_shape)
  File "/home/gal/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 331, in _true_getter
    caching_device=caching_device, validate_shape=validate_shape)
  File "/home/gal/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/variable_scope.py", line 677, in _get_single_variable
    expected_shape=shape)
  File "/home/gal/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/variables.py", line 224, in __init__
    expected_shape=expected_shape)
  File "/home/gal/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/variables.py", line 370, in _init_from_args
    self._snapshot = array_ops.identity(self._variable, name="read")
  File "/home/gal/anaconda2/lib/python2.7/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 "/home/gal/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 759, in apply_op
    op_def=op_def)
  File "/home/gal/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2240, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/home/gal/anaconda2/lib/python2.7/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 layer_conv1/bias
     [[Node: layer_conv1/bias/read = Identity[T=DT_FLOAT, _class=["loc:@layer_conv1/bias"], _device="/job:localhost/replica:0/task:0/cpu:0"](layer_conv1/bias)]]

所以我的问题是，我该如何解决此错误?

So my question is, How can i solve this error?

推荐答案

此问题是由 bug ，以及Pretty Tensor使用已过时的TensorFlow API(为此我打开了

This problem is caused by a bug in the 0.12rc0 release candidate of TensorFlow, and the fact that Pretty Tensor uses a deprecated TensorFlow API (for which I've opened an issue).

在修复此错误之前，我能想到的最佳解决方法是破解.在import tensorflow as tf之后，在程序顶部添加以下行:

Until this bug is fixed, the best workaround I can think of is a hack. Add the following line at the top of your program, after import tensorflow as tf:

tf.GraphKeys.VARIABLES = tf.GraphKeys.GLOBAL_VARIABLES

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