Ich arbeite mich durch das SensorFlow Tutorial, das ein "seltsames" Format verwendet, um die Daten hochzuladen. Ich möchte das NumPy- oder Pandas-Format für die Daten verwenden, damit ich sie mit den Ergebnissen von Scikit-Learn vergleichen kann.

Ich erhalte die Ziffernerkennungsdaten von Kaggle:https: //www.kaggle.com/c/digit-recognizer/dat.

Hier ist der Code aus dem TensorFlow-Tutorial (was gut funktioniert):

# 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)

Hier lese ich die Daten, entferne die Zielvariablen und teile die Daten in Test- und Trainingsdatensätze auf (alles funktioniert einwandfrei):

# 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)

enn ich jetzt versuche, den Trainingsschritt auszuführen, erhalte ich einFailedPreconditionError:

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})

Hier ist der vollständige Fehler:

---------------------------------------------------------------------------
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()

Haben Sie eine Idee, wie ich das beheben kann?