FailedPreconditionError Attempting to use uninitialized in Tensorflow

Question

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   I get the digit recognition data from Kaggle  https   www kaggle com c digit-recognizer data   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    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    lt  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    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     Here s the full error   --------------------------------------------------------------------------- FailedPreconditionError                   Traceback  most recent call last   lt ipython-input-82-967faab7d494 gt  in  lt module gt          4     Target batch   np array OHTarget i 50 i 50 50  values        5     Target batch   np multiply Target batch  1 0   255 0  ---- gt  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         - gt  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    - gt  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  -- gt  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  -- gt  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   lt ipython-input-45-59183d86e462 gt    line 1  in  lt module gt      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     Any ideas as to how I can fix this

User · Answer

When I had this issue with tf train string input producer   and tf train batch   initializing the local variables before I started the Coordinator solved the problem  I had been getting the error when I initialized the local variables after starting the Coordinator

User · Answer

Different use case  but set your session as the default session did the trick for me   with sess as default        result   compute fn  seed input 1     This is one of these mistakes that is so obvious  once you have solved it    My use-case is the following   1  store keras VGG16 as tensorflow graph  2  load kers VGG16 as a graph  3  run tf function on the graph and get    FailedPreconditionError  Attempting to use uninitialized value block1 conv2 bias        Node  block1 conv2 bias read   Identity T DT FLOAT   class   loc  block1 conv2 bias     device   job localhost replica 0 task 0 device GPU 0   block1 conv2 bias           Node  predictions Softmax  7    Recv client terminated false  recv device   job localhost replica 0 task 0 device CPU 0   send device   job localhost replica 0 task 0 device GPU 0   send device incarnation 1  tensor name  edge 168 predictions Softmax   tensor type DT FLOAT   device   job localhost replica 0 task 0 device CPU 0

User · Answer

From official documentation  FailedPreconditionError      This exception is most commonly raised when running an operation that   reads a tf Variable before it has been initialized    In your case the error even explains what variable was not initialized  Attempting to use uninitialized value Variable 1  One of the TF tutorials explains a lot about variables  their creation initialization saving loading  Basically to initialize the variable you have 3 options    initialize all global variables with tf global variables initializer   initialize variables you care about with tf variables initializer list of vars   Notice that you can use this function to mimic global variable initializer  tf variable initializers tf global variables    initialize only one variable with var name initializer   I almost always use the first approach  Remember you should put it inside a session run  So you will get something like this   with tf Session   as sess      sess run tf global variables initializer      If your are curious about more information about variables  read this documentation to know how to report uninitialized variables and check is variable initialized

User · Answer

You have to initialize variables before using them    If you try to evaluate the variables before initializing them you ll run into  FailedPreconditionError  Attempting to use uninitialized value tensor   The easiest way is initializing all variables at once using  tf global variables initializer    init   tf global variables initializer   with tf Session   as sess      sess run init    You use sess run init  to run the initializer  without fetching any value   To initialize only a subset of variables  you use tf variables initializer   listing the variables   var ab   tf variables initializer  a  b   name  a and b   with tf Session   as sess      sess run var ab    You can also initialize each variable separately using tf Variable initializer    create variable W as 784 x 10 tensor  filled with zeros W   tf Variable tf zeros  784 10    with tf Session   as sess      sess run W initializer

User · Answer

I got this error message from a completely different case  It seemed that the exception handler in tensorflow raised it  You can check each row in the Traceback  In my case  it happened in tensorflow python lib io file io py  because this file contained a different bug  where self   mode and self   name weren t initialized  and it needed to call self  FileIO  mode  and self FileIO  name instead

User · Answer

Tensorflow 2 0 Compatible Answer  In Tensorflow Version    2 0  the command for Initializing all the Variables if we use Graph Mode  to fix the FailedPreconditionError is shown below   tf compat v1 global variables initializer   This is just a shortcut for variables initializer global variables     It returns an Op that initializes global variables in the graph

User · Answer

The FailedPreconditionError comes because the session is trying to read a variable that hasn t been initialized   As of Tensorflow version 1 11 0  you need to take this    init op   tf global variables initializer    sess   tf Session   sess run init op

User · Answer

With tensorflow version  3 2 you may use this command   x1   tf Variable 5  y1   tf Variable 3   z1   x1   y1  init   tf compat v1 global variables initializer   with tf compat v1 Session   as sess      init run       print sess run z1     The output  8  will be displayed

User · Answer

Possibly something has changed in recent TensorFlow builds  because for me  running  sess   tf Session   sess run tf local variables initializer      before fitting any models seems to do the trick   Most older examples and comments seem to suggest tf global variables initializer

User · Answer

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     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

User · Answer

tf initialize all variables   is deprecated  Instead initialize tensorflow variables with    tf global variables initializer     A common example usage is   with tf Session   as sess       sess run tf global variables initializer

[python] FailedPreconditionError: Attempting to use uninitialized in Tensorflow

Examples related to python

Examples related to pandas

Examples related to classification

Examples related to tensorflow