When use Dataset API, got device placement error with tensorflow >= 1.11










1















My script used dataset API to realize input pipeline. When I use tensorflow 1.10, everything is ok, but when I upgrade to tensorflow 1.11 or 1.12. I got the following error message at the beginning of training:



Attempted create an iterator on device "/job:localhost/replica:0/task:0/device:GPU:0" from handle defined on device "/job:localhost/replica:0/task:0/device:CPU:0"



Here are piece of my code:



def build_all_dataset(self):
self.build_dataset(ROUTE_TRAIN)
self.build_dataset(ROUTE_VALIDATION)
self.build_dataset(ROUTE_TEST)

def build_dataset(self, p_route):
# Create dataset instance.
# ......
# ......

self.dataset[p_route] = dataset
self.iterators[p_route] = dataset.make_initializable_iterator()
self.handles[p_route] = (self.iterators[p_route].string_handle()).eval()

def build_model(self):
with tf.device("/GPU:0"):
# Build dataset for training/validation/test.
self.build_all_dataset()
self.ph_dataset_handle = tf.placeholder(tf.string, shape=)
iterator = tf.data.Iterator.from_string_handle(self.ph_dataset_handle, self.dataset[ROUTE_TRAIN].output_types,
self.dataset[ROUTE_TRAIN].output_shapes)

xxx, xxx, xxx = iterator.get_next()
# Build the following graph.
# ......
# ......

while True:
try:
session.run(xxx, self.ph_dataset_handle: self.handles[ROUTE_TRAIN])
except tf.errors.OutOfRangeError:
break


I checked that the placeholder "self.ph_dataset_handle" is placed on /GPU:0, why tensorflow said "handle defined on device"/job:localhost/replica:0/task:0/device:CPU:0"?



Could you please give any insight? Thanks!










share|improve this question


























    1















    My script used dataset API to realize input pipeline. When I use tensorflow 1.10, everything is ok, but when I upgrade to tensorflow 1.11 or 1.12. I got the following error message at the beginning of training:



    Attempted create an iterator on device "/job:localhost/replica:0/task:0/device:GPU:0" from handle defined on device "/job:localhost/replica:0/task:0/device:CPU:0"



    Here are piece of my code:



    def build_all_dataset(self):
    self.build_dataset(ROUTE_TRAIN)
    self.build_dataset(ROUTE_VALIDATION)
    self.build_dataset(ROUTE_TEST)

    def build_dataset(self, p_route):
    # Create dataset instance.
    # ......
    # ......

    self.dataset[p_route] = dataset
    self.iterators[p_route] = dataset.make_initializable_iterator()
    self.handles[p_route] = (self.iterators[p_route].string_handle()).eval()

    def build_model(self):
    with tf.device("/GPU:0"):
    # Build dataset for training/validation/test.
    self.build_all_dataset()
    self.ph_dataset_handle = tf.placeholder(tf.string, shape=)
    iterator = tf.data.Iterator.from_string_handle(self.ph_dataset_handle, self.dataset[ROUTE_TRAIN].output_types,
    self.dataset[ROUTE_TRAIN].output_shapes)

    xxx, xxx, xxx = iterator.get_next()
    # Build the following graph.
    # ......
    # ......

    while True:
    try:
    session.run(xxx, self.ph_dataset_handle: self.handles[ROUTE_TRAIN])
    except tf.errors.OutOfRangeError:
    break


    I checked that the placeholder "self.ph_dataset_handle" is placed on /GPU:0, why tensorflow said "handle defined on device"/job:localhost/replica:0/task:0/device:CPU:0"?



    Could you please give any insight? Thanks!










    share|improve this question
























      1












      1








      1








      My script used dataset API to realize input pipeline. When I use tensorflow 1.10, everything is ok, but when I upgrade to tensorflow 1.11 or 1.12. I got the following error message at the beginning of training:



      Attempted create an iterator on device "/job:localhost/replica:0/task:0/device:GPU:0" from handle defined on device "/job:localhost/replica:0/task:0/device:CPU:0"



      Here are piece of my code:



      def build_all_dataset(self):
      self.build_dataset(ROUTE_TRAIN)
      self.build_dataset(ROUTE_VALIDATION)
      self.build_dataset(ROUTE_TEST)

      def build_dataset(self, p_route):
      # Create dataset instance.
      # ......
      # ......

      self.dataset[p_route] = dataset
      self.iterators[p_route] = dataset.make_initializable_iterator()
      self.handles[p_route] = (self.iterators[p_route].string_handle()).eval()

      def build_model(self):
      with tf.device("/GPU:0"):
      # Build dataset for training/validation/test.
      self.build_all_dataset()
      self.ph_dataset_handle = tf.placeholder(tf.string, shape=)
      iterator = tf.data.Iterator.from_string_handle(self.ph_dataset_handle, self.dataset[ROUTE_TRAIN].output_types,
      self.dataset[ROUTE_TRAIN].output_shapes)

      xxx, xxx, xxx = iterator.get_next()
      # Build the following graph.
      # ......
      # ......

      while True:
      try:
      session.run(xxx, self.ph_dataset_handle: self.handles[ROUTE_TRAIN])
      except tf.errors.OutOfRangeError:
      break


      I checked that the placeholder "self.ph_dataset_handle" is placed on /GPU:0, why tensorflow said "handle defined on device"/job:localhost/replica:0/task:0/device:CPU:0"?



      Could you please give any insight? Thanks!










      share|improve this question














      My script used dataset API to realize input pipeline. When I use tensorflow 1.10, everything is ok, but when I upgrade to tensorflow 1.11 or 1.12. I got the following error message at the beginning of training:



      Attempted create an iterator on device "/job:localhost/replica:0/task:0/device:GPU:0" from handle defined on device "/job:localhost/replica:0/task:0/device:CPU:0"



      Here are piece of my code:



      def build_all_dataset(self):
      self.build_dataset(ROUTE_TRAIN)
      self.build_dataset(ROUTE_VALIDATION)
      self.build_dataset(ROUTE_TEST)

      def build_dataset(self, p_route):
      # Create dataset instance.
      # ......
      # ......

      self.dataset[p_route] = dataset
      self.iterators[p_route] = dataset.make_initializable_iterator()
      self.handles[p_route] = (self.iterators[p_route].string_handle()).eval()

      def build_model(self):
      with tf.device("/GPU:0"):
      # Build dataset for training/validation/test.
      self.build_all_dataset()
      self.ph_dataset_handle = tf.placeholder(tf.string, shape=)
      iterator = tf.data.Iterator.from_string_handle(self.ph_dataset_handle, self.dataset[ROUTE_TRAIN].output_types,
      self.dataset[ROUTE_TRAIN].output_shapes)

      xxx, xxx, xxx = iterator.get_next()
      # Build the following graph.
      # ......
      # ......

      while True:
      try:
      session.run(xxx, self.ph_dataset_handle: self.handles[ROUTE_TRAIN])
      except tf.errors.OutOfRangeError:
      break


      I checked that the placeholder "self.ph_dataset_handle" is placed on /GPU:0, why tensorflow said "handle defined on device"/job:localhost/replica:0/task:0/device:CPU:0"?



      Could you please give any insight? Thanks!







      python tensorflow tensorflow-datasets






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      asked Nov 14 '18 at 7:44









      ShuaiShuai

      63




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