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tensorflow: is there a way to specify XLA_GPU with tensorflow?


TensorFlow with PhonegapIs there a way to send data from Tensorflow to Arduino by Bluetooth?Is there a way to replace existing values with NaNRegression with Neural Networks in Tensorflow problemData extraction with TensorflowWhile using TensorFlow, is there some way I can 'create' the input values on the fly?Logistic Regression with Tensorflowproblems with installing tensorflow using anacondaIs there any way to make tensorflow serving server with multiple models linked dataflow?tensorflow: is there a way to specify XLA_GPU with tensorflow?













0












$begingroup$


following code is used to specify device on which tf node is running on



with tf.device('/gpu:0'):
a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')


i have already known:
this post, tensorflow doc and xla demo



what i want to know is:



is there a way to specify XLA_GPU as the device on which tf node is running on



with tf.device('/XLA_GPU:0'):
a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')


executing the code above gives ValueError: Unknown attribute: 'device' in '/job:localhost/replica:0/task:0/device:/XLA_GPU:0'



this is 100% reproducible on google colab.










share|improve this question









$endgroup$



migrated from ai.stackexchange.com 9 hours ago


This question came from our site for people interested in conceptual questions about life and challenges in a world where "cognitive" functions can be mimicked in purely digital environment.






















    0












    $begingroup$


    following code is used to specify device on which tf node is running on



    with tf.device('/gpu:0'):
    a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')


    i have already known:
    this post, tensorflow doc and xla demo



    what i want to know is:



    is there a way to specify XLA_GPU as the device on which tf node is running on



    with tf.device('/XLA_GPU:0'):
    a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')


    executing the code above gives ValueError: Unknown attribute: 'device' in '/job:localhost/replica:0/task:0/device:/XLA_GPU:0'



    this is 100% reproducible on google colab.










    share|improve this question









    $endgroup$



    migrated from ai.stackexchange.com 9 hours ago


    This question came from our site for people interested in conceptual questions about life and challenges in a world where "cognitive" functions can be mimicked in purely digital environment.




















      0












      0








      0





      $begingroup$


      following code is used to specify device on which tf node is running on



      with tf.device('/gpu:0'):
      a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')


      i have already known:
      this post, tensorflow doc and xla demo



      what i want to know is:



      is there a way to specify XLA_GPU as the device on which tf node is running on



      with tf.device('/XLA_GPU:0'):
      a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')


      executing the code above gives ValueError: Unknown attribute: 'device' in '/job:localhost/replica:0/task:0/device:/XLA_GPU:0'



      this is 100% reproducible on google colab.










      share|improve this question









      $endgroup$




      following code is used to specify device on which tf node is running on



      with tf.device('/gpu:0'):
      a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')


      i have already known:
      this post, tensorflow doc and xla demo



      what i want to know is:



      is there a way to specify XLA_GPU as the device on which tf node is running on



      with tf.device('/XLA_GPU:0'):
      a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')


      executing the code above gives ValueError: Unknown attribute: 'device' in '/job:localhost/replica:0/task:0/device:/XLA_GPU:0'



      this is 100% reproducible on google colab.







      python tensorflow






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked yesterday









      fu DLfu DL

      83




      83




      migrated from ai.stackexchange.com 9 hours ago


      This question came from our site for people interested in conceptual questions about life and challenges in a world where "cognitive" functions can be mimicked in purely digital environment.









      migrated from ai.stackexchange.com 9 hours ago


      This question came from our site for people interested in conceptual questions about life and challenges in a world where "cognitive" functions can be mimicked in purely digital environment.






















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          0












          $begingroup$

          try 'device:XLA_GPU:0'



          with tf.device('device:XLA_GPU:0'):
          a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')





          share|improve this answer









          $endgroup$












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            0












            $begingroup$

            try 'device:XLA_GPU:0'



            with tf.device('device:XLA_GPU:0'):
            a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')





            share|improve this answer









            $endgroup$

















              0












              $begingroup$

              try 'device:XLA_GPU:0'



              with tf.device('device:XLA_GPU:0'):
              a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')





              share|improve this answer









              $endgroup$















                0












                0








                0





                $begingroup$

                try 'device:XLA_GPU:0'



                with tf.device('device:XLA_GPU:0'):
                a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')





                share|improve this answer









                $endgroup$



                try 'device:XLA_GPU:0'



                with tf.device('device:XLA_GPU:0'):
                a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')






                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered yesterday







                Yong Jia


































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