According to TF 1:1 Symbols Map, in TF 2.0 you should use tf.compat.v1.Session() instead of tf.Session() https://docs.google.com/spreadsheets/d/1FLFJLzg7WNP6JHODX5q8BDgptKafq_slHpnHVbJIteQ/edit#gid=0 To get TF 1.x like behaviour in TF 2.0 one can run but then one cannot benefit of many improvements made in TF 2.0. For more details please refer to the migration guide https://www.tensorflow.org/guide/migrate
Found the solution: I reinstalled nvidia-381, CUDA-8.0 (using the runfile) and cuDNN 6.0. Then I added the following in my .bashrc:
In a tensorflow model you can define a placeholder such as x = tf.placeholder(tf.float32), then you will use x in your model. For example, I define a simple set of operations as: Now when I ask tensorflow to compute y, it’s clear that y depends on x. This will produce an error because I did … Read more
I found this to finally work. Edit 1: This was tested on Windows (8, 8.1, 10), Mac and Linux. Change python3 to python according to your configuration. Change py3 to py2 in the url if you are using Python 2.x. Edit 2: A list of different versions if someone needs: https://storage.googleapis.com/tensorflow Edit 3: A list of urls for the available wheel packages is available … Read more
This should be possible with tensorflow_gpu-1.9.0. Linked below is a table which displays compatibilities of CUDA and cuDNN with varying versions of tensorflow.
Please try: from tensorflow.keras.models import Sequential instead of from keras.models import Sequential
Refer to tensorflow issue#9701. Run tensorboard –logdir=YOUR_LOG_DIR –host=127.0.0.1 in command prompt, and type localhost:6006 in chrome, this works for me (Win10, anaconda4.3.16, python3.5.3, tensorflow1.1.0).
Apparently the new instructions on TensorFlow website run without issues I just tried the instructions posted on How to Retrain Inception’s Final Layer for New Categories It worked without any problems
I’m trying to implement a skip thought model using tensorflow and a current version is placed here. Currently I using one GPU of my machine (total 2 GPUs) and the GPU info is However, I got OOM when I’m trying to feed data to the model. I try to debug as follow: I use the … Read more
i am facing issue with my inception model during the performance testing with Apache JMeter. Error: OOM when allocating tensor with shape[800,1280,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [[Node: Cast = CastDstT=DT_FLOAT, SrcT=DT_UINT8, _device=”/job:localhost/replica:0/task:0/device:GPU:0″]] Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for … Read more