Open Zumbalamambo opened 6 years ago
I'm not sure what happened here. My dependencies: tensorflow 1.0.0 python 3.5.2
Are you inferencing in gpu or cpu?
GPU. This model was trained on Titan X and it can run on GTX 940.
I read that this issue is caused because tf.nn.max_pool_with_argmax is only supported on GPU. @Joker316701882 if you post your code for the graph, I can fix the issue
Looks like some issue with the new tensorflow commits of Conv2D definition as well. They change the property name of stride to "dilations" and it's causing some errors because the code is old. Is there any chance you can publish your code or change it so we can try running it?
I ran into the same issue, and tried eliminating the GPU dependencies via 'clear_devices=True'. Didn't work. @saeed68gm - did you find any other solution? I'm running on Python 2.7 and TF 1.4
I have same issue,could you tell me how to solve?
@LRLLRL @YedidyahD I did some more research and it looks like the operation MaxPoolWithArgmax is missing from tensorflow cpu operations. So my suggestion is that you modify the source code of tensorflow to add this op. I have posted a patch for a work around on this thread: https://github.com/tensorflow/tensorflow/issues/6035
it should work on tf 1.4 source code.
Let me know if you can get it to work.
i have same promblem. i used win10 python 3.5.4 gtx1060 3g
but command python--rgb = animal.jpg
show oom
By installing tensorflow-gpu 1.0.0, it seems solved the problem of @Zumbalamambo . But i met another problem of memory. Did it need so large memory of 10.9GB just test an image?
I tensorflow/core/common_runtime/gpu/gpu_device.cc:885] Found device 0 with properties: name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate (GHz) 1.683 pciBusID 0000:65:00.0 Total memory: 10.91GiB Free memory: 10.49GiB I tensorflow/core/common_runtime/gpu/gpu_device.cc:906] DMA: 0 I tensorflow/core/common_runtime/gpu/gpu_device.cc:916] 0: Y I tensorflow/core/common_runtime/gpu/gpu_device.cc:975] Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:65:00.0) E tensorflow/stream_executor/cuda/cuda_driver.cc:1002] failed to allocate 10.91G (11713708032 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY F tensorflow/stream_executor/cuda/cuda_dnn.cc:222] Check failed: s.ok() could not find cudnnCreate in cudnn DSO; dlerror: /home/usr/.virtualenvs/salient_detection/lib/python3.6/site-packages/tensorflow/python/_pywrap_tensorflow.so: undefined symbol: cudnnCreate Aborted (core dumped)
Sorry,I can not solve this problem.
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@Zumbalamambo Did you solve you problem?I met the same problem.
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@liutianling You can fix it by changing it to gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.333) in the inference.py
I tried to run on top of an image as python inference.py --rgb=Chris.jpg...
im getting the following error,