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Problem in running main.py #15

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denabazazian opened this issue Feb 18, 2020 · 2 comments
Open

Problem in running main.py #15

denabazazian opened this issue Feb 18, 2020 · 2 comments

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@denabazazian
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I have this error when I am running the python3 main.py InceptionTime :

iter 0
dataset_name: Coffee
Already_done /media/Disk1/projects/Time_series/data/results/inception/TSC/ Coffee
dataset_name: Meat
Already_done /media/cttc/Disk1/projects/Time_series/data/results/inception/TSC/ Meat
iter 1
dataset_name: Coffee
Already_done /media/Disk1/projects/Time_series/data/results/inception/TSC_itr_1/ Coffee
dataset_name: Meat
Already_done /media/cttc/Disk1/projects/Time_series/data/results/inception/TSC_itr_1/ Meat
iter 2
dataset_name: Coffee
Already_done /media/Disk1/projects/Time_series/data/results/inception/TSC_itr_2/ Coffee
dataset_name: Meat
Already_done /media/cttc/Disk1/projects/Time_series/data/results/inception/TSC_itr_2/ Meat
iter 3
dataset_name: Coffee
Already_done /media/Disk1/projects/Time_series/data/results/inception/TSC_itr_3/ Coffee
dataset_name: Meat
Already_done /media/cttc/Disk1/projects/Time_series/data/results/inception/TSC_itr_3/ Meat
iter 4
dataset_name: Coffee
Using TensorFlow backend.
2020-02-18 11:55:41.451561: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2020-02-18 11:55:41.553535: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:964] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2020-02-18 11:55:41.553936: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1432] Found device 0 with properties:
name: GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.545
pciBusID: 0000:0a:00.0
totalMemory: 10.76GiB freeMemory: 10.32GiB
2020-02-18 11:55:41.553949: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1511] Adding visible gpu devices: 0
2020-02-18 11:55:41.742036: I tensorflow/core/common_runtime/gpu/gpu_device.cc:982] Device interconnect StreamExecutor with strength 1 edge matrix:
2020-02-18 11:55:41.742067: I tensorflow/core/common_runtime/gpu/gpu_device.cc:988] 0
2020-02-18 11:55:41.742072: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1001] 0: N
2020-02-18 11:55:41.742141: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9960 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:0a:00.0, compute capability: 7.5)
Segmentation fault (core dumped)

I have 10.32GiB free memory on the GPU and I suppose this error didn't raise due to the lack of memory space since it would occupy 9960 MB in memory.
In any case I also tried to reduce the data size based on this line but it was not very clear about how can we manage it if the data is too big.
I have also tried to run it just with 'Coffee' by editing this line to UNIVARIATE_DATASET_NAMES = ['Coffee'], but the memory is still 9960 MB and I have the same error.
I have also tried to run python3 main.py InceptionTime_xp, but the same error happened.
I would appreciate it if you could provide any clue that why this error happens and how can I solve it.

@hfawaz
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hfawaz commented Feb 18, 2020

Thanks for sharing the issue.
I am not sure if such problem is due to using another version of tensorflow.
I will be updating the repository soon to make sure we are using tensorflow 2.1
Stay tuned for the update.

@denabazazian
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Thanks for your quick reply @hfawaz .
I have installed the same tensorflow version (1.12.0) as you mentioned in requirements. I don't think if the problem is related to the TF version.

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