Why does Tensorflow 1.11.0 return CUDA_ERROR_NOT_SUPPORTED?
My machine is Ubuntu 18.04.1 LTS, with CUDA has been successfully installed. The output of $nvcc --version is
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Sep__1_21:08:03_CDT_2017
Cuda compilation tools, release 9.0, V9.0.176
I have two GPUs of Tesla K80, and the command nvidia-smi shows:
output of nvidia-smi
I also tried to test with ./deviceQuery from NVIDIA_CUDA-9.0_Samples and its output is as the followings:
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 2 CUDA Capable device(s)`
...
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 10.0, CUDA Runtime Version = 9.0, NumDevs = 2
Result = PASS
However, once I install Tensorflow GPU version 1.11.0 from pip, I couldn't open a Tensorflow session.
>>> import tensorflow as tf
>>> sess = tf.Session()
and it outputs:
2018-11-15 00:13:46.593039: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/quoctin.phan/tools/anaconda/envs/tensorflow_1.11/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1511, in __init__
super(Session, self).__init__(target, graph, config=config)
File "/home/quoctin.phan/tools/anaconda/envs/tensorflow_1.11/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 634, in __init__
self._session = tf_session.TF_NewSessionRef(self._graph._c_graph, opts)
tensorflow.python.framework.errors_impl.InternalError: failed initializing StreamExecutor for CUDA device ordinal 0: Internal: failed call to cuDevicePrimaryCtxRetain: CUDA_ERROR_NOT_SUPPORTED: operation not supported
I have tried to reinstall Tensorflow 1.12.0, but nothing changes. Your help is appreciated.
python tensorflow ubuntu-18.04 tesla
asked Nov 15 '18 at 0:19
Quoc Tin PhanQuoc Tin Phan
13
add a comment |
My machine is Ubuntu 18.04.1 LTS, with CUDA has been successfully installed. The output of $nvcc --version is
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Sep__1_21:08:03_CDT_2017
Cuda compilation tools, release 9.0, V9.0.176
I have two GPUs of Tesla K80, and the command nvidia-smi shows:
output of nvidia-smi
I also tried to test with ./deviceQuery from NVIDIA_CUDA-9.0_Samples and its output is as the followings:
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 2 CUDA Capable device(s)`
...
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 10.0, CUDA Runtime Version = 9.0, NumDevs = 2
Result = PASS
However, once I install Tensorflow GPU version 1.11.0 from pip, I couldn't open a Tensorflow session.
>>> import tensorflow as tf
>>> sess = tf.Session()
and it outputs:
2018-11-15 00:13:46.593039: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/quoctin.phan/tools/anaconda/envs/tensorflow_1.11/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1511, in __init__
super(Session, self).__init__(target, graph, config=config)
File "/home/quoctin.phan/tools/anaconda/envs/tensorflow_1.11/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 634, in __init__
self._session = tf_session.TF_NewSessionRef(self._graph._c_graph, opts)
tensorflow.python.framework.errors_impl.InternalError: failed initializing StreamExecutor for CUDA device ordinal 0: Internal: failed call to cuDevicePrimaryCtxRetain: CUDA_ERROR_NOT_SUPPORTED: operation not supported
I have tried to reinstall Tensorflow 1.12.0, but nothing changes. Your help is appreciated.
python tensorflow ubuntu-18.04 tesla
asked Nov 15 '18 at 0:19
Quoc Tin PhanQuoc Tin Phan
13
add a comment |
My machine is Ubuntu 18.04.1 LTS, with CUDA has been successfully installed. The output of $nvcc --version is
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Sep__1_21:08:03_CDT_2017
Cuda compilation tools, release 9.0, V9.0.176
I have two GPUs of Tesla K80, and the command nvidia-smi shows:
output of nvidia-smi
I also tried to test with ./deviceQuery from NVIDIA_CUDA-9.0_Samples and its output is as the followings:
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 2 CUDA Capable device(s)`
...
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 10.0, CUDA Runtime Version = 9.0, NumDevs = 2
Result = PASS
However, once I install Tensorflow GPU version 1.11.0 from pip, I couldn't open a Tensorflow session.
>>> import tensorflow as tf
>>> sess = tf.Session()
and it outputs:
2018-11-15 00:13:46.593039: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/quoctin.phan/tools/anaconda/envs/tensorflow_1.11/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1511, in __init__
super(Session, self).__init__(target, graph, config=config)
File "/home/quoctin.phan/tools/anaconda/envs/tensorflow_1.11/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 634, in __init__
self._session = tf_session.TF_NewSessionRef(self._graph._c_graph, opts)
tensorflow.python.framework.errors_impl.InternalError: failed initializing StreamExecutor for CUDA device ordinal 0: Internal: failed call to cuDevicePrimaryCtxRetain: CUDA_ERROR_NOT_SUPPORTED: operation not supported
I have tried to reinstall Tensorflow 1.12.0, but nothing changes. Your help is appreciated.
python tensorflow ubuntu-18.04 tesla
asked Nov 15 '18 at 0:19
Quoc Tin PhanQuoc Tin Phan
13
My machine is Ubuntu 18.04.1 LTS, with CUDA has been successfully installed. The output of $nvcc --version is
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Sep__1_21:08:03_CDT_2017
Cuda compilation tools, release 9.0, V9.0.176
I have two GPUs of Tesla K80, and the command nvidia-smi shows:
output of nvidia-smi
I also tried to test with ./deviceQuery from NVIDIA_CUDA-9.0_Samples and its output is as the followings:
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 2 CUDA Capable device(s)`
...
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 10.0, CUDA Runtime Version = 9.0, NumDevs = 2
Result = PASS
However, once I install Tensorflow GPU version 1.11.0 from pip, I couldn't open a Tensorflow session.
>>> import tensorflow as tf
>>> sess = tf.Session()
and it outputs:
2018-11-15 00:13:46.593039: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/quoctin.phan/tools/anaconda/envs/tensorflow_1.11/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1511, in __init__
super(Session, self).__init__(target, graph, config=config)
File "/home/quoctin.phan/tools/anaconda/envs/tensorflow_1.11/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 634, in __init__
self._session = tf_session.TF_NewSessionRef(self._graph._c_graph, opts)
tensorflow.python.framework.errors_impl.InternalError: failed initializing StreamExecutor for CUDA device ordinal 0: Internal: failed call to cuDevicePrimaryCtxRetain: CUDA_ERROR_NOT_SUPPORTED: operation not supported
I have tried to reinstall Tensorflow 1.12.0, but nothing changes. Your help is appreciated.
python tensorflow ubuntu-18.04 tesla
python tensorflow ubuntu-18.04 tesla
asked Nov 15 '18 at 0:19
Quoc Tin PhanQuoc Tin Phan
13
asked Nov 15 '18 at 0:19
Quoc Tin PhanQuoc Tin Phan
13
edited Nov 15 '18 at 8:44
Quoc Tin Phan
asked Nov 15 '18 at 0:19
Quoc Tin PhanQuoc Tin Phan
13
asked Nov 15 '18 at 0:19
Quoc Tin PhanQuoc Tin Phan
13
asked Nov 15 '18 at 0:19
Quoc Tin PhanQuoc Tin Phan
13
13
add a comment |
add a comment |
1 Answer
1
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oldest
votes
Do you think your problem might be somehow connected to Compute Capability? The problem is described in here.
You can check them when you run deviceQuery.exe. Here is a thread about where to find it on windows distribution of CUDA package.
answered Dec 15 '18 at 21:58
Renard KorzeniowskiRenard Korzeniowski
1066
I was able to solve it. The problem was the mismatch between NVIDIA-SMI version and Driver Version (here). Thank you!
– Quoc Tin Phan
Jan 2 at 16:31
add a comment |
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1 Answer
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Do you think your problem might be somehow connected to Compute Capability? The problem is described in here.
You can check them when you run deviceQuery.exe. Here is a thread about where to find it on windows distribution of CUDA package.
answered Dec 15 '18 at 21:58
Renard KorzeniowskiRenard Korzeniowski
1066
I was able to solve it. The problem was the mismatch between NVIDIA-SMI version and Driver Version (here). Thank you!
– Quoc Tin Phan
Jan 2 at 16:31
add a comment |
Do you think your problem might be somehow connected to Compute Capability? The problem is described in here.
You can check them when you run deviceQuery.exe. Here is a thread about where to find it on windows distribution of CUDA package.
answered Dec 15 '18 at 21:58
Renard KorzeniowskiRenard Korzeniowski
1066
I was able to solve it. The problem was the mismatch between NVIDIA-SMI version and Driver Version (here). Thank you!
– Quoc Tin Phan
Jan 2 at 16:31
add a comment |
Do you think your problem might be somehow connected to Compute Capability? The problem is described in here.
You can check them when you run deviceQuery.exe. Here is a thread about where to find it on windows distribution of CUDA package.
answered Dec 15 '18 at 21:58
Renard KorzeniowskiRenard Korzeniowski
1066
Do you think your problem might be somehow connected to Compute Capability? The problem is described in here.
You can check them when you run deviceQuery.exe. Here is a thread about where to find it on windows distribution of CUDA package.
answered Dec 15 '18 at 21:58
Renard KorzeniowskiRenard Korzeniowski
1066
answered Dec 15 '18 at 21:58
Renard KorzeniowskiRenard Korzeniowski
1066
answered Dec 15 '18 at 21:58
Renard KorzeniowskiRenard Korzeniowski
1066
answered Dec 15 '18 at 21:58
Renard KorzeniowskiRenard Korzeniowski
1066
1066
I was able to solve it. The problem was the mismatch between NVIDIA-SMI version and Driver Version (here). Thank you!
– Quoc Tin Phan
Jan 2 at 16:31
add a comment |
I was able to solve it. The problem was the mismatch between NVIDIA-SMI version and Driver Version (here). Thank you!
– Quoc Tin Phan
Jan 2 at 16:31
I was able to solve it. The problem was the mismatch between NVIDIA-SMI version and Driver Version (here). Thank you!
– Quoc Tin Phan
Jan 2 at 16:31
I was able to solve it. The problem was the mismatch between NVIDIA-SMI version and Driver Version (here). Thank you!
– Quoc Tin Phan
Jan 2 at 16:31
add a comment |
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