Keras in PyCharm not using GPU
These threads did not solve my problem:
Keras does not use GPU on Pycharm having python 3.5 and Tensorflow 1.4
Keras with TensorFlow backend not using GPU
I have installed Tensorflow and Tensorflow-gpu (v.1.12.0) on my PC which is running Windows 10 and has GTX 750 Ti graphics card, So it does support CUDA. I have also installed CUDA Toolkit v10 and cuDNN libraries and when I run nvcc -V on command prompt I get:
nvcc: NVIDIA (R) Cuda compiler...
I am using PyCharm and I don't have any problem running Keras on CPU. But it doesn't use my GPU.
When I type
from keras import backend as K
K.tensorflow_backend._get_available_gpus()
it says
2018-11-25 10:47:57.448275: I tensorflow/core/platform/cpu_feature_gaurd.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
[ ]
What I have tried:
1) I tried uninstalling Tensorflow and Tensorflow-gpu and reinstalling Tensorflow-gpu like the above thread says. Didn't work and my code didn't run on CPU anymore and gave an error regarding Tensorflow. Once I reinstalled Tensorflow, It was OK again.
2) I tried using a library named Theano, which is mentioned on Keras official documentation here. When I add the following lines
import theano
theano.config.device='gpu'
theano.config.floatX='float32'
it says
WARNING (theano.configdefaults): g++ not available, if using conda: 'conda install m2w64-toolchain'
C:UsersHOME-PCPyCharmProjectsenvlibsite-packagestheanoconfigdefaults.py.=:560: UserWarning: DeprecationWarning: there is no c++ compiler.This is deprecated and with theano 0.11 a c++ compiler will be mandatory. warning.warn("DeprecationWarning: there is no c++ compiler."
3) I tried adding these lines and also nothing happened.
import os
os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"]="0"
What am I missing here? How should I introduce CUDA to PyCharm?
tensorflow keras pycharm cudnn
edited Nov 25 '18 at 7:35
talonmies
59.5k17129198
asked Nov 25 '18 at 7:22
AlirezaAlireza
15611
|
show 9 more comments
These threads did not solve my problem:
Keras does not use GPU on Pycharm having python 3.5 and Tensorflow 1.4
Keras with TensorFlow backend not using GPU
I have installed Tensorflow and Tensorflow-gpu (v.1.12.0) on my PC which is running Windows 10 and has GTX 750 Ti graphics card, So it does support CUDA. I have also installed CUDA Toolkit v10 and cuDNN libraries and when I run nvcc -V on command prompt I get:
nvcc: NVIDIA (R) Cuda compiler...
I am using PyCharm and I don't have any problem running Keras on CPU. But it doesn't use my GPU.
When I type
from keras import backend as K
K.tensorflow_backend._get_available_gpus()
it says
2018-11-25 10:47:57.448275: I tensorflow/core/platform/cpu_feature_gaurd.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
[ ]
What I have tried:
1) I tried uninstalling Tensorflow and Tensorflow-gpu and reinstalling Tensorflow-gpu like the above thread says. Didn't work and my code didn't run on CPU anymore and gave an error regarding Tensorflow. Once I reinstalled Tensorflow, It was OK again.
2) I tried using a library named Theano, which is mentioned on Keras official documentation here. When I add the following lines
import theano
theano.config.device='gpu'
theano.config.floatX='float32'
it says
WARNING (theano.configdefaults): g++ not available, if using conda: 'conda install m2w64-toolchain'
C:UsersHOME-PCPyCharmProjectsenvlibsite-packagestheanoconfigdefaults.py.=:560: UserWarning: DeprecationWarning: there is no c++ compiler.This is deprecated and with theano 0.11 a c++ compiler will be mandatory. warning.warn("DeprecationWarning: there is no c++ compiler."
3) I tried adding these lines and also nothing happened.
import os
os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"]="0"
What am I missing here? How should I introduce CUDA to PyCharm?
tensorflow keras pycharm cudnn
edited Nov 25 '18 at 7:35
talonmies
59.5k17129198
asked Nov 25 '18 at 7:22
AlirezaAlireza
15611
1
So uninstalling tensorflow and keras didn't help?
– Matthieu Brucher
Nov 25 '18 at 8:55
1
But if it fails to load the native runtime, that's all right, that what we want. The native runtime is the CPU one.
– Matthieu Brucher
Nov 25 '18 at 9:07
1
So if you don't have TF, only TF-gpu, you get a failure with keras? Did you try using the TF keras layers instead of keras directly?
– Matthieu Brucher
Nov 25 '18 at 9:12
1
They are intensorflow.keras, so you should be able to dofrom TensorFlow import kerasand use the API more or less like before (tensorflow.org/guide/keras). If you use this API, you can havetensorflow.
– Matthieu Brucher
Nov 25 '18 at 9:20
2
Are you sure that you installed "exactly" the Cuda version required by tensorflow 1.4? Tensoflow is picky and it needs "excactly" the one version that is compatible. I suggest you go to the latest tensorflow and install the exact Cuda version it says in the tutorial. -- You cannot have both tensorflow and tensorflow-gpu. Install only tensorflow GPU (if you're using conda, give a try at installing keras-gpu)
– Daniel Möller
Nov 27 '18 at 18:24
|
show 9 more comments
These threads did not solve my problem:
Keras does not use GPU on Pycharm having python 3.5 and Tensorflow 1.4
Keras with TensorFlow backend not using GPU
I have installed Tensorflow and Tensorflow-gpu (v.1.12.0) on my PC which is running Windows 10 and has GTX 750 Ti graphics card, So it does support CUDA. I have also installed CUDA Toolkit v10 and cuDNN libraries and when I run nvcc -V on command prompt I get:
nvcc: NVIDIA (R) Cuda compiler...
I am using PyCharm and I don't have any problem running Keras on CPU. But it doesn't use my GPU.
When I type
from keras import backend as K
K.tensorflow_backend._get_available_gpus()
it says
2018-11-25 10:47:57.448275: I tensorflow/core/platform/cpu_feature_gaurd.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
[ ]
What I have tried:
1) I tried uninstalling Tensorflow and Tensorflow-gpu and reinstalling Tensorflow-gpu like the above thread says. Didn't work and my code didn't run on CPU anymore and gave an error regarding Tensorflow. Once I reinstalled Tensorflow, It was OK again.
2) I tried using a library named Theano, which is mentioned on Keras official documentation here. When I add the following lines
import theano
theano.config.device='gpu'
theano.config.floatX='float32'
it says
WARNING (theano.configdefaults): g++ not available, if using conda: 'conda install m2w64-toolchain'
C:UsersHOME-PCPyCharmProjectsenvlibsite-packagestheanoconfigdefaults.py.=:560: UserWarning: DeprecationWarning: there is no c++ compiler.This is deprecated and with theano 0.11 a c++ compiler will be mandatory. warning.warn("DeprecationWarning: there is no c++ compiler."
3) I tried adding these lines and also nothing happened.
import os
os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"]="0"
What am I missing here? How should I introduce CUDA to PyCharm?
tensorflow keras pycharm cudnn
edited Nov 25 '18 at 7:35
talonmies
59.5k17129198
asked Nov 25 '18 at 7:22
AlirezaAlireza
15611
These threads did not solve my problem:
Keras does not use GPU on Pycharm having python 3.5 and Tensorflow 1.4
Keras with TensorFlow backend not using GPU
I have installed Tensorflow and Tensorflow-gpu (v.1.12.0) on my PC which is running Windows 10 and has GTX 750 Ti graphics card, So it does support CUDA. I have also installed CUDA Toolkit v10 and cuDNN libraries and when I run nvcc -V on command prompt I get:
nvcc: NVIDIA (R) Cuda compiler...
I am using PyCharm and I don't have any problem running Keras on CPU. But it doesn't use my GPU.
When I type
from keras import backend as K
K.tensorflow_backend._get_available_gpus()
it says
2018-11-25 10:47:57.448275: I tensorflow/core/platform/cpu_feature_gaurd.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
[ ]
What I have tried:
1) I tried uninstalling Tensorflow and Tensorflow-gpu and reinstalling Tensorflow-gpu like the above thread says. Didn't work and my code didn't run on CPU anymore and gave an error regarding Tensorflow. Once I reinstalled Tensorflow, It was OK again.
2) I tried using a library named Theano, which is mentioned on Keras official documentation here. When I add the following lines
import theano
theano.config.device='gpu'
theano.config.floatX='float32'
it says
WARNING (theano.configdefaults): g++ not available, if using conda: 'conda install m2w64-toolchain'
C:UsersHOME-PCPyCharmProjectsenvlibsite-packagestheanoconfigdefaults.py.=:560: UserWarning: DeprecationWarning: there is no c++ compiler.This is deprecated and with theano 0.11 a c++ compiler will be mandatory. warning.warn("DeprecationWarning: there is no c++ compiler."
3) I tried adding these lines and also nothing happened.
import os
os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID"
os.environ["CUDA_VISIBLE_DEVICES"]="0"
What am I missing here? How should I introduce CUDA to PyCharm?
tensorflow keras pycharm cudnn
tensorflow keras pycharm cudnn
edited Nov 25 '18 at 7:35
talonmies
59.5k17129198
asked Nov 25 '18 at 7:22
AlirezaAlireza
15611
edited Nov 25 '18 at 7:35
talonmies
59.5k17129198
asked Nov 25 '18 at 7:22
AlirezaAlireza
15611
edited Nov 25 '18 at 7:35
talonmies
59.5k17129198
edited Nov 25 '18 at 7:35
talonmies
59.5k17129198
edited Nov 25 '18 at 7:35
talonmies
59.5k17129198
59.5k17129198
asked Nov 25 '18 at 7:22
AlirezaAlireza
15611
asked Nov 25 '18 at 7:22
AlirezaAlireza
15611
asked Nov 25 '18 at 7:22
AlirezaAlireza
15611
15611
1
So uninstalling tensorflow and keras didn't help?
– Matthieu Brucher
Nov 25 '18 at 8:55
1
But if it fails to load the native runtime, that's all right, that what we want. The native runtime is the CPU one.
– Matthieu Brucher
Nov 25 '18 at 9:07
1
So if you don't have TF, only TF-gpu, you get a failure with keras? Did you try using the TF keras layers instead of keras directly?
– Matthieu Brucher
Nov 25 '18 at 9:12
1
They are intensorflow.keras, so you should be able to dofrom TensorFlow import kerasand use the API more or less like before (tensorflow.org/guide/keras). If you use this API, you can havetensorflow.
– Matthieu Brucher
Nov 25 '18 at 9:20
2
Are you sure that you installed "exactly" the Cuda version required by tensorflow 1.4? Tensoflow is picky and it needs "excactly" the one version that is compatible. I suggest you go to the latest tensorflow and install the exact Cuda version it says in the tutorial. -- You cannot have both tensorflow and tensorflow-gpu. Install only tensorflow GPU (if you're using conda, give a try at installing keras-gpu)
– Daniel Möller
Nov 27 '18 at 18:24
|
show 9 more comments
1
So uninstalling tensorflow and keras didn't help?
– Matthieu Brucher
Nov 25 '18 at 8:55
1
But if it fails to load the native runtime, that's all right, that what we want. The native runtime is the CPU one.
– Matthieu Brucher
Nov 25 '18 at 9:07
1
So if you don't have TF, only TF-gpu, you get a failure with keras? Did you try using the TF keras layers instead of keras directly?
– Matthieu Brucher
Nov 25 '18 at 9:12
1
They are intensorflow.keras, so you should be able to dofrom TensorFlow import kerasand use the API more or less like before (tensorflow.org/guide/keras). If you use this API, you can havetensorflow.
– Matthieu Brucher
Nov 25 '18 at 9:20
2
Are you sure that you installed "exactly" the Cuda version required by tensorflow 1.4? Tensoflow is picky and it needs "excactly" the one version that is compatible. I suggest you go to the latest tensorflow and install the exact Cuda version it says in the tutorial. -- You cannot have both tensorflow and tensorflow-gpu. Install only tensorflow GPU (if you're using conda, give a try at installing keras-gpu)
– Daniel Möller
Nov 27 '18 at 18:24
1
1
So uninstalling tensorflow and keras didn't help?
– Matthieu Brucher
Nov 25 '18 at 8:55
So uninstalling tensorflow and keras didn't help?
– Matthieu Brucher
Nov 25 '18 at 8:55
1
1
But if it fails to load the native runtime, that's all right, that what we want. The native runtime is the CPU one.
– Matthieu Brucher
Nov 25 '18 at 9:07
But if it fails to load the native runtime, that's all right, that what we want. The native runtime is the CPU one.
– Matthieu Brucher
Nov 25 '18 at 9:07
1
1
So if you don't have TF, only TF-gpu, you get a failure with keras? Did you try using the TF keras layers instead of keras directly?
– Matthieu Brucher
Nov 25 '18 at 9:12
So if you don't have TF, only TF-gpu, you get a failure with keras? Did you try using the TF keras layers instead of keras directly?
– Matthieu Brucher
Nov 25 '18 at 9:12
1
1
They are in
tensorflow.keras, so you should be able to do from TensorFlow import keras and use the API more or less like before (tensorflow.org/guide/keras). If you use this API, you can have tensorflow.– Matthieu Brucher
Nov 25 '18 at 9:20
They are in
tensorflow.keras, so you should be able to do from TensorFlow import keras and use the API more or less like before (tensorflow.org/guide/keras). If you use this API, you can have tensorflow.– Matthieu Brucher
Nov 25 '18 at 9:20
2
2
Are you sure that you installed "exactly" the Cuda version required by tensorflow 1.4? Tensoflow is picky and it needs "excactly" the one version that is compatible. I suggest you go to the latest tensorflow and install the exact Cuda version it says in the tutorial. -- You cannot have both tensorflow and tensorflow-gpu. Install only tensorflow GPU (if you're using conda, give a try at installing keras-gpu)
– Daniel Möller
Nov 27 '18 at 18:24
Are you sure that you installed "exactly" the Cuda version required by tensorflow 1.4? Tensoflow is picky and it needs "excactly" the one version that is compatible. I suggest you go to the latest tensorflow and install the exact Cuda version it says in the tutorial. -- You cannot have both tensorflow and tensorflow-gpu. Install only tensorflow GPU (if you're using conda, give a try at installing keras-gpu)
– Daniel Möller
Nov 27 '18 at 18:24
|
show 9 more comments
2 Answers
2
active
oldest
votes
It might not be the case but, installing and importing the same librariy can sometimes be confusing.
More clearly, my guess is your pycharm environment is different than the default python environment, youre installing packages in the default environment and importing from the pycharm's environment.
To ensure you have a package installed in pycharm's environment,
you can try the following,
from pycharm's python console
!python -m pip install --upgrade tensorflow, keras
this shall properly install the packages, and you can be sure of that installation isn't at fault
answered Dec 1 '18 at 16:22
dragonLOLzdragonLOLz
564
I assume you mean tensorflow-gpu. but I have tried installing packages from PyCharm project interpreter also. No change.
– Alireza
Dec 1 '18 at 19:11
You've followed the official installation guide? maybe checking out the steps again can help link
– dragonLOLz
Dec 2 '18 at 7:35
add a comment |
The problem was with CUDA's version. I had installed CUDA v10.0 but Tensorflow seems to work only with v9.0. Installed it and it works like a charm.
answered Dec 18 '18 at 17:46
AlirezaAlireza
15611
add a comment |
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2 Answers
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2 Answers
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It might not be the case but, installing and importing the same librariy can sometimes be confusing.
More clearly, my guess is your pycharm environment is different than the default python environment, youre installing packages in the default environment and importing from the pycharm's environment.
To ensure you have a package installed in pycharm's environment,
you can try the following,
from pycharm's python console
!python -m pip install --upgrade tensorflow, keras
this shall properly install the packages, and you can be sure of that installation isn't at fault
answered Dec 1 '18 at 16:22
dragonLOLzdragonLOLz
564
I assume you mean tensorflow-gpu. but I have tried installing packages from PyCharm project interpreter also. No change.
– Alireza
Dec 1 '18 at 19:11
You've followed the official installation guide? maybe checking out the steps again can help link
– dragonLOLz
Dec 2 '18 at 7:35
add a comment |
It might not be the case but, installing and importing the same librariy can sometimes be confusing.
More clearly, my guess is your pycharm environment is different than the default python environment, youre installing packages in the default environment and importing from the pycharm's environment.
To ensure you have a package installed in pycharm's environment,
you can try the following,
from pycharm's python console
!python -m pip install --upgrade tensorflow, keras
this shall properly install the packages, and you can be sure of that installation isn't at fault
answered Dec 1 '18 at 16:22
dragonLOLzdragonLOLz
564
I assume you mean tensorflow-gpu. but I have tried installing packages from PyCharm project interpreter also. No change.
– Alireza
Dec 1 '18 at 19:11
You've followed the official installation guide? maybe checking out the steps again can help link
– dragonLOLz
Dec 2 '18 at 7:35
add a comment |
It might not be the case but, installing and importing the same librariy can sometimes be confusing.
More clearly, my guess is your pycharm environment is different than the default python environment, youre installing packages in the default environment and importing from the pycharm's environment.
To ensure you have a package installed in pycharm's environment,
you can try the following,
from pycharm's python console
!python -m pip install --upgrade tensorflow, keras
this shall properly install the packages, and you can be sure of that installation isn't at fault
answered Dec 1 '18 at 16:22
dragonLOLzdragonLOLz
564
It might not be the case but, installing and importing the same librariy can sometimes be confusing.
More clearly, my guess is your pycharm environment is different than the default python environment, youre installing packages in the default environment and importing from the pycharm's environment.
To ensure you have a package installed in pycharm's environment,
you can try the following,
from pycharm's python console
!python -m pip install --upgrade tensorflow, keras
this shall properly install the packages, and you can be sure of that installation isn't at fault
answered Dec 1 '18 at 16:22
dragonLOLzdragonLOLz
564
answered Dec 1 '18 at 16:22
dragonLOLzdragonLOLz
564
answered Dec 1 '18 at 16:22
dragonLOLzdragonLOLz
564
answered Dec 1 '18 at 16:22
dragonLOLzdragonLOLz
564
564
I assume you mean tensorflow-gpu. but I have tried installing packages from PyCharm project interpreter also. No change.
– Alireza
Dec 1 '18 at 19:11
You've followed the official installation guide? maybe checking out the steps again can help link
– dragonLOLz
Dec 2 '18 at 7:35
add a comment |
I assume you mean tensorflow-gpu. but I have tried installing packages from PyCharm project interpreter also. No change.
– Alireza
Dec 1 '18 at 19:11
You've followed the official installation guide? maybe checking out the steps again can help link
– dragonLOLz
Dec 2 '18 at 7:35
I assume you mean tensorflow-gpu. but I have tried installing packages from PyCharm project interpreter also. No change.
– Alireza
Dec 1 '18 at 19:11
I assume you mean tensorflow-gpu. but I have tried installing packages from PyCharm project interpreter also. No change.
– Alireza
Dec 1 '18 at 19:11
You've followed the official installation guide? maybe checking out the steps again can help link
– dragonLOLz
Dec 2 '18 at 7:35
You've followed the official installation guide? maybe checking out the steps again can help link
– dragonLOLz
Dec 2 '18 at 7:35
add a comment |
The problem was with CUDA's version. I had installed CUDA v10.0 but Tensorflow seems to work only with v9.0. Installed it and it works like a charm.
answered Dec 18 '18 at 17:46
AlirezaAlireza
15611
add a comment |
The problem was with CUDA's version. I had installed CUDA v10.0 but Tensorflow seems to work only with v9.0. Installed it and it works like a charm.
answered Dec 18 '18 at 17:46
AlirezaAlireza
15611
add a comment |
The problem was with CUDA's version. I had installed CUDA v10.0 but Tensorflow seems to work only with v9.0. Installed it and it works like a charm.
answered Dec 18 '18 at 17:46
AlirezaAlireza
15611
The problem was with CUDA's version. I had installed CUDA v10.0 but Tensorflow seems to work only with v9.0. Installed it and it works like a charm.
answered Dec 18 '18 at 17:46
AlirezaAlireza
15611
answered Dec 18 '18 at 17:46
AlirezaAlireza
15611
answered Dec 18 '18 at 17:46
AlirezaAlireza
15611
answered Dec 18 '18 at 17:46
AlirezaAlireza
15611
15611
add a comment |
add a comment |
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1
So uninstalling tensorflow and keras didn't help?
– Matthieu Brucher
Nov 25 '18 at 8:55
1
But if it fails to load the native runtime, that's all right, that what we want. The native runtime is the CPU one.
– Matthieu Brucher
Nov 25 '18 at 9:07
1
So if you don't have TF, only TF-gpu, you get a failure with keras? Did you try using the TF keras layers instead of keras directly?
– Matthieu Brucher
Nov 25 '18 at 9:12
1
They are in
tensorflow.keras, so you should be able to dofrom TensorFlow import kerasand use the API more or less like before (tensorflow.org/guide/keras). If you use this API, you can havetensorflow.– Matthieu Brucher
Nov 25 '18 at 9:20
2
Are you sure that you installed "exactly" the Cuda version required by tensorflow 1.4? Tensoflow is picky and it needs "excactly" the one version that is compatible. I suggest you go to the latest tensorflow and install the exact Cuda version it says in the tutorial. -- You cannot have both tensorflow and tensorflow-gpu. Install only tensorflow GPU (if you're using conda, give a try at installing keras-gpu)
– Daniel Möller
Nov 27 '18 at 18:24