Trjtdtk

How do spell lists change if the party levels up without taking a long rest?

Solving overdetermined system by QR decomposition

Can withdrawing asylum be illegal?

How to substitute curly brackets with round brackets in a grid of list

Can each chord in a progression create its own key?

Windows 10: How to Lock (not sleep) laptop on lid close?

One-dimensional Japanese puzzle

What can I do if neighbor is blocking my solar panels intentionally?

different output for groups and groups USERNAME after adding a username to a group

Why are Marketing Cloud timestamps not stored in the same timezone as Sales Cloud?

Free operad over a monoid object

Did the UK government pay "millions and millions of dollars" to try to snag Julian Assange?

Is there a way to generate uniformly distributed points on a sphere from a fixed amount of random real numbers per point?

Can I visit the Trinity College (Cambridge) library and see some of their rare books

Can we generate random numbers using irrational numbers like π and e?

Hello, Goodbye, Adios, Aloha

Didn't get enough time to take a Coding Test - what to do now?

Why can't devices on different VLANs, but on the same subnet, communicate?

Did the new image of black hole confirm the general theory of relativity?

"... to apply for a visa" or "... and applied for a visa"?

How to determine omitted units in a publication

What other Star Trek series did the main TNG cast show up in?

Deal with toxic manager when you can't quit

Nested ellipses in tikzpicture: Chomsky hierarchy

multi GPU error [closed]

0

$begingroup$

Error "To call multi_gpu_model with gpus=2, we expect the following devices to be available: ['/cpu:0', '/gpu:0', '/gpu:1']. However this machine only has: ['/cpu:0']. Try reducing gpus.

code snippet here:

from keras.utils.training_utils import multi_gpu_model
import argparse

ap = argparse.ArgumentParser()
ap.add_argument("-o", "--output", help= "path to output plot")
ap.add_argument("-g", "--gpus", type=int, default=2, help="# of GPUs")
args = vars(ap.parse_args())


#grab the no of GPUs
G = args["gpus"]
G = args["gpus"]

model = SqueezeNet(nb_classes=nb_class, inputs=(width, height, 3))

#Replicate the model on 2 GPUs
parallel_model = multi_gpu_model(model, gpus=G)

I am using Pycharm and it allows me to create a virtual environment. Also install all the packages that will be rquired to run my code successfully. When i installed tensorflow-gpu and tried to run my code, i got the above error.

keras gpu

share|improve this question

edited Apr 3 at 4:48

Hellen

asked Apr 2 at 3:47

HellenHellen

62

$endgroup$

closed as unclear what you're asking by Ethan, Stephen Rauch♦, hbaderts, Kiritee Gak, thanatoz Apr 2 at 8:19

Please clarify your specific problem or add additional details to highlight exactly what you need. As it's currently written, it’s hard to tell exactly what you're asking. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  This means that Keras doesn't see any of your GPUs. We might need more details about how you installed the GPU drivers and if external tools are capable to see both of the GPUs.
  $endgroup$
  – Tasos
  Apr 2 at 6:13
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  @Tasos thank you so much for following up.
  $endgroup$
  – Hellen
  Apr 3 at 4:07
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  I had successfully installed cuDNN and CuDA on Ubuntu 18.0, I'm using pycharm and created a virtual environment for my training. In pycharm I had both tensorflow and tensorflow-gpu packages installed. That was the issue, when I uninstalled tensorflow and confirmed correct versions of the packages, the issue was solved.
  $endgroup$
  – Hellen
  Apr 3 at 4:16
  

  
  
  
  

add a comment | 

0

$begingroup$

Error "To call multi_gpu_model with gpus=2, we expect the following devices to be available: ['/cpu:0', '/gpu:0', '/gpu:1']. However this machine only has: ['/cpu:0']. Try reducing gpus.

code snippet here:

from keras.utils.training_utils import multi_gpu_model
import argparse

ap = argparse.ArgumentParser()
ap.add_argument("-o", "--output", help= "path to output plot")
ap.add_argument("-g", "--gpus", type=int, default=2, help="# of GPUs")
args = vars(ap.parse_args())


#grab the no of GPUs
G = args["gpus"]
G = args["gpus"]

model = SqueezeNet(nb_classes=nb_class, inputs=(width, height, 3))

#Replicate the model on 2 GPUs
parallel_model = multi_gpu_model(model, gpus=G)

I am using Pycharm and it allows me to create a virtual environment. Also install all the packages that will be rquired to run my code successfully. When i installed tensorflow-gpu and tried to run my code, i got the above error.

keras gpu

share|improve this question

edited Apr 3 at 4:48

Hellen

asked Apr 2 at 3:47

HellenHellen

62

$endgroup$

closed as unclear what you're asking by Ethan, Stephen Rauch♦, hbaderts, Kiritee Gak, thanatoz Apr 2 at 8:19

Please clarify your specific problem or add additional details to highlight exactly what you need. As it's currently written, it’s hard to tell exactly what you're asking. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  This means that Keras doesn't see any of your GPUs. We might need more details about how you installed the GPU drivers and if external tools are capable to see both of the GPUs.
  $endgroup$
  – Tasos
  Apr 2 at 6:13
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  @Tasos thank you so much for following up.
  $endgroup$
  – Hellen
  Apr 3 at 4:07
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  I had successfully installed cuDNN and CuDA on Ubuntu 18.0, I'm using pycharm and created a virtual environment for my training. In pycharm I had both tensorflow and tensorflow-gpu packages installed. That was the issue, when I uninstalled tensorflow and confirmed correct versions of the packages, the issue was solved.
  $endgroup$
  – Hellen
  Apr 3 at 4:16
  

  
  
  
  

add a comment | 

$begingroup$

Error "To call multi_gpu_model with gpus=2, we expect the following devices to be available: ['/cpu:0', '/gpu:0', '/gpu:1']. However this machine only has: ['/cpu:0']. Try reducing gpus.

code snippet here:

from keras.utils.training_utils import multi_gpu_model
import argparse

ap = argparse.ArgumentParser()
ap.add_argument("-o", "--output", help= "path to output plot")
ap.add_argument("-g", "--gpus", type=int, default=2, help="# of GPUs")
args = vars(ap.parse_args())


#grab the no of GPUs
G = args["gpus"]
G = args["gpus"]

model = SqueezeNet(nb_classes=nb_class, inputs=(width, height, 3))

#Replicate the model on 2 GPUs
parallel_model = multi_gpu_model(model, gpus=G)

I am using Pycharm and it allows me to create a virtual environment. Also install all the packages that will be rquired to run my code successfully. When i installed tensorflow-gpu and tried to run my code, i got the above error.

keras gpu

share|improve this question

edited Apr 3 at 4:48

Hellen

asked Apr 2 at 3:47

HellenHellen

62

$endgroup$

from keras.utils.training_utils import multi_gpu_model
import argparse

ap = argparse.ArgumentParser()
ap.add_argument("-o", "--output", help= "path to output plot")
ap.add_argument("-g", "--gpus", type=int, default=2, help="# of GPUs")
args = vars(ap.parse_args())


#grab the no of GPUs
G = args["gpus"]
G = args["gpus"]

model = SqueezeNet(nb_classes=nb_class, inputs=(width, height, 3))

#Replicate the model on 2 GPUs
parallel_model = multi_gpu_model(model, gpus=G)

share|improve this question

edited Apr 3 at 4:48

Hellen

asked Apr 2 at 3:47

HellenHellen

62

share|improve this question

edited Apr 3 at 4:48

Hellen

asked Apr 2 at 3:47

HellenHellen

62

asked Apr 2 at 3:47

HellenHellen

62

asked Apr 2 at 3:47

HellenHellen

62