Error installing TensorFlow GPU in Google Colab: subprocess-exited-with-error

Question

At first I choose the runtime to be GPU and selected the available T4 GPU. Then I try to install TensorFlow GPU in Google Colab by running the command !pip install tensorflow-gpu

!pip install tensorflow-gpu

But I encountered this error:

Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab- 
wheels/public/simple/
Collecting tensorflow-gpu
Using cached tensorflow-gpu-2.12.0.tar.gz (2.6 kB)
error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully.
│ exit code: 1
╰─> See above for output.

note: This error originates from a subprocess, and is likely not a problem with pip.
Preparing metadata (setup.py) ... error
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.

I have already tried upgrading pip, clearing the pip cache, and restarting the Colab runtime, but the issue persists. I suspect there might be compatibility or network-related problems. Can someone help me understand the cause of this error and suggest possible solutions to resolve it? Are there any specific steps I should take or alternative installation approaches I can try to successfully install TensorFlow GPU in Google Colab?

Thank you in advance for any assistance or insights you can provide.

"note: This error originates from a subprocess, and is likely not a problem with pip." I believe its a problem with the notebook, not with. Pip. Have you tried in another notebook-platform?? — Kenry Sanchez
– Kenry Sanchez, Commented Jun 12, 2023 at 4:04
No I tried it on the google colab only. Can u suggest some other platform where I can try? — Partha Pratim Sarma
– Partha Pratim Sarma, Commented Jun 12, 2023 at 4:22

TF_Renu Patel · Accepted Answer · 2023-06-24 10:42:02Z

Google Colab has by-default the latest stable tensorflow and python version installed. You need not to install the tensorflow-gpu to have GPU support enabled in Google Colab untill you need a specific tensorflow version required for your code. You can access the tensorflow package with gpu enabled directly by importing the tensorflow and setting the runtime to GPU as below.

You can follow the below steps to install and access the specific tensorflow version(suppose 2.10) with gpu support in Google Colab:

!pip install tensorflow==2.10   #restart the kernel
import tensorflow as tf
tf.__version__         # '2.10.0'

#to check, if GPU enabled
tf.config.list_physical_devices() 
# Output - [PhysicalDevice(name='/physical_device:CPU:0', device_type='CPU')]

#if no GPU device shows up, change the Colab runtime to GPU mode and re-run the same code

tf.config.list_physical_devices() 
#Output - [PhysicalDevice(name='/physical_device:CPU:0', device_type='CPU'),
#          PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]

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