Comments (12)
I was able to detect GPU in the colab GPU vm.
I followed the below list of commands.
Create a fresh environment and try.
!pip install -U keras-nlp
!pip install -U tensorflow
import tensorflow as tf
print(tf.config.list_physical_devices('GPU'))
[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]
If you are still unable to detect GPU
, you can close this issue and create a new issue in the TensorFlow
repo since it is related to TensorFlow
.
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You link is localhost runtime, we can't access it.
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I can see Num GPUs Available: 1
in your colab, what is the issue again?
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Got it, Looks like this is the TensorFlow issue for the specific OS.
You can create a new issue in TensorFlow and link this issue for context.
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I think it would be nice if keras-nlp was usable by older tensorflow versions, as 2.16.1 version has several bugs in it, and keras-nlp seems to be compatible with tf 2.15
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We always try to match the latest TensorFlow version during the time of release, it's the same practice we follow for Keras-Cv as well.
Moreover, TensorFlow 2.16.1
uses Keras 3
as a backend unlike 2.15 version which uses Keras 2
as a backend.
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@arsenstonelab thanks for the issue. This is indeed a bit of a rough edge. The issue is actually with tensorflow-text
most likely. keras-nlp
is unopinionated about tensorflow versions in our package setup, but if you install keras-nlp
it will try to install tensorflow-text
(the latest version if none is installed). Which in turn will try to install the latest tensorflow
version. Which can lead to a big upgrade of tensorflow.
One option is to pin the tf version you want during install for both tensorflow-text and tensorflow. E.g. this works for installing keras-nlp with tf 2.15.
pip install keras-nlp tensorflow-text~=2.15.0 tensorflow~=2.15.0
Does that work for you?
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This issue is stale because it has been open for 14 days with no activity. It will be closed if no further activity occurs. Thank you.
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