2.15 does not use GPU. Other versions do
Closed this issue · 9 comments
edwardyehuang commented
Solution to issue cannot be found in the documentation.
- I checked the documentation.
Issue
2.15 does not use GPU. Other versions do
Installed packages
_libgcc_mutex 0.1 conda_forge conda-forge
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absl-py 2.0.0 pyhd8ed1ab_0 conda-forge
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c-ares 1.24.0 hd590300_0 conda-forge
ca-certificates 2023.11.17 hbcca054_0 conda-forge
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cachetools 5.3.2 pyhd8ed1ab_0 conda-forge
certifi 2023.11.17 pyhd8ed1ab_0 conda-forge
cffi 1.16.0 py311hb3a22ac_0 conda-forge
charset-normalizer 3.3.2 pyhd8ed1ab_0 conda-forge
click 8.1.7 unix_pyh707e725_0 conda-forge
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cuda-cudart 12.0.107 h59595ed_1 conda-forge
cuda-nvcc-tools 12.0.76 h59595ed_1 conda-forge
cuda-nvrtc 12.0.76 hd3aeb46_2 conda-forge
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libaec 1.1.2 h59595ed_1 conda-forge
libblas 3.9.0 20_linux64_openblas conda-forge
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libcublas 12.0.1.189 hd3aeb46_3 conda-forge
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python_abi 3.11 4_cp311 conda-forge
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re2 2023.06.02 h2873b5e_0 conda-forge
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tensorflow 2.15.0 cuda120py311h5cbd639_1 conda-forge
tensorflow-base 2.15.0 cuda120py311h43b5e44_1 conda-forge
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tensorflow-gpu 2.15.0 cuda120py311hb76ca00_1 conda-forge
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zstd 1.5.5 hfc55251_0 conda-forgeEnvironment info
active environment : tf215
active env location : /home/edwardyehuang/miniconda3/envs/tf215
shell level : 3
user config file : /home/edwardyehuang/.condarc
populated config files : /home/edwardyehuang/.condarc
conda version : 4.12.0
conda-build version : not installed
python version : 3.9.12.final.0
virtual packages : __cuda=12.2=0
__linux=6.2.0=0
__glibc=2.35=0
__unix=0=0
__archspec=1=x86_64
base environment : /home/edwardyehuang/miniconda3 (writable)
conda av data dir : /home/edwardyehuang/miniconda3/etc/conda
conda av metadata url : None
channel URLs : https://repo.anaconda.com/pkgs/main/linux-64
https://repo.anaconda.com/pkgs/main/noarch
https://repo.anaconda.com/pkgs/r/linux-64
https://repo.anaconda.com/pkgs/r/noarch
package cache : /home/edwardyehuang/miniconda3/pkgs
/home/edwardyehuang/.conda/pkgs
envs directories : /home/edwardyehuang/miniconda3/envs
/home/edwardyehuang/.conda/envs
platform : linux-64
user-agent : conda/4.12.0 requests/2.27.1 CPython/3.9.12 Linux/6.2.0-32-generic ubuntu/22.04.3 glibc/2.35
UID:GID : 1000:1000
netrc file : None
offline mode : Falsehmaarrfk commented
I don’t doubt what you are saying but It would really help if you provided the code to validate that the GPU isn’t being used.
edwardyehuang commented
import tensorflow as tf
a = tf.constant(2) + 2
In 2.15, only the CPU is used, and the above code works fine in <=2.14
All versions are installed via conda install -c conda-forge tensorflow-gpu==xxxx
hmaarrfk commented
If you can make the above an assert statement, we can add it to our tests suite. Can you try to have an assert statement in your test please.
hmaarrfk commented
The test I found that fails with tensorflow 2.15.0 is:
import tensorflow as tf
assert len(tf.config.list_physical_devices(device_type='CPU')), "No CPU devices found"
assert len(tf.config.list_physical_devices(device_type='GPU')), "No GPU devices found"with tensorflow 2.13 + cuda 11.8 on my machine it passes.
hmaarrfk commented
@jakirkham @xhochy any clues (just in case you are looking to burn free time today!)
njzjz commented
>>> import tensorflow as tf
2023-12-29 16:17:51.727737: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: SSE4.1 SSE4.2 AVX AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
>>> tf.test.is_built_with_cuda()
Falsetensorflow 2.15.0 cuda120py311h5cbd639_1 conda-forge
tensorflow-base 2.15.0 cuda120py311h43b5e44_1 conda-forge
tensorflow-estimator 2.15.0 cuda120py311hf663016_1 conda-forge
njzjz commented
The GPU versions have the same size as the CPU versions, which should be incorrect:
hmaarrfk commented
Good observation.
Sorry for not catching this earlier.
We should probably mark the GPU builds here as broken.
edwardyehuang commented
Thank you. I tested it and it worked.