Installing Tensorflow on Fedora 40 about tensorflow HOT 1 OPEN

I got it fixed with tensorflow nightly in docker containers, forget building from source!!!

this worked!!

Step-by-Step Instructions

Ensure Podman is Installed and Configured:
If Podman isn't installed or configured yet, follow these steps:

sh

sudo dnf install -y podman

Install NVIDIA Container Toolkit:
Install the NVIDIA Container Toolkit to enable GPU support in Podman.

sh

distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.repo | sudo tee /etc/yum.repos.d/nvidia-docker.repo
sudo dnf install -y nvidia-container-toolkit
sudo systemctl restart containerd

Configure Podman for NVIDIA Runtime:
Update Podman’s configuration to use the NVIDIA runtime.

sh

mkdir -p ~/.config/containers
cat < ~/.config/containers/containers.conf
[engine]
runtime = “nvidia”
EOT

Run TensorFlow Nightly GPU Container with Podman:

Use Podman on your host system to run the TensorFlow nightly GPU container. The --runtime=nvidia flag ensures that GPU support is enabled.

sh

podman run --runtime=nvidia -it tensorflow/tensorflow:nightly-gpu bash

If the above command fails or --runtime is not recognized, use the --gpus all flag:

sh

podman run --gpus all -it tensorflow/tensorflow:nightly-gpu bash

Verify TensorFlow GPU Support Inside the Container:

Once inside the container, verify that TensorFlow can access the GPU:

sh

python -c "import tensorflow as tf; print(‘TensorFlow version:’, tf.version); prin

2m
$ podman run --gpus all -it tensorflow/tensorflow:nightly-gpu bash
WARN[0000] Using cgroups-v1 which is deprecated in favor of cgroups-v2 with Podman v5 and will be removed in a future version. Set environment variable PODMAN_IGNORE_CGROUPSV1_WARNING to hide this warning.

___ /________________________________ / /______ __
__ / _ _ _ __ _ / __ _ / / __ / __ _ | /| / /
_ / / / / / /( )/ // / / _ _/ _ / / // / |/ |/ /
// /// //// _/// // // _//|/

WARNING: You are running this container as root, which can cause new files in
mounted volumes to be created as the root user on your host machine.

To avoid this, run the container by specifying your user’s userid:

$ docker run -u $(id -u):$(id -g) args…

/sbin/ldconfig.real: /usr/lib/wsl/drivers/nvmdsi.inf_amd64_23a2cede5f1383ec/libnvidia-ml.so.1 is not a symbolic link

root@b24205da9419:/# python -c “import tensorflow as tf; print(‘TensorFlow version:’, tf.version); print(‘Num GPUs Available:’, len(tf.config.experimental.list_physical_devices(‘GPU’)))”
2024-06-13 21:27:38.985917: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable TF_ENABLE_ONEDNN_OPTS=0.
2024-06-13 21:27:39.009506: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
TensorFlow version: 2.18.0-dev20240612
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
I0000 00:00:1718314059.869098 17 cuda_executor.cc:990] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
I0000 00:00:1718314059.872207 17 cuda_executor.cc:990] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
I0000 00:00:1718314059.872254 17 cuda_executor.cc:990] could not open file to read NUMA node: /sys/bus/pci/devices/0000:01:00.0/numa_node
Your kernel may have been built without NUMA support.
Num GPUs Available: 1

from tensorflow.