TensorFlow : Install Docker Image (CPU)
Install TensorFlow which is the Machine Learning Library.
On this example, Install TensorFlow official Docker Image without GPU support and run it on Containers.
[1]. Install Podman, refer to here.
[2]. Install TensorFlow Docker (CPU only).
# pull TensorFlow 2.0 with Python3 image
[cent@dlp ~]$ podman pull tensorflow/tensorflow:2.0.0-py3
[cent@dlp ~]$ podman images
REPOSITORY TAG IMAGE ID CREATED SIZE
docker.io/tensorflow/tensorflow 2.0.0-py3 90f5cb97b18f 9 months ago 1.09 GB
# run container
[cent@dlp ~]$ podman run --rm tensorflow/tensorflow:2.0.0-py3 \
python -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"
2020-07-22 05:21:27.138093: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2801480000 Hz
2020-07-22 05:21:27.138647: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x34ccfe0 executing computations on platform Host. Devices:
2020-07-22 05:21:27.138671: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): Host, Default Version
tf.Tensor(1074.4442, shape=(), dtype=float32)
# create Hello World test script and run it on container
[cent@dlp ~]$ vi hello_tensorflow.py
import tensorflow as tf
hello = tf.constant('Hello, TensorFlow World!')
tf.print(hello)
[cent@dlp ~]$ podman run --rm -v $PWD:/tmp -w /tmp tensorflow/tensorflow:2.0.0-py3 python ./hello_tensorflow.py
2020-07-22 05:23:36.928319: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2801480000 Hz
2020-07-22 05:23:36.928717: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x4add050 executing computations on platform Host. Devices:
2020-07-22 05:23:36.928738: I tensorflow/compiler/xla/service/service.cc:175] StreamExecutor device (0): Host, Default Version
Hello, TensorFlow World!
[3]. If SELinux is enabled, change pilicy.
[root@dlp ~]# vi my-python.te
# create new
module my-python 1.0;
require {
type user_home_t;
type container_t;
type user_home_dir_t;
class file { create ioctl open read unlink write };
class dir { add_name remove_name write };
}
#============= container_t ==============
allow container_t user_home_dir_t:dir { add_name remove_name write };
allow container_t user_home_dir_t:file { create ioctl open read unlink write };
allow container_t user_home_t:file { ioctl open read };
[root@dlp ~]# checkmodule -m -M -o my-python.mod my-python.te
[root@dlp ~]# semodule_package --outfile my-python.pp --module my-python.mod
[root@dlp ~]# semodule -i my-python.pp
[4] Install TensorFlow Docker Image with Jupyter Notebook.
# pull TensorFlow 2.0 with Python3/Jupyter image
[cent@dlp ~]$ podman pull tensorflow/tensorflow:2.0.0-py3-jupyter
[cent@dlp ~]$ podman images
REPOSITORY TAG IMAGE ID CREATED SIZE
docker.io/tensorflow/tensorflow 2.0.0-py3-jupyter c652a4fc8a4f 9 months ago 1.24 GB
docker.io/tensorflow/tensorflow 2.0.0-py3 90f5cb97b18f 9 months ago 1.09 GB
# run container as daemon
[cent@dlp ~]$ podman run -dt -p 8888:8888 tensorflow/tensorflow:2.0.0-py3-jupyter
1d54bcba3f14eef778a45332b825b6dedd9efb7c8926fde76a5c81cbaed09947
[cent@dlp ~]$ podman ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
1d54bcba3f14 docker.io/tensorflow/tensorflow:2.0.0-py3-jupyter bash -c source /e... 6 seconds ago Up 6 seconds ago 0.0.0.0:8888->8888/tcp vigorous_blackburn
# confirm URL
[cent@dlp ~]$ podman exec 1d54bcba3f14 bash -c "jupyter notebook list"
Currently running servers:
http://0.0.0.0:8888/?token=2b1641a43d5bca23758e6cc1d1979cf3fd4003ba52f8ee4b :: /tf
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