CentOS 7
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TensorFlow : Install Docker Image (CPU)
2020/07/24
 
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]
[2] Install TensorFlow Docker (CPU only).
# pull TensorFlow 2.0 with Python3 image

[cent@dlp ~]$
docker pull tensorflow/tensorflow:2.0.0-py3
[cent@dlp ~]$
docker images

REPOSITORY              TAG                 IMAGE ID            CREATED             SIZE
tensorflow/tensorflow   2.0.0-py3           90f5cb97b18f        9 months ago        1.07GB

# run container

[cent@dlp ~]$
docker run --rm tensorflow/tensorflow:2.0.0-py3 \
python -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"

2020-07-23 22:08:51.520138: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2801845000 Hz
2020-07-23 22:08:51.520702: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x37ec9f0 executing computations on platform Host. Devices:
2020-07-23 22:08:51.523989: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): Host, Default Version
tf.Tensor(1521.4528, 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 ~]$
docker run --rm -v $PWD:/tmp -w /tmp tensorflow/tensorflow:2.0.0-py3 python ./hello_tensorflow.py

2020-07-23 22:10:02.484191: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2801845000 Hz
2020-07-23 22:10:02.486266: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x38f12a0 executing computations on platform Host. Devices:
2020-07-23 22:10:02.486299: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): Host, Default Version
Hello, TensorFlow World!
[3] Install TensorFlow Docker Image with Jupyter Notebook.
# pull TensorFlow 2.0 with Python3/Jupyter image

[cent@dlp ~]$
docker pull tensorflow/tensorflow:2.0.0-py3-jupyter
[cent@dlp ~]$
docker images

REPOSITORY              TAG                 IMAGE ID            CREATED             SIZE
tensorflow/tensorflow   2.0.0-py3-jupyter   c652a4fc8a4f        9 months ago        1.22GB
tensorflow/tensorflow   2.0.0-py3           90f5cb97b18f        9 months ago        1.07GB

# run container as daemon

[cent@dlp ~]$
docker run -dt -p 8888:8888 tensorflow/tensorflow:2.0.0-py3-jupyter

4b65c77143ea83773db64031dc73eddb8b31c71c74e3506b700aaa3a523af9b5

[cent@dlp ~]$
docker ps

CONTAINER ID        IMAGE                                     COMMAND                  CREATED             STATUS              PORTS                    NAMES
4b65c77143ea        tensorflow/tensorflow:2.0.0-py3-jupyter   "bash -c 'source /et…"   38 seconds ago      Up 37 seconds       0.0.0.0:8888->8888/tcp   suspicious_easley

# confirm URL

[cent@dlp ~]$
docker exec 4b65c77143ea bash -c "jupyter notebook list"

Currently running servers:
http://0.0.0.0:8888/?token=7357a472cdce008e59298c69b20731f1f6ed0bc3f8529a8f :: /tf
  Accessto the URL above, then it's possible to use Jupyter Notebook.
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