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Making dockerhub the primary installation location. #17521

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Mar 8, 2018
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Making dockerhub the primary installation location. #17521

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31 changes: 15 additions & 16 deletions tensorflow/docs_src/install/install_linux.md
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Original file line number Diff line number Diff line change
Expand Up @@ -356,32 +356,31 @@ where:
to 6006.
* <tt><i>TensorFlowCPUImage</i></tt> is required. It identifies the Docker
container. Specify one of the following values:
* <tt>gcr.io/tensorflow/tensorflow</tt>, which is the TensorFlow CPU binary image.
* <tt>gcr.io/tensorflow/tensorflow:latest-devel</tt>, which is the latest
* <tt>tensorflow/tensorflow</tt>, which is the TensorFlow CPU binary image.
* <tt>tensorflow/tensorflow:latest-devel</tt>, which is the latest
TensorFlow CPU Binary image plus source code.
* <tt>gcr.io/tensorflow/tensorflow:<i>version</i></tt>, which is the
* <tt>tensorflow/tensorflow:<i>version</i></tt>, which is the
specified version (for example, 1.1.0rc1) of TensorFlow CPU binary image.
* <tt>gcr.io/tensorflow/tensorflow:<i>version</i>-devel</tt>, which is
* <tt>tensorflow/tensorflow:<i>version</i>-devel</tt>, which is
the specified version (for example, 1.1.0rc1) of the TensorFlow GPU
binary image plus source code.

<tt>gcr.io</tt> is the Google Container Registry. Note that some
TensorFlow images are also available at
TensorFlow images are available at
[dockerhub](https://hub.docker.com/r/tensorflow/tensorflow/).

For example, the following command launches the latest TensorFlow CPU binary image
in a Docker container from which you can run TensorFlow programs in a shell:

<pre>
$ <b>docker run -it gcr.io/tensorflow/tensorflow bash</b>
$ <b>docker run -it tensorflow/tensorflow bash</b>
</pre>

The following command also launches the latest TensorFlow CPU binary image in a
Docker container. However, in this Docker container, you can run TensorFlow
programs in a Jupyter notebook:

<pre>
$ <b>docker run -it -p 8888:8888 gcr.io/tensorflow/tensorflow</b>
$ <b>docker run -it -p 8888:8888 tensorflow/tensorflow</b>
</pre>

Docker will download the TensorFlow binary image the first time you launch it.
Expand All @@ -405,14 +404,14 @@ where:
<tt><i>hostPort</i></tt> and <code><em>containerPort</em></code> to `8888`.
* <i>TensorFlowGPUImage</i> specifies the Docker container. You must
specify one of the following values:
* <tt>gcr.io/tensorflow/tensorflow:latest-gpu</tt>, which is the latest
* <tt>tensorflow/tensorflow:latest-gpu</tt>, which is the latest
TensorFlow GPU binary image.
* <tt>gcr.io/tensorflow/tensorflow:latest-devel-gpu</tt>, which is
* <tt>tensorflow/tensorflow:latest-devel-gpu</tt>, which is
the latest TensorFlow GPU Binary image plus source code.
* <tt>gcr.io/tensorflow/tensorflow:<i>version</i>-gpu</tt>, which is the
* <tt>tensorflow/tensorflow:<i>version</i>-gpu</tt>, which is the
specified version (for example, 0.12.1) of the TensorFlow GPU
binary image.
* <tt>gcr.io/tensorflow/tensorflow:<i>version</i>-devel-gpu</tt>, which is
* <tt>tensorflow/tensorflow:<i>version</i>-devel-gpu</tt>, which is
the specified version (for example, 0.12.1) of the TensorFlow GPU
binary image plus source code.

Expand All @@ -421,21 +420,21 @@ following command launches the latest TensorFlow GPU binary image in a
Docker container from which you can run TensorFlow programs in a shell:

<pre>
$ <b>nvidia-docker run -it gcr.io/tensorflow/tensorflow:latest-gpu bash</b>
$ <b>nvidia-docker run -it tensorflow/tensorflow:latest-gpu bash</b>
</pre>

The following command also launches the latest TensorFlow GPU binary image
in a Docker container. In this Docker container, you can run TensorFlow
programs in a Jupyter notebook:

<pre>
$ <b>nvidia-docker run -it -p 8888:8888 gcr.io/tensorflow/tensorflow:latest-gpu</b>
$ <b>nvidia-docker run -it -p 8888:8888 tensorflow/tensorflow:latest-gpu</b>
</pre>

The following command installs an older TensorFlow version (0.12.1):

<pre>
$ <b>nvidia-docker run -it -p 8888:8888 gcr.io/tensorflow/tensorflow:0.12.1-gpu</b>
$ <b>nvidia-docker run -it -p 8888:8888 tensorflow/tensorflow:0.12.1-gpu</b>
</pre>

Docker will download the TensorFlow binary image the first time you launch it.
Expand Down Expand Up @@ -505,7 +504,7 @@ If you installed through Docker, start a Docker container
from which you can run bash. For example:

<pre>
$ <b>docker run -it gcr.io/tensorflow/tensorflow bash</b>
$ <b>docker run -it tensorflow/tensorflow bash</b>
</pre>


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13 changes: 6 additions & 7 deletions tensorflow/docs_src/install/install_mac.md
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Original file line number Diff line number Diff line change
Expand Up @@ -292,24 +292,23 @@ where:
to 6006.
* <i>TensorFlowImage</i> is required. It identifies the Docker container.
You must specify one of the following values:
* <code>gcr.io/tensorflow/tensorflow</code>: TensorFlow binary image.
* <code>gcr.io/tensorflow/tensorflow:latest-devel</code>: TensorFlow
* <code>tensorflow/tensorflow</code>: TensorFlow binary image.
* <code>tensorflow/tensorflow:latest-devel</code>: TensorFlow
Binary image plus source code.

<code>gcr.io</code> is the Google Container Registry. Note that some
TensorFlow images are also available at
The TensorFlow images are available at
[dockerhub](https://hub.docker.com/r/tensorflow/tensorflow/).

For example, the following command launches a TensorFlow CPU binary image
in a Docker container from which you can run TensorFlow programs in a shell:

<pre>$ <b>docker run -it gcr.io/tensorflow/tensorflow bash</b></pre>
<pre>$ <b>docker run -it tensorflow/tensorflow bash</b></pre>

The following command also launches a TensorFlow CPU binary image in a
Docker container. However, in this Docker container, you can run
TensorFlow programs in a Jupyter notebook:

<pre>$ <b>docker run -it -p 8888:8888 gcr.io/tensorflow/tensorflow</b></pre>
<pre>$ <b>docker run -it -p 8888:8888 tensorflow/tensorflow</b></pre>

Docker will download the TensorFlow binary image the first time you launch it.

Expand Down Expand Up @@ -376,7 +375,7 @@ do the following:
If you installed through Docker, start a Docker container that runs bash.
For example:

<pre>$ <b>docker run -it gcr.io/tensorflow/tensorflow bash</b></pre>
<pre>$ <b>docker run -it tensorflow/tensorflow bash</b></pre>



Expand Down