docker image updates (#67)

* transfer learning example - dataflow- and gcloud-related updates

* docker image updates

INSTALL.md

@@ -52,7 +52,7 @@ If you like, you can start up a Google Compute Engine (GCE) VM with docker insta
 Once Docker is installed and running, download the workshop image:
 
 ```sh
-$ docker pull gcr.io/google-samples/tf-workshop:v5
+$ docker pull gcr.io/google-samples/tf-workshop:v6
 ```
 
 [Here's the Dockerfile](https://github.com/amygdala/tensorflow-workshop/tree/master/workshop_image) used to build this image.
@@ -67,7 +67,7 @@ Once you've downloaded the container image, you can run it like this:
 
 ```sh
 docker run -v `pwd`/workshop-data:/root/tensorflow-workshop-master/workshop-data -it \
-    -p 6006:6006 -p 8888:8888 -p 5000:5000 gcr.io/google-samples/tf-workshop:v5
+    -p 6006:6006 -p 8888:8888 -p 5000:5000 gcr.io/google-samples/tf-workshop:v6
 ```
 
 Edit the path to the directory you're mounting as appropriate. The first component of the `-v` arg is the local directory, and the second component is where you want to mount it in your running container.

workshop_image/Dockerfile

@@ -26,11 +26,12 @@ RUN pip install --upgrade --force-reinstall https://storage.googleapis.com/cloud
 
 # RUN python -c "import nltk; nltk.download('punkt')"
 
-RUN curl https://dl.google.com/dl/cloudsdk/channels/rapid/downloads/google-cloud-sdk-138.0.0-linux-x86_64.tar.gz | tar xvz
+RUN curl https://dl.google.com/dl/cloudsdk/channels/rapid/downloads/google-cloud-sdk-159.0.0-linux-x86_64.tar.gz | tar xvz
 RUN ./google-cloud-sdk/install.sh -q
 RUN ./google-cloud-sdk/bin/gcloud components install beta
 
 ADD download_git_repo.py download_git_repo.py
+ENV PATH="${PATH}:/root/google-cloud-sdk/bin"
 
 # TensorBoard
 EXPOSE 6006