Assignments for Udacity Deep Learning class with TensorFlow
===========================================================

Running the Docker container from the Google Cloud repository
-------------------------------------------------------------

    docker run -p 8888:8888 -it --rm b.gcr.io/tensorflow-udacity/assignments

Accessing the Notebooks
-----------------------

On linux, go to: http://127.0.0.1:8888

On mac, find the virtual machine's IP using:

    docker-machine ip default

Then go to: http://IP:8888 (likely http://192.168.99.100:8888)

Building a local Docker container
---------------------------------

    cd tensorflow/examples/udacity
    docker build -t $USER/assignments .

Running the local container
---------------------------

    docker run -p 8888:8888 -it --rm $USER/assignments

Pushing a Google Cloud release
------------------------------

    V=0.1.0
    docker tag $USER/assignments b.gcr.io/tensorflow-udacity/assignments:$V
    docker tag $USER/assignments b.gcr.io/tensorflow-udacity/assignments:latest
    gcloud docker push b.gcr.io/tensorflow-udacity/assignments

Assignments for Udacity Deep Learning class with TensorFlow
===========================================================

Running the Docker container from the Google Cloud repository
-------------------------------------------------------------

    docker run -p 8888:8888 -it --rm b.gcr.io/tensorflow-udacity/assignments

Accessing the Notebooks
-----------------------

On linux, go to: http://127.0.0.1:8888

On mac, find the virtual machine's IP using:

    docker-machine ip default

Then go to: http://IP:8888 (likely http://192.168.99.100:8888)

FAQ
---

* **I'm getting a MemoryError when loading data in the first notebook.**

If you're using a Mac, Docker works by running a VM locally (which
is controlled by `docker-machine`). It's quite likely that you'll
need to bump up the amount of RAM allocated to the VM beyond the
default (which is 1G).
[This Stack Overflow question](http://stackoverflow.com/questions/32834082/how-to-increase-docker-machine-memory-mac)
has two good suggestions; we recommend using 8G.

In addition, you may need to pass `--memory=8g` as an extra argument to
`docker run`.

Notes for anyone needing to build their own containers (mostly instructors)
===========================================================================

Building a local Docker container
---------------------------------

    cd tensorflow/examples/udacity
    docker build -t $USER/assignments .

Running the local container
---------------------------

    docker run -p 8888:8888 -it --rm $USER/assignments

Pushing a Google Cloud release
------------------------------

    V=0.1.0
    docker tag $USER/assignments b.gcr.io/tensorflow-udacity/assignments:$V
    docker tag $USER/assignments b.gcr.io/tensorflow-udacity/assignments:latest
    gcloud docker push b.gcr.io/tensorflow-udacity/assignments

Use cc_binary rather than cc_library to reduce size of native library in APK from 5.5mb to 3.2mb (compressed). Change: 113369407
Use cc_binary rather than cc_library to reduce size of native library in APK from 5.5mb to 3.2mb (compressed).
Change: 113369407
