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_posts/hpc/2018-07-19-jupyter-tensorflow.md

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password, or you might be entering the wrong password.
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### Step 1: Download the Repository
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## Step 1: Download the Repository
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First, clone the repository, and remember the location. You will generate a parameters flie
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`params.sh` that you can go back to and use again.
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└── start.sh (-- how you start a connection
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```
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### Step 2: Generate your Parameters
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## Step 2: Generate your Parameters
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You will need to generate a file of parameters to source before using the tool. Importantly, if you
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want to use tensorflow with a gpu, you should select the partition to be "gpu" when it asks you.
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TIME="8:00:00"
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```
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### Step 3: SSH Credentials
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## Step 3: SSH Credentials
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Follow the <a href="https://www.sherlock.stanford.edu/docs/getting-started/connecting/" target="_blank">instructions here</a> to set up your Sherlock credentials. You
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can see what you have by looking at your `~/.ssh/config`:
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bash hosts/sherlock_ssh.sh >> ~/.ssh/config
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```
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### Step 4. On Sherlock
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## Step 4. On Sherlock
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<br>
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$ pip3 install protobuf --user
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```
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### Step 5. Usage
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## Step 5. Usage
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We have just set up a password on Sherlock, and are now back on our _local machine_. Here are the general commands to start and stop sessions. In the tutorial below, we will walk through using Jupyter notebook.
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bash end.sh py2-tensorflow`
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```
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### Step 6. Notebook
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## Step 6. Notebook
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Once you have jupyter running, you want to **make sure you select the python kernel corresponding to
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the one for your job!** For our tutorial, we loaded python 2, so we would want to create a Python 2 notebook.
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Well what are you waiting for? Ask for help by <a href="https://github.com/drorlab/forward" target="_blank">opening an issue</a>! or submitting a pull request.
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## Why not Containers
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## Wait, Why not Containers?
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It occurs to me, it's pretty annoying to need to load modules, and still have broken dependencies.
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Would you be interested in a function like this to start an interactive container? And then allow it to

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