anchor.diff:  Step 5. Submit your job. You will need to set `QUEUE`, `PROJECT`, `PROCS`, and `WALLTIME`.
   You can configure those in `cfg-sys-1.sh` (see Step 3), set as env variables, or you can provide in your command line (see below).
   ----
  -$ export QUEUE=default
  +$ export QUEUE=debug-cache-quad
   $ export PROJECT=myproject
   $ export PROCS=3
  -$ export WALLTIME=01:00:00
  -
  -$ ./test/upf-1.sh theta upf-1.txt
  +$ export WALLTIME=00:10:00
  +
  +$ ./test/upf-1.sh theta
   
   // or 
   
  -$ QUEUE=default PROJECT=myproject PROCS=3 WALLTIME=01:00:00 ./test/upf-1.sh theta upf-1.txt
  +$ QUEUE=debug-cache-quad PROJECT=myproject PROCS=3 WALLTIME=00:10:00 ./test/upf-1.sh theta
   ----
   
   * `QUEUE` refers to the system queue name. The Theta machine has `default`, `debug-flat-quad`, and `debug-cache-quad`. For more information, please check https://www.alcf.anl.gov/user-guides/job-scheduling-policy-xc40-systems#queues
   * `PROJECT` refers to your allocated project name. Please check https://www.alcf.anl.gov/user-guides/allocations, for more detail.
   * `PROCS` is a number of nodes. We recommend adding extra 1 node in addition to the number of executions in your plan. In this example, we set 3 (1 + 2).
  +* `WALLTIME` refers to computing time you are requesting for individual node. The production queues are limited by policy. Check https://www.alcf.anl.gov/user-guides/job-scheduling-policy-xc40-systems#queues for more deail.
  +
   
   Step 6. Check queue status
   ----
  -$ qstat -h user_name -f
  -----
  +$ qstat -u user_name -f
  +----
  +
  +Step 7. Reviewing result files
  +After the job is completed, the results files are available in experiments directory (Supervisor/workflow/upf/experiments).
  +For example, `/home/hsyoo/candle_tutorial/Supervisor/workflows/upf/experiments/X000` will contains files like below,
  +----
  +-rw-r--r-- 1 hsyoo cobalt  2411 Aug 17 19:13 262775.cobaltlog
  +-rw-r--r-- 1 hsyoo users   1179 Aug 17 18:55 cfg-sys-1.sh <3>
  +-rw-r--r-- 1 hsyoo users      7 Aug 17 18:55 jobid.txt
  +-rw-r--r-- 1 hsyoo users   3310 Aug 17 19:13 output.txt <1>
  +drwxr-xr-x 4 hsyoo users    512 Aug 17 19:07 run <2>
  +-rw------- 1 hsyoo users  10863 Aug 17 18:55 swift-t-workflow.8X4.tic
  +-rw-r--r-- 1 hsyoo users    677 Aug 17 18:55 turbine.log
  +-rwxr--r-- 1 hsyoo users   5103 Aug 17 18:55 turbine-theta.sh
  +-rw-r--r-- 1 hsyoo users     60 Aug 17 18:55 upf-1.txt <3>
  +-rw-r--r-- 1 hsyoo users   4559 Aug 17 18:55 workflow.sh.log
  +
  +hsyoo@thetalogin4:~/candle_tutorial/Supervisor/workflows/upf/experiments/X000> ls -al run/ <2>
  +total 2
  +drwxr-xr-x 4 hsyoo users  512 Aug 17 19:07 .
  +drwxr-xr-x 3 hsyoo users 1024 Aug 17 20:33 ..
  +drwxr-xr-x 3 hsyoo users  512 Aug 17 20:34 test0
  +drwxr-xr-x 3 hsyoo users  512 Aug 17 19:13 test1
  +
  +hsyoo@thetalogin4:~/candle_tutorial/Supervisor/workflows/upf/experiments/X000> cat run/test0/model.log <4>
  +... many lines omitted ...
  +Epoch 10/10
  +60000/60000 [==============================] - 12s - loss: 4.3824 - acc: 0.7253 - val_loss: 2.1082 - val_acc: 0.8671
  +('Test loss:', 2.1082268813190574)
  +('Test accuracy:', 0.86709999999999998)
  +result: 2.10822688904
  +----
  +<1> `output.txt` contains stdout and stderr of this experiment. This is helpful to debug errors.
  +<2> `run` directory contains the output files. You will see two directories that are corresponding the IDs configured in upf-1.txt
  +<3> a copy of configuration files are available so that you can trace what were passed to this experiment.
  +<4> stdout of test0. After 10 epoches, validation loss was 2.1082. 
  +
   
   == Running mlrMBO based Hyperparameters Optimization (HPO) on Theta
   
  -Step 1. Checkout Supervisor repo
  -----
  -$ git clone https://github.com/ECP-CANDLE/Supervisor.git
  +Step 1. Create directory and checkout Supervisor & Candle repos.
  +You can skip this step if you already have done in previous section.
  +----
  +$ mkdir candle_tutorial
  +$ cd candle_tutorial
  +$ git clone -b master https://github.com/ECP-CANDLE/Supervisor.git
  +$ git clone -b library https://github.com/ECP-CANDLE/Candle.git
   ----
   
   Step 2. Move to mlrMBO workflow directory
  
positive.code: you will need to set `BENCHMARK_DIR` to point the directory that your script locates, and
  `MODEL_PYTHON_SCRIPT` to name the script you want to run
  ----
  BENCHMARK_DIR=directory_where_my_script_locates
  MODEL_PYTHON_SCRIPT=my_script
  ----
  
  Step 4. Set execution plan. Check `test/upf-1.txt` for parameter configuration and modify as needed.
  This file contains multiple number of JSON documents. Each JSON document will contain the command line parameters.
  
negative.code:     ##########################################
      # End of mnist_mlp.py ####################
      ##########################################
    return history  // <2>
  
  ----
  <1> run method receives parameter dictionary
  <2> returns keras history object or None*
  
  * The mlrMBO workflow requires to return keras history object so that the workflow can evaluate the model. The upf workflow does not have the evaluation process, so you can return `None`.
  
  
  = How to run CANDLE compliant code in Theta
  As mentioned above, we offer two different workflows in CANDLE:
  