made an app

> make a new app

You create a new application in Xcode called "Play Me". You then write a little
 program that will allow you to play a song on your phone. You spend most of
 the day coding this up.
> add features to my app

You add a few more features to your app, such as a button to play/pause or skip
 through songs. You also add a slider so you can change the volume between 0-100%
> launch my app

You open up Play Me and it works! You have created an app that allows people
 to listen to music from their phones. You are proud of yourself
> put my app on google play

You upload your app to Google Play and it is downloaded by many users. Your app
 has been downloaded over 100,000 times. You feel good about yourself.
> read reviews for my app

You go back into your app and see all the positive comments people leave. They
 really liked your app. You are happy with how well it did.
> read the negative reviews for my app

You go back into your app and see all the bad reviews people left. Some of them
 were pretty harsh. You don't want to deal with those right now. You need to
 focus on getting more downloads.
> monetize my app

You decide to monetize your app. You can either charge money for every download
 or you can get free ad space. The latter seems much better since you don't want
 to get too attached to any one user.
> put small unobtrusive ads on my app

You put small ads on your app. These ads aren't intrusive at all. People who
 download your app never seem to notice them.
> check how much my app is making

Your app is doing great! You've made over $1000 dollars in just a week. You're
 feeling pretty good about yourself.
> add features to my app

You continue to work hard on your app. You add a couple more features to it.
 You decide to make it so when someone listens to your song they can select which
 song they want to hear next. This way you can keep adding songs to your playlist.
> debug my app
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1365, in _do_call
    return fn(*args)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1350, in _run_fn
    target_list, run_metadata)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/client/session.py", line 1443, in _call_tf_sessionrun
    run_metadata)
tensorflow.python.framework.errors_impl.ResourceExhaustedError: 2 root error(s) found.
  (0) Resource exhausted: OOM when allocating tensor with shape[1,48,2,25,539,64] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
	 [[{{node sample_sequence/while/concat}}]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

	 [[sample_sequence/while/Exit_3/_1387]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

  (1) Resource exhausted: OOM when allocating tensor with shape[1,48,2,25,539,64] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
	 [[{{node sample_sequence/while/concat}}]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

0 successful operations.
0 derived errors ignored.
...