Ge Yang geyang

Test Gitst update revision number

The new 1.10 version of hdf5 library is stable. You can now install from the source to use this new capability.

The installation process has a few caveats, so here is how to do it.

you need to first remove the hdf5 libraries currently installed in ubuntu.
Then you need to reinstall h5py.
when you reinstall h5py via pip, use the --no-binary flag. This is because the h5py wheel comes with its own hdf5 binary.

Getting SSHFS to work on Mac OSX HighSierra

Below is the working recipe for High Sierra 10.13.4

sudo chown -R $(whoami):staff /usr/local/Caskroom
brew cask install osxfuse
sudo reboot
brew install sshfs

Just changing the computer name in Sharing doesn't work. if you do ssh-keygen the older computer name still shows up.

In order to change the name of the computer, you need to do the following:

   sudo scutil --set ComputerName "new-name"
   sudo scutil --set LocalHostName "new-name"
   sudo scutil --set HostName "new-name"

These code come from the Tensorflow documentation the (experimental) new Dataset API.

General types:

	/** Created by ge on 2/19/17. */
	function scanInlineDelims(state, start, delimLength, allowLineBreaks) {
	var pos = start, lastChar, nextChar, count, can_open, can_close,
	isLastWhiteSpace, isNextWhiteSpace,
	left_flanking = true,
	right_flanking = true,
	max = state.posMax,
	isWhiteSpace = state.md.utils.isWhiteSpace;

	lastChar = allowLineBreaks ?

	In 2014 I made a small rails application called Project-Teacup to demonstrate that I knew what I was doing with rails
	(spoiler: I did not) as part of applying for employment. That application attempted to be a twitter for dreams
	(https://github.com/mcnuttandrew/Project-Teacup) which was based on an idea I had, naturally, while dreaming.
	The project was quite successful in that it got me a job, but also in that it inspired a number of people to record
	their dreams.

	Project-Teacup has been down for a number of years, yet the data lives on. Heroku, where the project was hosted,
	has been going through some ~stuff~ so I figured it would be good to extract the data and expose it publically
	for general consumption. The database was seeded with several hundred dreams from a (single) friends dream
	journal which was hacked apart by hand, and then inserted into the database under the guise of variety of random

	Traceback (most recent call last):
	File "/Users/ge/machine_learning/berkeley-playground/learning_to_learn_from_imperfect_demonstrations/super_expert/experiments/run.py", line 148, in _
	fn(**kwargs)
	File "/Users/ge/machine_learning/berkeley-playground/learning_to_learn_from_imperfect_demonstrations/rl/train_ppo.py", line 138, in run_ppo
	fps=30)
	File "/usr/local/lib/python3.6/dist-packages/ml_logger/ml_logger.py", line 531, in log_video
	imageio.mimsave(ntp.name, frame_stack, format=format, fps=fps, **imageio_kwargs)
	File "/usr/local/lib/python3.6/dist-packages/imageio/core/functions.py", line 341, in mimwrite
	writer.append_data(im)
	File "/usr/local/lib/python3.6/dist-packages/imageio/core/format.py", line 492, in append_data