drscotthawley

from einops import rearrange as _rearrange

class RearrangeWrapper():
    "wrapper to endow einops.rearrange with an 'inverse' operation"
    def __init__(self):
        self.shape, self.s = None, None     # just in case someone tries to call inverse first
      
    def __call__(self, x, s:str, **kwargs): # this 'forward' call is lightweight to preserve original usage
        self.shape, self.s = x.shape, s
        return _rearrange(x, s, **kwargs)

drscotthawley

def magic_mult(a, b):
    """
    Tries to multiply two arrays/matrices in a variety of ways
    Returns all possible working combos as a dict, with the shapes of their respective outputs
    Author: Scott H. Hawley, @drscotthawley
    """
    combos = ['a*b', 'a*b.T', 'a.T*b', 'a.T*b.T','b*a', 'b*a.T', 'b.T*a', 'b.T*a.T'] # elementwise multiplications
    combos += [s.replace('*',' @ ') for s in combos] # matrix multiplications (I like the space here)
    working_combos = {}
    for s in combos:

drscotthawley

#! /usr/bin/env python3 

"""
SLURM usage tracker Discord bot by drscotthawley & rom1504

Requires external file token_channel.csv to connect to Discord
Syntax of that file should be:

token,channel
<DISCORD_BOT_TOKEN>,<CHANNEL_ID>

drscotthawley

drscotthawley

#!/usr/bin/env python3

# Do violence to the Logitech C920s webcam settings in realtime
# To annoy your Zoom-mates by constantly changing the image

from pynput.keyboard import Listener
import os, sys
import random
import time

drscotthawley

# In case you didn't think to add k-fold cross-validation until late in your
# ML project,...
# This is built for a situation where datasets are arrays of, say, images. 

def kfold_swap(train_X, train_Y, val_X, val_Y, k):
    """
    Swaps val with a section of train, given a value for k
    "Duct tape" approach used to "retro-fit" k-fold cross-validation while minimally 
        disturbing the rest of the code, while avoiding reloading data from disk and 
        keeping RAM use manageable. (e.g. np.append() is bad b/c it would copy all of train)

drscotthawley

#! /usr/bin/env python
'''
Simulation of a 'magnetic' pendulum. Actually we'll just use
electrostatic charges instead of magnets, but..good enough, right?

Plots an image showing which source the object is closest to after a certain time
(Note: Depending on params like maxiter, the object may still be moving at the
end of the simulation, so the 'ending position' may not be where it comes to rest.)

This code integrates all the (non-interacting) test objects at once, on the GPU.

drscotthawley

#! /usr/bin/env python

# Little script I use to start a new Markdown blog entry.
# Run from the parent directory above the blog directory,
# or supply a full path to run from anywhere.
#
# Usage:  newpost.py <title>
#  It automatically figures out what the current date is to
#  create a new entry, and supplies a default header with a title
#  and a bibliography placement

drscotthawley

diff --git a/src/core/lib/gpr/log_linux.cc b/src/core/lib/gpr/log_linux.cc
index 561276f0c2..1af0935e1f 100644
--- a/src/core/lib/gpr/log_linux.cc
+++ b/src/core/lib/gpr/log_linux.cc
@@ -40,7 +40,7 @@
 #include <time.h>
 #include <unistd.h>
 
-static long gettid(void) { return syscall(__NR_gettid); }
+static long sys_gettid(void) { return syscall(__NR_sys_gettid); }

drscotthawley

#! /usr/bin/env python3
# Test script for Phase 'Unrolling' / Instantaneous frequency
#
# See Jesse Engel's "rainbowgrams" script, https://gist.github.com/jesseengel/e223622e255bd5b8c9130407397a0494
#
# Modifications by Scott H. Hawley, @drscotthawley and Billy Mitchell
# These modified versions seem to be both more accurate (~2000x less reconstruction error)
# and faster (>20%)
#
# note, to really see/hear the difference, change dtypes to np.float16!