lucgiffon

export TIME='TIME Command being timed: "%C"
TIME User time (seconds): %U
TIME System time (seconds): %S
TIME Elapsed (wall clock) time : %e
TIME Percent of CPU this job got: %P
TIME Average shared text size (kbytes): %X
TIME Average unshared data size (kbytes): %D
TIME Average stack size (kbytes): %p
TIME Average total size (kbytes): %K
TIME Maximum resident set size (kbytes): %M

JustinShenk

#!/bin/bash
# Add to instance metadata with `gcloud compute instances add-metadata \
#   instance-name --metadata-from-file startup-script=idle-shutdown.sh` and reboot
# NOTE: requires `bc`, eg, sudo apt-get install bc
# Modified from https://stackoverflow.com/questions/30556920/how-can-i-automatically-kill-idle-gce-instances-based-on-cpu-usage
threshold=0.1

count=0
wait_minutes=60
while true

jayspeidell

# Info on how to get your api key (kaggle.json) here: https://github.com/Kaggle/kaggle-api#api-credentials
!pip install kaggle
api_token = {"username":"USERNAME","key":"API_KEY"}
import json
import zipfile
import os
with open('/content/.kaggle/kaggle.json', 'w') as file:
    json.dump(api_token, file)
!chmod 600 /content/.kaggle/kaggle.json
!kaggle config path -p /content

pydevops

• 0.1. References
• 0.2. Other cheatsheets
• 0.3. Manage multiple gcloud config configurations
  • 0.3.1. Switch gcloud context with gcloud config
• 0.4. Credentials
• 0.5. info
• 0.6. projects
• 0.7. zones & regions
• 0.8. Organization
• 0.9. billing

swyoon

import numpy as np
import tensorflow as tf

__author__ = "Sangwoong Yoon"

def np_to_tfrecords(X, Y, file_path_prefix, verbose=True):
    """
    Converts a Numpy array (or two Numpy arrays) into a tfrecord file.
    For supervised learning, feed training inputs to X and training labels to Y.
    For unsupervised learning, only feed training inputs to X, and feed None to Y.

djsutherland

'''
Implementation of Fastfood (Le, Sarlos, and Smola, ICML 2013).

Primarily by @esc (Valentin Haenel) and felixmaximilian
from https://github.com/scikit-learn/scikit-learn/pull/3665.

Modified by @dougalsutherland.

FHT implementation was "inspired by" https://github.com/nbarbey/fht.
'''

lttlrck

git branch -m old_branch new_branch         # Rename branch locally    
git push origin :old_branch                 # Delete the old branch    
git push --set-upstream origin new_branch   # Push the new branch, set local branch to track the new remote

akesling

import os
import struct
import numpy as np

"""
MNist loading helper for Python 2.7.

For Python 3.x, see https://gist.github.com/akesling/42393ccb868125071fdea77d98a0d2f0

Loosely inspired by http://abel.ee.ucla.edu/cvxopt/_downloads/mnist.py