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@jsocol
jsocol / mymodel.py
Last active June 3, 2019 14:21
django caching pattern examples
from django.core.cache import cache
from django.db import models
EMPTY = '-' # Not "None"
class MyModel(models.Model):
@classmethod
def _cache_key(cls, key):
return 'mymodel:{}'.format(key)
@joseluisq
joseluisq / terminal-git-branch-name.md
Last active April 13, 2026 22:07
Add Git Branch Name to Terminal Prompt (Linux/Mac)

Add Git Branch Name to Terminal Prompt (Linux/Mac)

image

Open ~/.bash_profile in your favorite editor and add the following content to the bottom.

# Git branch in prompt.

parse_git_branch() {
@toranb
toranb / create_user.sh
Created July 10, 2015 14:44
a simple bash script to create a new (non admin) user on OSX Yosemite
#!/bin/bash
USERNAME="toranb"
FULLNAME="Toran Billups"
PASSWORD="put something fun here ????"
SECONDARY_GROUPS="" #non-admin user
if [[ $UID -ne 0 ]]; then echo "Please run $0 as root." && exit 1; fi
@kylemcdonald
kylemcdonald / build-caffe.md
Last active March 26, 2024 05:52
How to build Caffe for OS X.

Theory of Building Caffe on OS X

Introduction

Our goal is to run python -c "import caffe" without crashing. For anyone who doesn't spend most of their time with build systems, getting to this point can be extremely difficult on OS X. Instead of providing a list of steps to follow, I'll try to explain why each step happens.

This page has OS X specific install instructions.

I assume:

@baraldilorenzo
baraldilorenzo / readme.md
Last active September 13, 2025 12:17
VGG-16 pre-trained model for Keras

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

@anirudhjayaraman
anirudhjayaraman / mergesort.py
Last active August 5, 2020 19:51
Merge Sort Algorithm Implimentation
# Code for the merge subroutine
def merge(a,b):
""" Function to merge two arrays """
c = []
while len(a) != 0 and len(b) != 0:
if a[0] < b[0]:
c.append(a[0])
a.remove(a[0])
else:
@toranb
toranb / ember-v-next.js
Created January 26, 2016 17:12
what my ember 3 apps will look like?
import Ember from 'ember';
import hbs from 'htmlbars-inline-precompile';
import connect from 'ember-redux/components/connect';
var stateToComputed = (state) => {
return {
users: state.users.all
};
};
# -*- coding: utf-8 -*-
"""Example Google style docstrings.
This module demonstrates documentation as specified by the `Google Python
Style Guide`_. Docstrings may extend over multiple lines. Sections are created
with a section header and a colon followed by a block of indented text.
Example:
Examples can be given using either the ``Example`` or ``Examples``
sections. Sections support any reStructuredText formatting, including
@fchollet
fchollet / classifier_from_little_data_script_2.py
Last active February 26, 2025 01:37
Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats
@fchollet
fchollet / classifier_from_little_data_script_3.py
Last active February 26, 2025 01:37
Fine-tuning a Keras model. Updated to the Keras 2.0 API.
'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats