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YapDatabaseViewGroupingWithObjectBlock groupingBlock = ^NSString *(NSString *collection, NSString *key, id object) {
if (![object isKindOfClass:[MealLogRemote class]]) {
return nil;
}
return "all"; // we only need one section/group in this case
};
YapDatabaseViewSortingWithObjectBlock sortingBlock = ^NSComparisonResult (NSString *group, NSString *collection1, NSString *key1, MealLogRemote *obj1,
NSString *collection2, NSString *key2, MealLogRemote *obj2){
// we don't need sorting but this using a sorting for a view is mandatory, lets sort it by date
@clementgenzmer
clementgenzmer / FBAnimationPerformanceTracker.h
Last active September 18, 2023 23:02
FBAnimationPerformanceTracker
/*
* This is an example provided by Facebook are for non-commercial testing and
* evaluation purposes only.
*
* Facebook reserves all rights not expressly granted.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
* OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NON INFRINGEMENT. IN NO EVENT SHALL
* FACEBOOK BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN
@mackuba
mackuba / wwdc15.md
Last active August 6, 2022 17:28
New stuff from WWDC 2015

Here's my own list of the interesting stuff announced during this year's WWDC, collected from the keynotes, various Apple docs, blog posts and tweets.

If you're planning to watch the videos, I really recommend this Mac app that helps you download and watch them: https://github.com/insidegui/WWDC.

OS X El Capitan

http://www.apple.com/osx/elcapitan-preview/

  • split view - two apps side by side on full screen
@natecook1000
natecook1000 / nshipster-new-years-2016.md
Last active July 10, 2018 19:24
NSHipster New Year's 2016

Greetings and salutations, NSHipsters!

As the year winds down, it's a tradition here at NSHipster to ask you, dear readers, to offer up your favorite tricks and tips from the past year as gifts to your fellow hipsters. With iOS 9, El Capitan, brand new watch- and tvOS's, and the open-sourcing of some minor Apple-related tech, there's bound to be lots to share.

Submit your favorite piece of Swift or @objc trivia, helpful hints, unexpected discoveries, useful workarounds, useless fascinations, or anything else you found cool this year. Just comment below!

If you need inspiration, try [the list from last year][2015], or [from the year before][2014], or [from the year before that][2013].

@import UIKit;
NS_ASSUME_NONNULL_BEGIN
@protocol MFBPreviewableCollectionView
- (nullable NSIndexPath *)mfb_previewableCollectionIndexPathForItemAtPoint:(CGPoint)point;
- (CGRect)mfb_previewableCollectionItemRectForIndexPath:(NSIndexPath *)indexPath;
@Catfish-Man
Catfish-Man / sethack.m
Created March 11, 2016 06:21
Demonstrating the trick of using stack-allocated mimics and sets for lookup tables instead of heap allocated keys and dictionaries
// Compile with clang -framework Foundation sethack.m
#import <Foundation/Foundation.h>
#import <objc/runtime.h>
/*
CFHashBytes from http://www.opensource.apple.com/source/CF/CF-1153.18/CFUtilities.c
*/
#define ELF_STEP(B) T1 = (H << 4) + B; T2 = T1 & 0xF0000000; if (T2) T1 ^= (T2 >> 24); T1 &= (~T2); H = T1;
@orta
orta / fish_lazy_commits.sh
Created March 21, 2016 09:14
Fish versions of my bash commands from Lazy Automation
# http://artsy.github.io/blog/2016/03/02/Lazily-Automation/
function git_branch_info
git branch ^/dev/null | grep \* | sed 's/* //'
end
function branch
git checkout master;
git pull upstream master;
git checkout -b $argv[1]
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@danijar
danijar / blog_tensorflow_variable_sequence_labelling.py
Last active May 15, 2022 14:28
TensorFlow Variable-Length Sequence Labelling
# Working example for my blog post at:
# http://danijar.com/variable-sequence-lengths-in-tensorflow/
import functools
import sets
import tensorflow as tf
from tensorflow.models.rnn import rnn_cell
from tensorflow.models.rnn import rnn
def lazy_property(function):
@wingedsheep
wingedsheep / evolution.py
Created June 19, 2016 11:35
Simple Neuroevolution Cartpole
# import os
# os.environ["THEANO_FLAGS"] = "mode=FAST_RUN,device=gpu,floatX=float32"
# import theano
# import the neural net stuff
from keras.models import Sequential
from keras import optimizers
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.layers.convolutional import Convolution1D
from keras.layers.normalization import BatchNormalization