Tutorial by Examples: g

package com.mcf7.spring.domain; import org.springframework.validation.Errors; import org.springframework.validation.Validator; public class BeforeCreateBookValidator implements Validator{ public boolean supports(Class<?> clazz) { return Book.class.equals(clazz); } ...

package com.mcf7.spring.domain; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.boot.CommandLineRunner; import org.springframework.stereotype.Component; @Component public class DatabaseLoader implements CommandLineRunner { private final BookRep...

package com.mcf7.spring.config; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; import org.springframework.context.annotation.Primary; import org.springframework.data.rest.core.event.ValidatingRepositoryEventListener; import org...

buildscript { repositories { jcenter() } dependencies { classpath 'io.spring.gradle:dependency-management-plugin:0.5.4.RELEASE' } } apply plugin: 'io.spring.dependency-management' apply plugin: 'idea' apply plugin: 'java' dependencyManagement { imp...

Usually, J and K move up and down file lines. But when you have wrapping on, you may want them to move up and down the displayed lines instead. set wrap " if you haven't already set it nmap j gj nmap k gk

PHP Classes are powerful tool for improving code organization and minimizing naming collisions. At some point or another, the question of how to create an action hook for a class method inevitably arises. The $function_to_add argument is often shown as a string containing the function's name, howev...

Python Code import numpy as np import cv2 #loading haarcascade classifiers for face and eye #You can find these cascade classifiers here #https://github.com/opencv/opencv/tree/master/data/haarcascades #or where you download opencv inside data/haarcascades face_cascade = cv2.CascadeClassi...

With Ruby you can modify the structure of the program in execution time. One way to do it, is by defining methods dynamically using the method method_missing. Let's say that we want to be able to test if a number is greater than other number with the syntax 777.is_greater_than_123?. # open Numeric...

Monkey patching's main issue is that it pollutes the global scope. Your code working is at the mercy of all the modules you use not stepping on each others toes. The Ruby solution to this is refinements, which are basically monkey patches in a limited scope. module Patches refine Fixnum do ...

Image img = new Image(); BitmapImage bitmap = new BitmapImage(new Uri("ms-appx:///Path-to-image-in-solution-directory", UriKind.Absolute)); img.Source = bitmap;

public override async void ViewDidLoad(){ base.ViewDidLoad(); // Perform any additional setup after loading the view, typically from a nib. Title = "Pull to Refresh Sample"; table = new UITableView(new CGRect(0, 20, View.Bounds.Width, View.Bounds.Height - 20)); //table.Aut...

drop table table01; drop table table02; create table table01 ( code int, name varchar(50), old int ); create table table02 ( code int, name varchar(50), old int ); truncate table table01; insert into table01 values (1, 'A', 10); insert in...

The simplest approach to parallel reduction in CUDA is to assign a single block to perform the task: static const int arraySize = 10000; static const int blockSize = 1024; __global__ void sumCommSingleBlock(const int *a, int *out) { int idx = threadIdx.x; int sum = 0; for (int i ...

Doing parallel reduction for a non-commutative operator is a bit more involved, compared to commutative version. In the example we still use a addition over integers for the simplicity sake. It could be replaced, for example, with matrix multiplication which really is non-commutative. Note, when ...

Sometimes the reduction has to be performed on a very small scale, as a part of a bigger CUDA kernel. Suppose for example, that the input data has exactly 32 elements - the number of threads in a warp. In such scenario a single warp can be assigned to perform the reduction. Given that warp execut...

Sometimes the reduction has to be performed on a very small scale, as a part of a bigger CUDA kernel. Suppose for example, that the input data has exactly 32 elements - the number of threads in a warp. In such scenario a single warp can be assigned to perform the reduction. Given that warp execut...

Typically, reduction is performed on global or shared array. However, when the reduction is performed on a very small scale, as a part of a bigger CUDA kernel, it can be performed with a single warp. When that happens, on Keppler or higher architectures (CC>=3.0), it is possible to use warp-shu...

Go to Catalog > Filters and select Insert to create a filter group. Assign a filter group name (e.g. Color) and add filter name values (e.g. Blue, Red, Yellow).

Go to Catalog > Categories and Edit a category. Under the Data tab add the filters you want to be able to apply to that category (e.g. Color > Blue, Color > Red).

Sometimes it is hard to make all the data of your Pivot Table confirm to the reporting format you have to present your crunched data into. Then use GetPivotData! It has an automatic fill in of arguments that you easy can learn from and it lets you through its parameters flexibly choose and pick from...