Synthesis by Chris Piech. Based on a handout by Marty Stepp. Problems by Eric Roberts, Stuart Reges and Chris Piech.
October 14, 2016
In order to learn recursion, you will teach recursion.
In order to teach recursion, you must first learn recursion.
Thanks to Khan Academy (no affiliation) for the image.
In this assignment you will build tools for a learning platform, called Meta Academy, that teaches recursion. Online learning platforms like Coursera, Khan Academy and one day Meta Academy, offer education to anyone for free. If the quality of the education delivered were high enough this could have an enormous social impact. There are many open questions in this domain, and several of the open questions like "how do we generate personalized content?" and "how can we understand students as they learn?" can be approached using computer science techniques. In fact, current state of the art solutions for knowledge tracing, finding optimal student routes and several other problems are recursive algorithms.
This assignment consists of two main types of contributions: (1) demonstrations of how recursion works and (2) tools for computational education. The aim of this assignment is to get you warmed up to recursion: that beautiful but sometimes mind-bending new way of solving problems. In order to build the Meta Academy you will write five different recursive functions. The starter code for this project is available as a ZIP archive:
Turn in only the following file:
recursion.cpp
, the C++ code for all of your recursion functions.This is a pair assignment. You may work in a pair or alone. Find a partner in section or use the course message board. If you work as a pair, comment both members' names atop every code file. Only one of you should submit the program; do not turn in two copies. You will not help either partner by "dividing up the assignment (e.g., "you do 1,2,3 and I'll do 4,5"). Working as partners means that both partners should always work at one computer, together. There should never be a time where a partner is working independently on a pair-programming assignment.
Submit using the Paperless system linked on the class web site.
When you run Meta Academy you will be presented with a menu that has 5 options (plus the choice to exit). You would have been more than able to write the code to; navigate the menu, output instructions and update the display. However, we provide you with code that already does those basic operations. This allows you to focus on writing the recursive functions.
The Meta Academy menu. This should run with your starter code.
When you first download the starter code, run the program and try each menu item to see how the program works. The five menu items are:
Once all of these are written you will have a tool to start teaching others recursion. And there is nothing like teaching to help you learn.
For all the functions you have to write in this assignment you must use recursion. That is for two reasons. First, the point of this assignment is for you to learn recursion. Second, all of the problems are ones for which recursion is the most natural fit.
For this problem, write a recursive function to compute the greatest common divisor that shows its work:
int gcd(int a, int b)
Some operations are much easier to define recursively.
One amazing example of this is Euclid's Algorithm to
calculate the greatest common divisor (GCD). In the algorithm
Euclid famously shows that the gcd(a, b)
is equal to
gcd(b, r)
where r is the remainder when you divide a by b.
In the case where b is equal to 0, gcd(a, 0)
is simply a.
Since gcd is defined recursively, it is much easier to program
using recursion. Let's calculate gcd.
Euclid's recursive definition of GCD.
When the user choses to show the demo of recursion by definition, the meta program will call the function int gcd(int a, int b)
that you will write (see recursion.cpp
). Your job is to calculate the gcd of the values that are passed in and to show your work as you go. Each invocation of the GCD function should create an output that shows how that invocation calculated the GCD.
An example run of the recursive definition demo, that calls your gcd function.
As an aside, though its straightforward to take Euclid's recursive definition and turn it into C++ code, it's slightly more challenging to see why it holds true. Understanding the proof for why it is true is beyond what we are asking of you, but for those so inclined you can check out the proof on the wikipedia page (warning: not simple). It is amazing to imagine that someone came up with this idea around 2,300 years ago.
For this problem, write a recursive function to draw a Serpinskii triangle:
void drawSierpinskiTriangle(GWindow& gw, int x, int y, int size, int order)
Recursion can also create incredible graphic designs of images that have self-similar subparts. One example is the Sierpinski Triangle, named after the Polish mathematician Waclaw Sierpinski.
Your function should draw a black outlined Sierpinski triangle when passed a reference to a graphical window, the x/y coordinates of the top/left of the triangle, the length of each side of the triangle, and the order of the figure to draw (such as 1 for Order-1, etc.). The provided files already contain a main function that constructs the window and passes the relevant information to your function. The rest is up to you.
If the order passed is 0, your function should not draw anything. If the order passed is negative, your function should throw a string exception. Otherwise you may assume that the window passed is large enough to draw the figure at the given position and size.
If you search the web for fractal designs, you will find many intricate wonders beyond the Koch snowflake illustrated in Chapter 8. One of these is the Sierpinski Triangle, named after its inventor, the Polish mathematician Waclaw Sierpinski (1882–1969). The order-1 Sierpinski Triangle is an equilateral triangle, as shown in the diagram below.
To create an order-K Sierpinski Triangle, you draw three Sierpinski Triangles of order K-1, each of which has half the edge length of the original. Those three triangles are placed in the corners of the larger triangle. Take a look at the Order-2 Sierpinski triangle below to get the idea
The upward-pointing triangle in the middle of the Order-2 figure is not drawn explicitly, but is instead formed by the sides of the other three triangles. That area, moreover, is not recursively subdivided and will remain unchanged at every order of the fractal decomposition. Thus, the Order-3 Sierpinski Triangle has the same open area in the middle.
Different order Serpinskii triangles.
We have not really learned much about the GWindow class, but you do not need to know much about it to solve this problem. The only member function you will need from the GWindow is its drawLine function:
gw.drawLine(x1, y1, x2, y2);
Which draws a line from point (x1, y1) to point (x2, y2)
Note: You may find yourself needing to compute the height of a given triangle so you can pass the right x/y coordinates to your function or to the drawing functions. Keep in mind that the height h of an equilateral triangle is not the same as its side length s. The diagram at right shows the relationship between the triangle and its height. You may want to look at information about equilateral triangles on Wikipedia and/or refresh your trigonometry. You may also find the worked examples from the Fractals class to be useful.
Another thing you should avoid is re-drawing the same line multiple times. If your code is structured well, you should never end up drawing a line again (or part of a line again) that was already drawn.
For this problem, write a recursive function to perform a "flood fill" on a graphical window as described below.
int floodFill(GBufferedImage& image, int x, int y, int color)
A third great use of recursion is when you want to explore a series of decisions. Often decision making is recursive. Once you make one decision you find yourself in a situation which is of the same format. Here we will show how recursion can be used to explore a region of pixels. We will recursively try all possible combinations of making the decisions: move up a pixel, move left, move right and move down.
Most computer drawing programs make it possible to fill a region with a solid color. Typically you do this by selecting the "fill" tool and selecting a color, then clicking the mouse somewhere in your drawing. When you click, the paint color spreads outward from the point you clicked to every contiguous part of the image that is the same color as the pixel where you clicked. For example, if you select the Fill tool and choose Red as your color, then click on a purple part of the image, the Fill operation will cause that part of the image, along with any purple part that is touching it, to become red. The screenshots below provide an illustration:
Flood fill demonstration.
Think of the image as being composed of a 2-D grid of tiny square dots called pixels (picture elements). When the user clicks, whatever color that pixel was, it should be replaced by the fill color outward in all four directions: up, down, left, and right. For example, if the initial pixel color is purple, change it to red, then explore one pixel up, down, left, and right from there, looking for more purple pixels and changing them to red. If your exploration leads you to a pixel that is a different color (such as yellow rather than purple in our example), stop exploring in that direction.
Drawing pixels: The Sierpinski Triangle problem asks you to interact with a GWindow object, but that class is not built for accessing individual pixels. So we will use a different object called GBufferedImage to color pixels here. You can use the following member functions of the buffered image object to get and set the color of individual pixels.
| Command | Description |
|---|---|
image.getRGB(x, y);
|
returns the color of the given pixel as an integer. |
image.setRGB(x, y, color);
|
sets the color of the given pixel to the given color as an integer. |
image.getWidth(); image.getHeight();
|
returns the width or height of the image in pixels. |
image.inBounds(x, y);
|
returns true if pixel (x, y) is within the bounds of the image |
Your code should take care not to access any pixel outside of the bounds of the graphical image, (0, 0) through (width-1, height-1). If you try to get/set a pixel color that is out of bounds, your program will crash.
int color: The colors of pixels are returned as int values. The exact values that map to various colors don't
especially matter to your code, though you can see what color maps to what integer value by looking at the
meta.cpp
file. If you want to print a color out on the console for debugging, it is easier to view it in
hexadecimal (base-16) mode. To do that, you'd issue a special 'hex' command to cout to make it print an integer in
hexadecimal rather than decimal (base-10), such as the following:
cout << hex << color << endl;
Optimization: For efficiency, your function is required to implement a particular optimization. If the caller passes the same fill color as the current pixel's existing color, do not color any pixels and immediately return 0. For example, if the user has the Fill color set to Blue and clicks a blue area, your function should immediately return 0. You can test whether your function is implementing this correctly by watching the console's output while clicking
Return value: Your function must return the total number of pixels that changed color. For example, if your code ends up filling a 50x30 rectangular region, your function would return 1500. If no pixels change color, return 0.
On some machines (such as my machine), filling a very large area of pixels can crash your program because of too many nested function calls ("stack overflow"). This is out of your control. You may ignore this issue, so long as your algorithm is correct.
For this problem, write a recursive function to calculate a personalized curriculum for a student as described below.
void personalCurriculum(Map<string, Vector<string> > & prereqMap, string goal)
When students learn, they come with a variety of different goals. If a learner wants to master a particular goal-concept they may not need to learn every other concept in the course. Instead they just need to learn that goal-concept and all the course concepts that it builds upon. The point of the Personalized Curriculum tool is to output, for a particular course and a particular goal, all of the required concepts that the student must learn to be ready to learn their "goal-concept." The concepts should be printed in an order such that if the student were to learn the concepts in that order they never would be working on a concept for which they don't have the necessary pre-requisites. Here are two examples:
Two example runs of Personalized Curriculum
In order to compute a personalized curriculum we are going to be given a prereqMap that associate each concept with the immediate prerequisites needed for that concept. You are probably familiar with the idea of prerequisites on the course level. Our class cs106b lists cs106a as a prerequisite. The course cs107 lists cs106b as its only prerequisite. However, in order to take cs107 you must first take cs106a then cs106b as prerequisites apply recursively. In general the you can calculate all prerequisites of a concept using the following recursion:
allPrereqsOfConcept(prereqMap, concept){ it's direct prerequisites and for (childConcept : direct prerequisites){ allPrereqsOfConcept(prereqMap, childConcept) } }The first example run (the one on the left) invokes personalized curriculum on the "recursion" course, which is a tiny course you can use to test your program (it does not include all concepts in cs106b). Here is the chain of prerequisites for that course:
The recursion prerequisite relationship is the smallest one you can test your algorithm on. An arrow means that in order to learn the concept on the right, you must first learn the concept on the left.
If your goal is to learn "exploration recursion" you must first learn "recursion." Before you learn "recursion" you must learn its prerequisites, "collections" and "functions." The pattern continues until you get to "simpleC++" which has no prerequisites. Thus if your goal was to learn "exploration recursion" then a good personalized curriculum for you would be:
simpleC++ function calls collections recursion exploration recursion
One important note: if you recursively expand the prerequisites of "exploration recursion" some concepts will be generated many times. A common mistake will be to output the concept more than once.
simpleC++ functionCalls simpleC++ collections recursion explorationRecursion
Use a collection to keep track of the concepts you have already printed so that if you have already told the student they should learn, for example, "simpleC++" you don't list "simpleC++" again.
When you run Personalized Curriculum you will be given the prerequisite map that corresponds to the course the user selected. You do not have to load the prerequisite map from file. As an example, if personalized curriculum was run on the recursion
course you would be passed the following prereqMap
:
"fractals" → ["recursion"] "explorationRecursion" → ["recursion"] "definitionRecursion" → ["recursion"] "recursion" → ["collections", "functionCalls"]
There are three different courses that we have created:
| Command | Description |
|---|---|
cs106b
|
A general prerequisite map for the entire cs106b course. |
recursion
|
A tiny prerequisite map only focused on the concept of recursion. |
stanfordcs
|
The prerequisite map for many of the courses in the stanford cs department. (There is a corresponding file stanfordcs-names.txt that shows how the course numbers map to course names). |
For this problem, write a recursive function to generate a random expansion of a grammar as described below. You can use this function to create random question for students to answer -- specifically we are going to make random program traces (like the sort you will have to do on your midterm).
string generate(Map<string, Vector<string> > & grammar, string symbol)
sentence.txt
and then make sure that the same code works with mystery.txt
. Both are grammars. We added a new example to show a grammer expansion for mystery.A formal language is a set of words and/or symbols along with a set of rules, collectively called the syntax of the language, defining how those symbols may be used together. A grammar is a way of describing the syntax and symbols of a formal language. Many language grammars are described in a format called Backus-Naur Form (BNF). Since most languages are recursive, BNF is too.
Some symbols in a grammar are called terminals because they represent fundamental words of the language. A terminal in English might be "boy" or "run" or "Jessica". Other symbols of the grammar are called non-terminals and represent high-level parts of the language syntax, such as a noun phrase or a sentence. Every non-terminal consists of one or more terminals; for example, the verb phrase "throw a ball" consists of three terminal words.
The BNF description of a language consists of a set of derivation rules, where each rule names a symbol and the legal transformations that can be performed between that symbol and other constructs in the language. For example, a BNF grammar for the English language might state that a sentence consists of a noun phrase and a verb phrase, and that a noun phrase can consist of an adjective followed by a noun or just a noun. Rules can be described recursively (in terms of themselves). For example, a noun phrase might consist of an adjective followed by another noun phrase, such as the phrase "big green tree" which consists of the adjective "big" followed by the noun phrase "green tree".
A BNF grammar is specified as an input file containing one or more rules, of the form:
non-terminal: rule|rule|rule|...|rule
In the following example, non-terminal names <s>, <np> and <tv> are short for linguistic elements sentences, noun phrases, and transitive verbs respectively.
<s>:<np> <vp> ----- <np>:<dp> <adjp> <n>|<pn> ----- <dp>:the|a ----- <adjp>:<adj>|<adj> <adjp> ----- <adj>:big|fat|green|wonderful|faulty|subliminal|pretentious ----- <n>:dog|cat|man|university|father|mother|child|television ----- <pn>:John|Jane|Sally|Spot|Fred|Elmo ----- <vp>:<tv> <np>|<iv> ----- <tv>:hit|honored|kissed|helped ----- <iv>:died|collapsed|laughed|wept -----
This grammar's language can represent sentences such as "The fat university laughed" and "Elmo kissed a green pretentious television". This grammar cannot describe the sentence "Stuart kissed the teacher" because the words "Stuart" and "teacher" are not part of the grammar. It also cannot describe "fat John collapsed Spot" because there are no rules that permit an adjective before the proper noun "John", nor an object after intransitive verb "collapsed".
In this milestone you are going to use grammars that describe different question types. Your task will be to generate random questions using those grammars. Your function will be passed in a grammar as a Map<string, Vector<string> > grammar
which will associate each non-terminal with the Vector of each of its production rules (the strings separated by the | symbols). Using the grammar above as an example the key <np>
would map to a vector with two elements:
<np> → ["<dp> <adjp> <n>", "<pn>"]
Your function involves recursively walking the grammar data structure to generate elements by successively expanding them. To generate a random occurrence of a symbol S:
For example, the grammar on the previous page could be used to randomly generate a <s> non-terminal for the sentence, "Fred honored the green wonderful child", as shown in the following diagram.
Exansion example.
If the string passed to your function is a non-terminal in your grammar, use the grammar's rules to recursively expand that symbol fully into a sequence of terminals. For example, using the grammar on the previous pages, a call of grammarGenerate("<np>") might potentially return the string, "the green wonderful child"
Generating a non-terminal involves picking one of its rules at random and then generating each part of that rule, which might involve more non-terminals to recursively generate. For each of these you pick rules at random and generate each part, etc.
When you encounter a terminal, simply include it in your string. This becomes a base case. If the string passed to your function is not a non-terminal in your grammar, you should assume that it is a terminal symbol and return it.
Your job is to write the recursive function generate that takes in a grammar and a symbol and expands that symbol using the grammar.
When you want to loop over a string exansion you will need to process the string one "token" at a time where a token could be a non-terminal or a terminal. CS106B has a handy library TokenScanner
that makes this very easy. Here is an example:
TokenScanner scanner(production); while (scanner.hasMoreTokens()) { string token = scanner.nextToken(); // do something with token }
Start by testing your code on sentence.txt
. Once it is working, try using the grammar mystery.txt
to expand the symbol QUESTION. If your code is working correctly this should produce a random recursion code-trace question.
There are three different question grammars that come with the starter code (and the sentence grammar described above):
| Command | Description |
|---|---|
sentence.txt
|
This is not a recursion question, but we provided this grammar for testing. |
mystery.txt
|
A template for a random mystery trace problem. |
mysteryHard.txt
|
A template for a random mystery trace problem for people who love a challenge. |
collectionsRecursion.txt
|
A template for slightly ambiguous recursion problems using collections. |
Here is an example question that we generated when expanding the QUESTION symbol for the mystery.txt
grammar:
int mystery(int level, int x) { if(level == 0) { return 5; } else { int r = mystery(level - 1, r); return r % x + 1; } } What is the result of mystery(3, 5);
Thats all! You are done. Consider adding extra features.


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Lobster Mac 'n Cheese
- 16 ounces corkscrew pasta
- 2 large garlic cloves, minced
- 1/2 cup finely chopped red onion
- 1 1/2 cups (6 ounces) grated Gruyčre cheese
- 1 tablespoon Dijon mustard
- 1/2 cup minced fresh chives
- 1/8 teaspoon cayenne pepper
- 1/2 teaspoon salt, divided
- 1/2 teaspoon freshly ground black pepper, divided
- Cook pasta until al dente according to package directions. Drain, rinse with cold water, and drain again.
- Place 4 tablespoons melted butter in a saucepot over medium-low heat. Add garlic and onion; cook 5 minutes or until onion is softened. Whisk in flour; cook 1 minute. Pour in milk; bring mixture to a boil over medium-high heat, whisking frequently. Reduce heat to medium-low, and simmer 3 minutes or until sauce is smooth and thickened.
- Remove from heat, and whisk in cheeses and next 3 ingredients. Stir in 1⁄4 teaspoon salt and 1⁄4 teaspoon pepper. Fold in pasta and lobster. Pour into a greased 3-quart baking dish.
- Combine crushed crackers and remaining 2 tablespoons melted butter. Stir in remaining 1⁄4 teaspoon salt and 1⁄4 teaspoon pepper. Sprinkle over casserole. Bake at 375° for 30 minutes or until crust is crisp and sauce bubbles. Let stand 5 minutes before serving.


Write a Query
In poetry, content and form combine to create meaning. Poetic content refers to a poem's language. ... Elements like the poem's type, stanza structure, line lengths, rhyme scheme, and rhythm express its form. Together, content and form make meaning, which is the message the poet gives to the reader.


Remember, new objects can be created with a constructor function, like new F()
.
If F.prototype
is an object, then the new
operator uses it to set [[Prototype]]
for the new object.
JavaScript had prototypal inheritance from the beginning. It was one of the core features of the language.
But in the old times, there was no direct access to it. The only thing that worked reliably was a `"prototype"` property of the constructor function, described in this chapter. So there are many scripts that still use it.
Please note that F.prototype
here means a regular property named "prototype"
on F
. It sounds something similar to the term “prototype”, but here we really mean a regular property with this name.
Here’s the example:
```js run let animal = { eats: true };
function Rabbit(name) { this.name = name; }
! Rabbit.prototype = animal; /!
let rabbit = new Rabbit(“White Rabbit”); // rabbit.__proto__ == animal
alert( rabbit.eats ); // true ```
Setting Rabbit.prototype = animal
literally states the following: “When a new Rabbit
is created, assign its [[Prototype]]
to animal
”.
That’s the resulting picture:
On the picture, "prototype"
is a horizontal arrow, meaning a regular property, and [[Prototype]]
is vertical, meaning the inheritance of rabbit
from animal
.
``smart header="
F.prototypeonly used at
new Ftime"
F.prototypeproperty is only used when
new Fis called, it assigns
[[Prototype]]` of the new object.
If, after the creation, F.prototype
property changes (F.prototype = <another object>
), then new objects created by new F
will have another object as [[Prototype]]
, but already existing objects keep the old one. ```
Every function has the "prototype"
property even if we don’t supply it.
The default "prototype"
is an object with the only property constructor
that points back to the function itself.
Like this:
We can check it:
```js run function Rabbit() {} // by default: // Rabbit.prototype = { constructor: Rabbit }
alert( Rabbit.prototype.constructor == Rabbit ); // true ```
Naturally, if we do nothing, the constructor
property is available to all rabbits through [[Prototype]]
:
```js run function Rabbit() {} // by default: // Rabbit.prototype = { constructor: Rabbit }
let rabbit = new Rabbit(); // inherits from {constructor: Rabbit}
alert(rabbit.constructor == Rabbit); // true (from prototype) ```
We can use constructor
property to create a new object using the same constructor as the existing one.
Like here:
```js run function Rabbit(name) { this.name = name; alert(name); }
let rabbit = new Rabbit(“White Rabbit”);
! let rabbit2 = new rabbit.constructor(“Black Rabbit”); /! ```
That’s handy when we have an object, don’t know which constructor was used for it (e.g. it comes from a 3rd party library), and we need to create another one of the same kind.
But probably the most important thing about "constructor"
is that…
…JavaScript itself does not ensure the right "constructor"
value.
Yes, it exists in the default "prototype"
for functions, but that’s all. What happens with it later – is totally on us.
In particular, if we replace the default prototype as a whole, then there will be no "constructor"
in it.
For instance:
```js run function Rabbit() {} Rabbit.prototype = { jumps: true };
let rabbit = new Rabbit(); ! alert(rabbit.constructor === Rabbit); // false /! ```
So, to keep the right "constructor"
we can choose to add/remove properties to the default "prototype"
instead of overwriting it as a whole:
function Rabbit() {}
// Not overwrite Rabbit.prototype totally
// just add to it
Rabbit.prototype.jumps = true
// the default Rabbit.prototype.constructor is preserved
Or, alternatively, recreate the constructor
property manually:
Rabbit.prototype = {
jumps: true,
*!*
constructor: Rabbit
*/!*
};
// now constructor is also correct, because we added it
In this chapter we briefly described the way of setting a [[Prototype]]
for objects created via a constructor function. Later we’ll see more advanced programming patterns that rely on it.
Everything is quite simple, just a few notes to make things clear:
F.prototype
property (don’t mistake it for [[Prototype]]
) sets [[Prototype]]
of new objects when new F()
is called.F.prototype
should be either an object or null
: other values won’t work."prototype"
property only has such a special effect when set on a constructor function, and invoked with new
.On regular objects the prototype
is nothing special:
By default all functions have F.prototype = { constructor: F }
, so we can get the constructor of an object by accessing its "constructor"
property.


To work in a dynamic professional environment with a growing organization and utilize my creativity and innovative thinking for the success of organization and myself.
Percentage: 71.7%
Percentage: 79.2%
Percentage: 80%
IOT based home automation for worldwide accessing.
IOT based home automation for worldwide accessing. In this project is used for controlling home appliances from anywhere in the world.
Description
In this project we can control home appliances from anywhere in the world. for example if light is ON state no one inside the home and door was closed, then GSM sends message to the registered mobile number like light ON please take action soon..Thank you. We are using android mobile with BLYNK application to control home appliances wirelessly by using WIFI. Finally that registered mobile number user will control the entire home appliances wirelessly by using BLYNK android mobile application to turn OFF the home appliances.


SIP Servlet Timing Three-Way Calling Manager
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---
layout: post
title: ToxoDB 4.3 is released
category: [ToxoDB]
---
The ApiDB team is pleased to announce the release of ToxoDB 4.3
New features include:
- Gene ID queries allow users to query with the identifiers from the predicted gene models.
- Graphic of the alternate gene predictions is now on the gene record page.
- View and download multiple sequence alignments between the sequenced strains with polymorphisms highlighted.
- Clustered and assembled ESTs are now available from the EST queries / pages and aligned to the genome (GBrowse).
- Additional Mass Spec data has been loaded.
- All BLAST queries have been consolidated to a single interface.
- Faster rendering of gene pages and GBrowse.
- Querying with a single identifier goes directly to the gene page rather than the summary results page.
- More convenient access to help ... please click the "Ask us a Question" link on the left of every page, or the "Contact Us" at bottom to report problems or suggest improvements to the database.
Best regards,
Your ApiDB project team


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Across: 1. More troops stop and make people go to back street (14) 9. Mountain God of India? (7) 10. They may cut back rubbish inside (7) 11. Charges for holes? (5) 12. Like graduate disturbing rest to describe purity (9) 13. Statement may be solution twice over (9) 14. Thinking-man's sculptor makes cane acceptable (5) 15. Do well with around 50 fish! (5) 17. Tamsin and Meg have personal charm....(9) 20. ....Alan Corot is upset and down in the mouth....(4 5) 22. ....Copycat Chatles follows motorways (5) 23.  Turning brown on river is normal (7) 25. Onassis orders them to unite, after nervous start, by manipulating figures (14) Down: 1. Scottish hero, possibly associated with Australian pythons? (6 3 5) 2. Goes in pubs holding mixed gin (7) 3. Get in early and cover everything with wood! (9) 4. She swallowed, blushing! (7) 5. Stylish eastern leader meets support worker (7) 6. I laze around with Miss Doolittle (5) 7. Edward the Red moved quickly! (7) 8. Unbelievably, upset Orca, my stallion! (14) 14. Mum has twitch after her bad turn caused by stiff muscles (9) 16. Dish for dog with red back (7) 17. Note hesitation, at least! (7) 18.  One short measure spoken wrong (7) 21. Mr Eastwood has 150-inch table-top (5)


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---
layout: default
title: Git Commands - Git Init Command, git init command help to create a new git repository or to convert the exisiting reposity into git repository.
description: Git init command convert the existing repository into version control repo or create a new version control reposiotry
keywords: git init, git commands, git clone.
---
Git Init (
git init
) Command
git init
command helps us to initialize a repository to version control repository i.e a git repository.
git init
will initialize the present directory into version control system (VCS)
repository and add a configuration directory .git into the present directory and makes it
to start recording versions of the project.
$pwd
Let's check whether the above directory [commands-test] is a git repository or not by the git command git status or by checking whether there is configuration directory .git present in current directory or not.
$git status
$ls -a
So, it is clearly visible that it is not a git repository. let's make it by git init command.
$git init
The commands used for the above discussion


You are the National Focal Point and an ABSCH publishing authority(PA) for the Wizards Kingdom.
You receive an email from the ABSCH requesting you to publish a Checkpoint Communiqué
You sign-in to the ABSCH and carefully review the CPC records and publish the record in the ABSCH


My name is yuanzm,a boy.
This is my email<EMAIL_ADDRESS>This is my blog: yuanzm
Director
David Twohy
Sequel
Vin Diesel announced on his Facebook page that Universal Pictures wishes to develop a fourth Riddick film.
Home media
Riddick was released on DVD and Blu-ray on January 14, 2014.


I,the author, assumes no responsibility or liability for any errors or omissions in the content of this site. The information contained in this site is provided on an "as is" basis with no guarantees of completeness, accuracy, usefulness or timeliness...
What I am trying to say is; I have no idea what I am talking about. It's all just theoretic.
If anything you get out of this is. "Some nerdy dude is going around saying you can buy a $500 device that could make free Cryptocurrency for you.
I would also like to mention. This site is for my documentation with Helium.
As I explore Helium more. I will update this more.
What is Helium
Helium is building a decentralized wireless network to make it easier to connect anything to the internet with a new blockchain, wireless network, and open source software. Helium was founded in 2013 by Shawn Fanning of Napster, Amir Haleem, and Sean Carey. The company is backed by Khosla Ventures, GV (formerly Google Ventures), FirstMark Capital, Marc Benioff, HSB/MunichRe Ventures and others.
Documentation on Helium
Helium miners Links
What is a Helium miner
BobCat Miner 300
BobCat
Bobcat Miner 300 is a high-efficiency miner hotspot for HNT. It is compatible with Helium LongFi, an architecture that combines the leading wireless LoRaWAN protocol, and the Helium Blockchain technology. The Bobcat Miner 300 is also compatible with all LoRaWAN devices. The Bobcat Miner 300 runs on ultra-low power consumption (5W) and its signal range can cover up to 10+ miles, providing connectivity to tens of thousands of LoRaWAN end nodes detected within its range.
RAK Hotspot Miner V2
RAK.v2
Hotspot Details
Efficient miner for a new cryptocurrency, Helium (HNT) Complete set-up in minutes using a smartphone LongFi™ technology maximizes range and battery life Low Power – uses about the same amount as a 5W LED bulb. Easily manage Hotspots and tokens from the mobile app
RAK Hotspot Miners earn HNT when devices connect, and for validating wireless coverage delivered by peers. Using a system called Proof-of-Coverage, RAK Hotspot Miners earn more HNT when they're in range of other RAK Hotspot Miners, but need to be at least 300 meters apart.
Range depends on the environment, for rural areas up to 10 miles or more, but for more dense areas up to a mile. Single RAK Hotspot Miners earn less as they can only issue Challenges over the internet, and can’t participate in Proof-of-Coverage.
Nebra inside and outside
Nebra shop
Earn HNT cryptocurrency by mining and building coverage for The People’s Network using Nebra HNT Hotspot Miner. Anyone can join The People's Network and provide hundreds of square miles of wireless network coverage, while mining HNT on the Helium Blockchain just as Helium Hotspots do.
The People's Network runs on Helium LongFi™, a technology architecture that combines a leading wireless technology, LoRaWAN, and the Helium Blockchain. LongFi™ is optimised for miles of range, and long battery life for IoT devices.
The Nebra HNT Indoor Hotspot Miner earns the cryptocurrency HNT when devices connect., and for validating wireless coverage delivered by peers. Using a system called Proof-of-Coverage, Hotspot Miners earn more HNT when they're in range of other miners, but need to be at least 300 metres apart.
The Hotspot Miner sets up in minutes and has a smartphone app interface. This variation is the indoor model. The Nebra Outdoor HNT Hotspot Miner provides the same functionality in a rugged outdoor ready enclosure.
HotSpotty the App
https://app.hotspotty.net/hotspots https://www.sitebot.com/helium/locations/city?country=US&state=TX
Let's talk crazy talk now.. like the what if....
Austin And Helium
If we take a look at the example picture. We can see at this time Texas is the second leading state in HNT.
In the example we can see Austin is second in the state of Texas.
| Location: Austin, Texas | Rewards in 360 Days | Helium (HNT) | Austin's Total in HNT |
|---|---|---|---|
| September 2021 | 396,567 | $17 | $7,138,206.00 |
| Januany 1 2021 | 396,567 | $1.36 | $539,331.00 |
| August 22 2021 | 396,567 | $26.53 | $10,520,922.51 |


Web Development
Modern, responsive web design for personal and small business websites that is easy to navigate, visually attractive, SEO optimized, and mobile friendly.
UX/UI Design
Wireframing, prototyping, testing, and visual development with a high focus on user usability and attractive user interfaces that better communicates your brand to the rest of the world.
Graphic Design
Let me help bring your project to life with customized logos, web apps, mobile apps, business cards, ads, posters, image editing, and icons.
Website Maintenance
Keep your website content and systems current, safe and secure, and issue-free with on-going support or in an as-needed basis!


|
JASPL
0.1
Just Another Signal Processing Library
|
Base class for every class that needs access to OpenCL Platforms, Contexts or Devices. More...
#include <openclbase.h>
Public Member Functions | |
| OpenCLBase (uint platform_number=0, uint device_number=0) | |
| Initialize OpenCL Objects Note that the Platform and Context are selected automatically: Platform is set to cl::Platform( 0 ) Context is set to cl::Context( device[ device_number ] ) More... | |
Protected Member Functions | |
| void | SetUp (uint platform_number, uint device_number) |
Base class for every class that needs access to OpenCL Platforms, Contexts or Devices.
This class a common OpenCL Platform, Context, CommandQueue and Device for derived classes to share.
Definition at line 31 of file openclbase.h.
| jaspl::ocl::OpenCLBase::OpenCLBase | ( | uint | platform_number = 0 , |
| uint | device_number = 0 |
||
| ) |
Initialize OpenCL Objects Note that the Platform and Context are selected automatically: Platform is set to cl::Platform( 0 ) Context is set to cl::Context( device[ device_number ] )
The underlying assumption is that the host machine has only one OpenCL Platform ( e.g. one of AMD-APP, Nvidia CUDA, Intel )
| device_number | Number of the OpenCL device to use as described by cl::Platform::getDevices(CL_DEVICE_TYPE_ALL) |
Definition at line 78 of file openclbase.cpp.


| File | Statements | Branches | Functions | Lines | |||||
|---|---|---|---|---|---|---|---|---|---|
| src | 89.58% | 43/48 | 68.75% | 11/16 | 90.91% | 10/11 | 89.36% | 42/47 | |
| src/handlers | 92.05% | 162/176 | 82.35% | 98/119 | 97.14% | 34/35 | 92% | 161/175 | |
| src/resolver | 96.94% | 95/98 | 91.18% | 62/68 | 100% | 20/20 | 96.94% | 95/98 | |
| src/utils | 91.63% | 558/609 | 86.21% | 394/457 | 99.07% | 106/107 | 91.86% | 553/602 | |
| tests | 82.35% | 14/17 | 77.78% | 7/9 | 87.5% | 7/8 | 82.35% | 14/17 |


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Notebooks
Story: The Bushmen's presentiments of things that are going to happen
The Bushmen's presentiments of things that are going to happen
Title
The Bushmen's presentiments of things that are going to happen
Collection
Summary
Bushman Presentiments. They feel in their bodies that certain events are going to happen. There is a kind of beating of the flesh, which tells them things.  The beatings tell those who understand them, which way they are not to go, and which arrow they had better not use, and also warn them when many people are coming to the house on a wagon. They inform people where they can find the person of whom they are in search, i.e., which way they must go to seek him successfully (LII.-28. 2531-2565). The |xam believe that dreams deceive people whereas presentiments speak the truth. The narrator taps his blood when he is about to kill springbok and the people feel tapping while they sit waiting for the ostriches to come. The verso pages contain additional details about the /kumm or 'Bushman letters'.
Comments
1) p.2530v: 'Bushman letters' are compared with letters that carry messages to another place, 2) p.2531v: these beatings, or 'Bushman letters', are called !gwe, 3) p.2536v: two |xam names for Brinkkop and a description, 4) p.2541v: ||kabbo says that |kaggen named all places, but not the people, 5) p.2542v: a name of the thorn tree's flower, 6) p.2551v: the ostrich can see with its eye's bones, which function as a bony cylinder through which they see, 7) p.2554v: the springbok's markings influence where the tappings occur, 8) p.2556v: a comparison between letting the game get away and an anecdote about missing the train, 9) p.2563v: a note by Lloyd on her delay of a week in taking down narration due to Bleek's holiday, and her and ||kabbo's poor health, 10) This story is found in Book II-28
Contributors
Date
18 February – 20 March 1873
Categories
Keywords
presentiments (of |xam) , presentiments (of things that are going to happen) , presentiments (a beating of the flesh which tells the |xam things) , presentiments (premonitions) , presentiments (about springbok) , presentiments (telling things are about to happen) , presentiments (and hunting or perceiving meat) , presentiments (about game) , presentiments (and finding people) , presentiments (tapping) , presentiments (beating of flesh) , presentiments (letters) , presentiments ('Bushman letters') , presentiments (|kumm) , presentiments (quivering) , presentiments (are inside people's bodies, flesh) , presentiments (speak truth) , letters (presentiments of things that are going to happen) , letters (called |kumm) , letters ('Bushman letters') , letters (a beating of the flesh, which tells the |xam things) , letters (are in people's bodies) , letters (presentiments) , letters ('speak truly') , letters (at 'old wound's place') , letters (and knowing people are coming) , dreams (and presentiments of things that are going to happen) , dreams (|xam beliefs about) , dreams ('deceive') , dreams (lie) , dreams (and a beating of the flesh which tells the |xam things) , tapping (a beating of the flesh which tells the |xam things) , tapping (and presentiments of things that are going to happen) , tapping (and feeling things come) , tapping (and doings of animals) , tapping (and time of day) , tapping (and bringing things) , tapping (and blood) , tapping (brings game) , tapping (felt in flesh) , tapping (at 'old wound's place') , tapping (brings people) , tapping (of wounds) , tapping (and hunting) , tapping (and springbok) , Bushman letters (presentiments of things that are going to happen) , Bushman letters (called |kumm) , Bushman letters (a beating of the flesh which tells the |xam things) , Bushman letters (are in people's bodies) , Bushman letters ('speak truly') , Bushman letters (at 'old wound's place') , Bushman letters (and knowing people are coming) , springbok (doings of) , springbok (and presentiments) , springbok (its tapping of its blood) , springbok (hunting of, and 'Bushman letters') , springbok (the people feel them coming) , springbok (and a beating of the flesh which tells the |xam things) , hunting (and presentiments of things that are going to happen) , hunting (and a beating of the flesh which tells the |xam things) , hunting (the hunter's body and game's) , hunting (methods) , hunting (and tapping blood) , hunting (and 'Bushman's letters') , hunting (and perceiving game) , hunting (using look-outs) , hunting (of springbok) , hunting (of ostrich) , ostrich (and presentiments of things that are going to happen) , ostrich (and a beating of the flesh which tells the |xam things) , ostrich (the nature and habits of) , ostrich (hunting of) , ostrich (doings of) , ostrich (and tapping) , ostrich (ostrich-louse) , mountain (Brinkkop) , mountain (and hunting look-outs) , mountain (and perceiving game) , mountain (and presentiments of things that are going to happen) , names (|xam for 'Bushman's letters') , names (a mountain called Brinkkop) , wound (and presentiments of things that are going to happen) , wound (and tapping or beating felt at 'old wound's place') , wound (and 'Bushman letters') , portent (see presentiment) , premonition (see presentiment) , beating (of the flesh which tells the |xam things) , beating (and presentiments of things that are going to happen) , flesh (and presentiments of things that are going to happen) , flesh (a beating felt in which tells the |xam things) , blood (tapping and presentiments of things that are going to happen) , blood (and a beating felt in the flesh which tells the |xam things) , food (finding and presentiments of things that are going to happen) , food (a beating felt in which tells the |xam things) , food (hunting and 'Bushman letters')
Story Pages
2531-2565


having Segwit coin BTC go up like this is amazing as I mine it to fund the real #Bitcoin #BSV. But it does show you how uneducated the market is about the value of utility. BSV is still the only undervalued long term digital asset because of its ability to scale massively


How to use MORTICIA¶
In order to use MORTICIA you will require a python installation (version 2.7 onwards). A Python 3.x distribution is still under development. A step-by-step guide will be provided on how to correctly use MORTICIA. From prerequisites, to installation instructions to running a simulation, providing links to nbMORTICIA examples etc
MORTICIA Dependencies¶
MORTICIA
has been developed using the Anaconda distribution from
Continuum Analytics and this is the recommended distribution for MORTICIA
users.
In principle, any Python 2.7 installation that can meet the dependencies should also work.
MORTICIA
makes use of a variety of other Python packages. The most important of these are:
- numpy and scipy : The mainstay of technical computing in Python.
- matplotlib : Plotting.
- xray : A package for handling N-dimensional data arrays and datasets with named axes. Also for reading and writing data from netCDF format files.
- pandas : For handling time-series and data in a tabular/relational view.
- pint : for handling unit checking and conversion. Note that using
pint
for all numerical operations is not recommended and not done inMORTICIA
. Rather, apint
Quantity object can be carried as metadata to anxray.DataArray
object and checked (for example using Pythonassert
) at object construction time or judiciously so that there is no significant performance impact of any unit checking. - astropy and pyephem : for various astronomy-related calculations (sun, moon position).
- easygui is used for simple file/open and save dialogs.
- ipyparallel is used for parallel computation in IPython/Jupyter notebooks as well as other Python launch modes.
- dill will be required if running libRadtran on remote machines using
ipyparallel
- paramiko will be required for authentication when using
ipyparallel
across machine boundaries
Installation and Requirements¶
MORTICIA
has been developed largely in Python 2.7 and has not yet been tested in Python 3.X. A working installation of libRadtran is required to compute radiant environment maps and atmospheric transmittance. In the Monte carlo/statistical mode of operation, a compute cluster is generally required to achieve adequate sampling in a reasonable time. Parallel computation is performed using the ipyparallel package, which works in IPython/Jupyter notebooks as well as other Python launch modes. In principle, withipyparallel
it is possible to run the Python worker engines on any network-accessible compute resource. This means that it is possible to utilise a Linux-based compute cluster with a libRadtran installation in the background, while all foreground work is performed on a Windows machine, for example. However, this setup may require significant setup to implement. All the required information to do this is provided in theipyparallel
documentation. Examples are provided in the MORTICIA notebooks in the nbMORITICIA repository on GitHub.
The most important top-level classes in MORTICIA
are Sensor, Scene and Snap.
A Sensor comprises an imaging camera on a platform. A Scene comprises at least 2 scene elements (a target and a background). A Snap comprises a single integration period of the camera (snapshot), viewing the scene in a specific geometry (including range) under a specific set of atmospheric and illumination conditions. Illumination can be natural (sun, moon, stars) or artificial such as using a laser illuminator.


Superstar (1999) Reviewed by Eugene Novikov http://www.ultimate-movie.com/ Member: Online Film Critics Society
"You might not want to say 'Superstar' anymore because some people might say that you super suck."
Starring Molly Shannon, Will Ferrell, Elaine Hendrix, Mark McKinney. Rated PG-13.
I love Saturday Night Live. The legendary variety show has slipped a bit in consistency of late, but it's still the smartest, funniest 90 minutes on tv. The good thing about the show -- and head honcho Lorne Michaels is still not getting this -- is that the laughs come in four minute skits. That's right, four minutes. Four, not ninety. When a concept that can barely fill four minutes with laughs is stretched to more than twenty times that length, very bad things happen. Those bad things are called "SNL Movies".
There have, actually, been a couple of successful ones. The Blues Brothers was a hit, and Wayne's World developed an inordinately large fan following, though I didn't really like it. But they were followed by abominations such as Wayne's World 2, It's Pat! (a title eventually tagged with "but who cares?") and A Night at the Roxbury, proving that a variety sketch is not the best model for a feature-length movie. And yet the saga continues with Superstar, which earns points for breaking the gender barrier but quickly loses them for being, well, not very funny.
Whether she likes it or not, the film belongs to SNL vet Molly Shannon who plays Mary Katherine Gallagher, an unpopular schoolgirl with dreams of big-time stardom and fantasies about the French-kissing the school hunk (Will Ferrell). Her dream is to become famous so she tries out for her Catholic School's talent show ("Cheerleaders Fight VD"). Being the most unpopular girl in school, she is mocked and jeered at every turn, except, of course, by the school psycho (Harland Williams) who inevitably turns out to be a sweet and tender "big lug".
There are obstacles everywhere, from Mary's grandmother who wants her to be a business woman, to the nasty Evian ("Go drink a bottle of yourself," Mary exclaims), the head cheerleader whose goal in life is to make Mary miserable. Can she hop over all the hurdles in her path and become a Superstar? What do you think?
There is something inherently amusing about watching 40-year-olds play high-schoolers (not to give any bright minds in Hollywood any ideas), and I liked the fact that they let Shannon, a woman, do all-out Carrey- style full body humor. In fact, Shannon is a funny and talented actress, but she is stuck with a script that makes her rerun the same gags over and over until even she looks like she is about to bail. Superstar is intermittently amusing, but those moments are few and far between. It's full of jabs at Catholicism (I'm surprised the ubiquitous and rather blind to reality Catholic League didn't make this film a prime target of its protests; at times, it's downright offensive) that aren't particularly clever, just mean-spirited.
Superstar is redundant, repetitive and not particularly amusing, with an unacceptably low gag-to-laugh ratio. A gleeful spirit surrounds the film's star, but she is lost in a meandering plot and an unsatisfying screenplay. I have a feeling that sooner or later she will get the project she deserves; for now, she'll have to settle at making us laugh on tv, forgetting this misguided production as quickly as possible. Shannon is a veritable superstar already. This was the last thing she needed.
Grade: C
©1999 Eugene Novikov
Sent via Deja.com http://www.deja.com/ Before you buy.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


| com.thoughtworks.xstream.io.xml.AbstractDocumentReader(Object, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.AbstractDocumentWriter(Object, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.AbstractPullReader(XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.AbstractXmlDriver()
|
| com.thoughtworks.xstream.io.xml.AbstractXmlDriver(XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.AbstractXmlReader(XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.AbstractXmlWriter(XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.mapper.AnnotationMapper(Mapper, ConverterRegistry, ConverterLookup, ClassLoader, ReflectionProvider, JVM)
|
| com.thoughtworks.xstream.annotations.AnnotationReflectionConverter(Mapper, ReflectionProvider, AnnotationProvider) |
| com.thoughtworks.xstream.mapper.AttributeMapper(Mapper)
|
| com.thoughtworks.xstream.io.xml.BEAStaxDriver()
|
| com.thoughtworks.xstream.io.xml.BEAStaxDriver(NameCoder)
|
| com.thoughtworks.xstream.io.xml.BEAStaxDriver(QNameMap)
|
| com.thoughtworks.xstream.io.xml.BEAStaxDriver(QNameMap, NameCoder)
|
| com.thoughtworks.xstream.io.xml.BEAStaxDriver(QNameMap, XmlFriendlyNameCoder)
|
| com.thoughtworks.xstream.io.xml.BEAStaxDriver(XmlFriendlyNameCoder)
|
| com.thoughtworks.xstream.converters.reflection.CGLIBEnhancedConverter(Mapper, ReflectionProvider)
|
| com.thoughtworks.xstream.converters.reflection.CGLIBEnhancedConverter(Mapper, ReflectionProvider, ClassLoader)
|
| com.thoughtworks.xstream.io.xml.CompactWriter(Writer, int, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.CompactWriter(Writer, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.core.DefaultConverterLookup(Mapper)
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| com.thoughtworks.xstream.mapper.DefaultMapper(ClassLoader)
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| com.thoughtworks.xstream.io.xml.Dom4JDriver(DocumentFactory, OutputFormat, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.Dom4JReader(Document, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.Dom4JReader(Element, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.Dom4JWriter(Branch, DocumentFactory, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.Dom4JWriter(Branch, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.Dom4JWriter(DocumentFactory, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.Dom4JXmlWriter(XMLWriter, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.DomDriver(String, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.DomReader(Document, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.DomWriter(Element, Document, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.DomWriter(Element, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.converters.extended.DynamicProxyConverter(Mapper)
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| com.thoughtworks.xstream.converters.extended.DynamicProxyConverter(Mapper, ClassLoader)
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| com.thoughtworks.xstream.mapper.EnumMapper(Mapper, ConverterLookup)
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| com.thoughtworks.xstream.converters.reflection.ExternalizableConverter(Mapper)
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| com.thoughtworks.xstream.converters.reflection.ExternalizableConverter(Mapper, ClassLoader)
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| com.thoughtworks.xstream.converters.extended.FontConverter()
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| com.thoughtworks.xstream.XStream.InitializationException(String)
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| com.thoughtworks.xstream.XStream.InitializationException(String, Throwable)
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| com.thoughtworks.xstream.converters.javabean.JavaBeanConverter(Mapper, String)
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| com.thoughtworks.xstream.converters.extended.JavaClassConverter(ClassLoader)
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| com.thoughtworks.xstream.converters.extended.JavaFieldConverter(ClassLoader)
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| com.thoughtworks.xstream.converters.extended.JavaMethodConverter(ClassLoader)
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| com.thoughtworks.xstream.io.xml.JDomDriver(XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.JDomReader(Document, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.JDomReader(Element, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.JDomWriter(Element, JDOMFactory, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.JDomWriter(Element, XmlFriendlyReplacer)
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| com.thoughtworks.xstream.io.xml.JDomWriter(JDOMFactory, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.json.JettisonStaxWriter(QNameMap, XMLStreamWriter, boolean, boolean, XmlFriendlyReplacer, MappedNamespaceConvention)
|
| com.thoughtworks.xstream.io.json.JsonHierarchicalStreamWriter(Writer)
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| com.thoughtworks.xstream.io.json.JsonHierarchicalStreamWriter(Writer, char[])
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| com.thoughtworks.xstream.io.json.JsonHierarchicalStreamWriter(Writer, char[], String)
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| com.thoughtworks.xstream.io.json.JsonHierarchicalStreamWriter(Writer, String)
|
| com.thoughtworks.xstream.io.json.JsonHierarchicalStreamWriter(Writer, String, String)
|
| com.thoughtworks.xstream.io.json.JsonWriter(Writer, char[])
|
| com.thoughtworks.xstream.io.json.JsonWriter(Writer, char[], String)
|
| com.thoughtworks.xstream.io.json.JsonWriter(Writer, char[], String, int)
|
| com.thoughtworks.xstream.io.json.JsonWriter(Writer, String)
|
| com.thoughtworks.xstream.io.json.JsonWriter(Writer, String, String)
|
| com.thoughtworks.xstream.core.JVM()
|
| com.thoughtworks.xstream.io.xml.PrettyPrintWriter(Writer, char[], String)
|
| com.thoughtworks.xstream.io.xml.PrettyPrintWriter(Writer, char[], String, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.PrettyPrintWriter(Writer, int, char[], XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.PrettyPrintWriter(Writer, int, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.PrettyPrintWriter(Writer, String, String)
|
| com.thoughtworks.xstream.io.xml.PrettyPrintWriter(Writer, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.converters.extended.RegexPatternConverter(Converter)
|
| com.thoughtworks.xstream.io.xml.SaxWriter(boolean, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.SaxWriter(XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.converters.reflection.SerializableConverter(Mapper, ReflectionProvider)
|
| com.thoughtworks.xstream.converters.reflection.SerializableConverter(Mapper, ReflectionProvider, ClassLoader)
|
| com.thoughtworks.xstream.io.xml.SjsxpDriver()
|
| com.thoughtworks.xstream.io.xml.SjsxpDriver(QNameMap)
|
| com.thoughtworks.xstream.io.xml.SjsxpDriver(QNameMap, XmlFriendlyNameCoder)
|
| com.thoughtworks.xstream.io.xml.SjsxpDriver(XmlFriendlyNameCoder)
|
| com.thoughtworks.xstream.io.xml.StandardStaxDriver(QNameMap, XmlFriendlyNameCoder)
|
| com.thoughtworks.xstream.io.xml.StandardStaxDriver(XmlFriendlyNameCoder)
|
| com.thoughtworks.xstream.io.xml.StaxDriver(QNameMap, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.StaxDriver(XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.StaxReader(QNameMap, XMLStreamReader, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.StaxWriter(QNameMap, XMLStreamWriter, boolean, boolean, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.converters.reflection.Sun14ReflectionProvider()
|
| com.thoughtworks.xstream.converters.reflection.Sun14ReflectionProvider(FieldDictionary)
|
| com.thoughtworks.xstream.converters.extended.ThrowableConverter(Converter)
|
| com.thoughtworks.xstream.io.xml.WstxDriver(QNameMap, XmlFriendlyNameCoder)
|
| com.thoughtworks.xstream.io.xml.WstxDriver(XmlFriendlyNameCoder)
|
| com.thoughtworks.xstream.mapper.XmlFriendlyMapper(Mapper)
|
| com.thoughtworks.xstream.io.xml.XmlFriendlyReplacer()
|
| com.thoughtworks.xstream.io.xml.XmlFriendlyReplacer(String, String)
|
| com.thoughtworks.xstream.io.xml.XomDriver(Builder)
|
| com.thoughtworks.xstream.io.xml.XomDriver(Builder, NameCoder)
|
| com.thoughtworks.xstream.io.xml.XomDriver(Builder, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.XomReader(Document, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.XomReader(Element, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.XomWriter(Element, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.xppdom.Xpp3Dom(String)
|
| com.thoughtworks.xstream.io.xml.XppDomDriver(XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.XppDomReader(XppDom, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.XppDomWriter(XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.XppDomWriter(XppDom, XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.XppDriver(XmlFriendlyReplacer)
|
| com.thoughtworks.xstream.io.xml.XppReader(Reader)
|
| com.thoughtworks.xstream.XStream(ReflectionProvider, HierarchicalStreamDriver, ClassLoader)
|
| com.thoughtworks.xstream.XStream(ReflectionProvider, HierarchicalStreamDriver, ClassLoader, Mapper)
|
| com.thoughtworks.xstream.XStream(ReflectionProvider, HierarchicalStreamDriver, ClassLoader, Mapper, ConverterLookup, ConverterRegistry)
|
| com.thoughtworks.xstream.XStream(ReflectionProvider, Mapper, HierarchicalStreamDriver)
|
| com.thoughtworks.xstream.io.xml.XStream11XmlFriendlyReplacer()
|


Simple RPC Server
You will need a STOMP broker running. The defaults will work for fresh RabbitMQ on local machine.
Adjust the
configuration
as per your STOMP broker.
This example uses
queue destination of RabbitMQ
. The queue must be created before running the sample. The ruby server creates the queue if it is not there.
The server endpoint will wait for a random period (max 1000ms) before responding.
Request and responses are logged into Console.
See guide at
https://stomp-js.github.io/guide/rx-stomp/ng2-stompjs/2018/10/12/remote-procedure-call.html


Deleting a Table
How to delete a table from the DotNetNuke.RadEditorProvider for the RTE.
Option One:
- Click on the corner of the table to select it.
- Strike the Delete button on your keyboard.
Option Two:
- Click on the corner of the table to select it.
- Click on the corner of the table to select it. and select Delete Table from the drop down list.
Option Three:
- Place your cursor before or after the table.
- Strike either the Backspace or Delete button on your keyboard respectively.


Hmm, seems Firebug 1.2 Beta does support FF3. Makes me nervous, though, given how much I rely on Firebug.
8/2/2008, 7:10:14 PM
Favs: 0
Retweets: 0
link--- layout: tweet ---
Hmm, seems Firebug 1.2 Beta does support FF3. Makes me nervous, though, given how much I rely on Firebug.
8/2/2008, 7:10:14 PM
Favs: 0
Retweets: 0
link


Package algorithms.search
Class NearestNeighbor2DLong
- java.lang.Object
-
- algorithms.search.NearestNeighbor2DLong
-
public class NearestNeighbor2DLong extends java.lang.Object
a nearest neighbor's algorithm using XFastTrie for predecessor and successor queries on spatially indexed numbers. The algorithm performs better on dense data (that is because the base of the prefix tree is filled, leaving smaller number of nodes to create in linear time). The queries depend upon the maximum of x and maximum of y to be entered. At this time, all entries must be non-negative numbers and so must inquiries. A worst case query would be when column 0 is filled with points and no others filled elsewhere, and the last point in the last row and last column is the query point. In this worst case, the query time would scale roughly as maxY * O(log_2(w)) The algorithm starts with a predecessor and successor call on the query point. The minimum distance among those 2 becomes the goal to search to for completeness as rows above and below the query in the same column. The search continues to higher rows making predecessor and successor calls until the goal is reached. The next higher row is one less than the predecessor result. The goal to the complete search is reduced by smaller distance answers. The same is repeated for lower rows.an example would be: 0 1 2 3 4 5 6 7 8 9 10 11 *12 13 14 q='18'. pred='15', succ='null' to goals(3, 23) 13.pred='12' 15 16 17 *18 19 goals change to (13,23) 13.succ='15', not closer than 12. 20 21 22 23 24 23.pred and 23.succ not closer than 12 ans='12'. queries: 3 pred, 3 succ queries. at O(log_2(w)) each complexity was 6 * O(log_2(w)) for max index = 24, have w = 6
first implemented in project https://github.com/nking/curvature-scale-space-corners-and-transformations w/ Copyright (c) 2014 Climb With Your Feet and using The MIT License (MIT) then moved to this shared library project which has the same copyright TODO: consider for the y-axis, adding locality based hashing or similar- Author:
- nichole
-
-
Constructor Summary
Constructors Constructor Description NearestNeighbor2DLong(gnu.trove.set.TLongSet pointIdxs, int imgWidth, int imgHeight)
NearestNeighbor2DLong(java.util.Set<PairInt> points, int imgWidth, int imgHeight)
-
Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description void
doNotUseCache()
static long
estimateSizeOnHeap(int numberOfPoints, int maxBitLength)
java.util.Set<PairInt>
findClosest(int x, int y)
runtime complexity is best case: Note that caching leads to an O(1) term over time.java.util.Set<PairInt>
findClosest(int x, int y, int dMax)
runtime complexity is best case: Note that caching leads to an O(1) term over time.java.util.Set<PairInt>
findClosestNotEqual(int x, int y)
runtime complexity is best case: 2 * O(log_2(maxW)).java.util.Set<PairInt>
findClosestWithinTolerance(int x, int y, double tolerance)
NOTE: NOT READY FOR USE method to return only the nearest point and any that are at the same distance within a tolerance.protected int
getCol(long internalIndex)
protected long
getInternalIndex(int col, int row)
protected int
getRow(long internalIndex)
-
-
-
Constructor Detail
-
NearestNeighbor2DLong
public NearestNeighbor2DLong(java.util.Set<PairInt> points, int imgWidth, int imgHeight)
- Parameters:
points
- non-negative coordinatesimgWidth
- maximum x value of any data point + 1 including those to be queriesimgHeight
- maximum y value of any data point + 1 including those to be queries
-
NearestNeighbor2DLong
public NearestNeighbor2DLong(gnu.trove.set.TLongSet pointIdxs, int imgWidth, int imgHeight)
- Parameters:
pointIdxs
- pixel indexes formed from relationship pixIdx = (row * width) + colimgWidth
- maximum x value of any data point + 1including those to be queriesimgHeight
- maximum y value of any data point + 1including those to be queries
-
-
Method Detail
-
doNotUseCache
public void doNotUseCache()
-
getInternalIndex
protected long getInternalIndex(int col, int row)
- Parameters:
col
-row
-- Returns:
-
getRow
protected int getRow(long internalIndex)
- Parameters:
internalIndex
-- Returns:
-
getCol
protected int getCol(long internalIndex)
- Parameters:
internalIndex
-- Returns:
-
findClosest
public java.util.Set<PairInt> findClosest(int x, int y)
runtime complexity is best case: Note that caching leads to an O(1) term over time. worst case: Note, worst case is: first column filled with points and all else is empty and the number of rows is same or larger than number of columns and the query is for the point in the last column and last row... a predecessor call is necessary for each row in the worst case. Note: maxW = 1 + Math.ceil(Math.log(maxX * maxY)/Math.log(2));
- Parameters:
x
- non-negative x coord to query fory
- non-negative y coord to query for- Returns:
-
findClosestWithinTolerance
public java.util.Set<PairInt> findClosestWithinTolerance(int x, int y, double tolerance)
NOTE: NOT READY FOR USE method to return only the nearest point and any that are at the same distance within a tolerance. This is meant to be a nearest neighbor method with ability to return more than one at same distance within a tolerance of that distance. TODO: calculate the runtime complexity bounds....- Parameters:
x
- non-negative x coord to query fory
- non-negative y coord to query fortolerance
-- Returns:
-
findClosestNotEqual
public java.util.Set<PairInt> findClosestNotEqual(int x, int y)
runtime complexity is best case: 2 * O(log_2(maxW)). Note that caching leads to an O(1) term over time instead of the logarithmic term. worst case: nRows * 2 * O(log_2(maxW)) Note, worst case is: first column filled with points and all else is empty and the number of rows is same or larger than number of columns and the query is for the point in the last column and last row... a predecessor call is necessary for each row in the worst case. Note: maxW = 1 + Math.ceil(Math.log(maxX * maxY)/Math.log(2));
- Parameters:
x
- non-negative x coord to query fory
- non-negative y coord to query for- Returns:
-
findClosest
public java.util.Set<PairInt> findClosest(int x, int y, int dMax)
runtime complexity is best case: Note that caching leads to an O(1) term over time. worst case: Note: maxW = 1 + Math.ceil(Math.log(maxX * maxY)/Math.log(2));
- Parameters:
x
-y
-dMax
-- Returns:
- a set of points within dMax that are the closest points, else returns an empty set
-
estimateSizeOnHeap
public static long estimateSizeOnHeap(int numberOfPoints, int maxBitLength)
- Parameters:
numberOfPoints
-maxBitLength
-- Returns:
-
-


B.Tech II(CO) Semester – 3 |
L |
T |
P |
C |
CO201 : COMPUTER BASED INFORMATION PROCESSING (CS-I) |
3 |
1 |
2 |
5 |
| |
(05 Hours) |
|||
Data Processing Techniques, Traditional Data Processing & Data Base Processing Techniques, View of data, Introduction to DBMS, Advantages and application of DBMS |
||||
| |
(15 Hours) |
|||
Data Models : E-R Model, Relational Model, Hierarchical Model, Network Models. Data base architecture, Data Storage and Querying, Database Languages -Relational Algebra, Relational Calculus, SQL, Key, Joins, Set operations, Aggregate functions, NULL values, Embedded SQL, Dynamic SQL. |
||||
| |
(10 Hours) |
|||
Characteristics of Different Storages, Performance Measures, Optimization, RAID, Storage Access - Buffer Management, Fixed length and Variable length records, Organization of Records in Files, Algorithms and implementation for building, retrieving of data, updating of data and maintaining for File Organizations like Unordered(Heap), Sequential, Direct Access, Indexed Sequential, Inverted, Multi Key file organization |
||||
| |
(12 Hours) |
|||
Comparison of file organization, File Indexing: Properties of indexes, Performance factors, Tree structured indexing, Hash-based indexing (static and dynamic), External Sorting. |
||||
| |
(14 Hours) |
|||
(Total Contact Time: 42 Hours + 14 Hours = 56 Hours) |
||||
PRACTICALS |
||||
1). Implement Sequential File and Sequential/Direct Access of record from the file. |
||||
BOOKS RECOMMENDED |
||||
1). A Silberschatz, H. F. Korth, and S Sudarshan, "Database System Concepts", 5/E,TMH, 2006 |


I've had two experiences with Paxil, one positive, one down right horrifying.
Towards the end of my senior year in high school, I was experiencing very worrisome symptoms: dizziness, visual blackouts, extreme fatigue, and I even fainted once. So eventually, I went to the doctor. After numerous tests, he diagnosed me as having depression, and prescribed Paxil. The first two weeks were awesome, I hardly needed sleep, lost weight, always felt happy and productive, and for the first time in my life, felt outgoing.
It was great. Eventually the extreme effects wore off, but I continued taking it for a while.
Fast forward two years later. I'm kind of down, and withdrawn. I figure I can just start Paxil again, have the nice effects for a while, and then settle down into a normal routine. So I went back to the same doctor and was got my prescription filled. Unfortunately my experience wasn't so pleasant. I didn't sleep for days at a time, and was irritible and paranoid. I quit my new job screaming and cursing at my employers. I walked home flipping numerous people off. I had constantly had crazy amounts of energy, I couldn't sit still, and was extremely emotional.
My boyfriend got worried about me and brought me over to his parents house to be 'supervised,' as he had to work, and his mother, being a teacher, had the summer off. Even that didn't work out. They took me to a local psychiatric hospital. I was all right until my boyfriend left, and the ICU door slammed in my face and I discovered it was locked. Then I freaked out. I started pounded on the glass at the nurses station screaming to be let out. They eventually wrestled me to the ground to give me a shot of Haldol, an anti-psychotic, and then forced me into a locked room. They said I assaulted a nurse, but I know I didn't, and I'm the one with the scar on my elbow because of it anyhow. I spent ten days there, was prescribed Zyprexa, and was released. Unfortunately, I still wasn't right. So back I went.
I only spent a few hours there this time, though. The other patients were seriously creeping me out, and they gave me some kind of medication that made me feel really weird. So I somehow tricked a nurse into signing something that said I could be let out.  She took me back to my home town, which I don't remember at all, because I passed out. I woke up in the emergency room. A few days later, she made me admit myself to the psychiatric hospital there. That was particularly unpleasant. I had made suicidal remarks, so they were able to get a court order to keep me there.
I was misdiagnosed as being schizoaffective, which is kind of like a blend of schizophrenia and bipolar disorder. So I was on numerous anti-psychotics, which didn't work, and lithium, which sent my thyroid levels to hell. (I had a bad doctor!) Its possible that I was on anti-psychotics for so long that they prolonged my psychotic symptoms. I was very paranoid, and constantly had extremely morbid and disturbing thoughts going through my head. All I could ever do was walk, and I refused to eat.
Eventually, I was transferred to the State Hospital, which is in the city I live in. I spent six weeks there, and was still plauged by paranoia and morbid thoughts, although it was a bit better. The day after I was released, I went to see a completely new doctor and was almost immediately diagnosed as having manic depression, or bipolar disorder. Nearly all the treatments I recieved were completely wrong.
In the end, I spent over three months in a psychiatric hospital, brought about by Paxil. I'm currently on one steady medication, compared to the seven I was on at one time. It was a traumatic experience and I hope no one has to go through anything like it. Be careful with anti-depressants! If you feel highly energized, experience rapid thoughts and ideas, or other similar symptoms, stop taking the medication immediately, and contact your doctor. There is a chance you could be bipolar, and there are better treatments out there for you.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Compare Coronavirus (COVID-19) by country
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Select one or more countries to compare statistics.
Compare infections and deaths over time per country, caused by COVID-19.
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This roadmap document outlines the proposed technology stack and development
timeline for the set of technologies being worked on by the Credentials
Community Group.
Introduction
This document outlines the technology stack and development timeline for the
set of technologies being worked on by the Credentials Community Group. It
is intended for those people that want to understand all of the technical
pieces being proposed, how they fit together, and the development timeline
for each technology.
Readers should understand that this roadmap document is a work in progress
and while many of the technologies discussed in this document have been
implemented and are in production, others may be changed or modified heavily
if driven through a standardization track at W3C. This document is a proposed
roadmap, not the final roadmap for version 1.0.
Technology Stack
The Credentials technology stack is designed on generally accepted design
principles outlined for the Architecture of the World Wide Web[[WEBARCH]]. It
also heavily re-uses W3C and IETF technology, such as JSON-LD [[JSON-LD]]
and HTTP [[RFC7230]]. A high-level diagram of the technology stack is shown
below for reference:
A description of the technologies shown in the diagram above is provided for
those that may be unfamiliar with the technologies:
- Javascript Object Notation [[RFC4627]]
-
JavaScript Object Notation (JSON) is a text format for the serialization of
structured data. JSON can represent four primitive types (strings, numbers,
booleans, and null) and two structured types (objects and arrays). It is a
very popular format among Web developers.
- HyperText Transport Protocol [[RFC7230]]
-
The Hypertext Transfer Protocol (HTTP) is a generic interface protocol for
information systems. It is
designed to hide the details of how a service is implemented by
presenting a uniform interface to clients that is independent of the
types of resources provided. Likewise, servers do not need to be
aware of each client's purpose: an HTTP request can be considered in
isolation rather than being associated with a specific type of client
or a predetermined sequence of application steps. The result is a
protocol that can be used effectively in many different contexts and
for which implementations can evolve independently over time.
- JSON for Linking Data [[JSON-LD]]
-
JSON-LD is a lightweight syntax to serialize Linked Data in JSON [[RFC4627]].
Its design allows existing JSON to be interpreted as Linked Data with minimal
changes. JSON-LD is primarily intended to be a way to use Linked Data in
Web-based programming environments, to build interoperable Web services,
and to store Linked Data in JSON-based storage engines.
- Signing HTTP Messages [[HTTP-SIGNATURES]]
-
When communicating over the Internet using the HTTP protocol, it can be
desirable for a server or client to authenticate the sender of a particular
message. It can also be desirable to ensure that the message was not tampered
with during transit. The "Signing HTTP Messages" specification describes a
way for servers and clients to simultaneously add authentication and message
integrity to HTTP messages by using a digital signature.
- RDF Dataset Normalization [[RDF-NORMALIZATION]]
-
RDF (which JSON-LD uses) utilizes a graph-based data model for making claims
about the world and provides the foundation for reasoning upon that graph
of information. At times, it becomes necessary to compare the differences
between graphs, digitally sign graphs, or generate short identifiers for
graphs via hashing algorithms. RDF Dataset Normalization outlines an
algorithm for normalizing RDF graphs such that these operations can be
performed on the normalized graphs.
- Secure Messaging [[SECURE-MESSAGING]]
-
The Secure Messaging specification describes a simple, decentralized security
infrastructure for the Web based on public key cryptography. This system
enables Web applications to establish identities for agents on the Web,
associate security credentials with those identities, and then use those
security credentials to send and receive messages that are both encrypted
and verifiable via digital signatures.
- Open Badges [[OPEN-BADGES]]
-
The Open Badges specification stack is published by the
Badge Alliance and
its purpose is to enable the storage and transmission of earned skills in a
way that is verifiable and easily sharable.
- Identity Credentials [[IDENTITY-CREDENTIALS]]
-
An identity is a description of a particular entity such as a person, software
agent, or organization. A credential is a qualification, achievement, quality,
or information about an identity's background such as a name, government ID,
home address, or university degree. The Identity Credentials specification
describes mechanisms for reading credentials from and writing credentials to an
identity while ensuring that the information is only accessible to
authorized applications.
Timeline
The technologies proposed by the group are layered in such a way to allow the
base technologies to be re-used by other Web-based standards. Thus, there is
a natural order of progression in developing these technologies, from low-level
to high-level:
Active Collaborators
The following organizations are expected to be directly involved in the
creation of the technologies outlined in this roadmap:


{% extends "layout.html" %} {% block content %}
Please enter your username and recover your password.
We will send email to your registered address. The email will contain a link for password recovery
Follow the link and create a new password. Then you can login with your username and new password.


# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Sensitivity analysis implementations for increasing activation sparsity by using FATReLU
"""
from typing import Callable, Dict, List, Tuple, Union
import torch
from torch import Tensor
from torch.nn import Module
from torch.utils.data import DataLoader, Dataset
from torch.utils.hooks import RemovableHandle
from sparseml.pytorch.nn.fatrelu import FATReLU, convert_relus_to_fat
from sparseml.pytorch.optim.analyzer_as import ModuleASAnalyzer
from sparseml.pytorch.utils import (
LossWrapper,
ModuleRunResults,
ModuleTester,
get_layer,
model_to_device,
)
__all__ = ["ASLayerTracker", "LayerBoostResults", "ModuleASOneShootBooster"]
[docs]class ASLayerTracker(object):
"""
An implementation for tracking activation sparsity properties for a module.
:param layer: the module to track activation sparsity for
:param track_input: track the input sparsity for the module
:param track_output: track the output sparsity for the module
:param input_func: the function to call on input to the layer
and receives the input tensor
:param output_func: the function to call on output to the layer
and receives the output tensor
"""
def __init__(
self,
layer: Module,
track_input: bool = False,
track_output: bool = False,
input_func: Union[None, Callable] = None,
output_func: Union[None, Callable] = None,
):
super().__init__()
self._layer = layer
self._track_input = track_input
self._track_output = track_output
self._input_func = input_func
self._output_func = output_func
self._enabled = False
self._tracked_input = {}
self._tracked_output = {}
self._hook_handle = None # type: RemovableHandle
def __del__(self):
self._disable_hooks()
[docs] def enable(self):
"""
Enable the forward hooks to the layer
"""
if not self._enabled:
self._enabled = True
self._enable_hooks()
self.clear()
[docs] def disable(self):
"""
Disable the forward hooks for the layer
"""
if self._enabled:
self._enabled = False
self._disable_hooks()
self.clear()
[docs] def clear(self):
"""
Clear out current results for the model
"""
self._tracked_input.clear()
self._tracked_output.clear()
@property
def tracked_input(self):
"""
:return: the current tracked input results
"""
return self._tracked_input
@property
def tracked_output(self):
"""
:return: the current tracked output results
"""
return self._tracked_output
def _enable_hooks(self):
if self._hook_handle is not None:
return
def _forward_hook(
_mod: Module,
_inp: Union[Tensor, Tuple[Tensor]],
_out: Union[Tensor, Tuple[Tensor]],
):
if self._track_input:
tracked = _inp
if self._input_func is not None:
tracked = self._input_func(_inp)
key = (
"cpu"
if not tracked.is_cuda
else "cuda:{}".format(tracked.get_device())
)
self._tracked_input[key] = tracked
if self._track_output:
tracked = _out
if self._output_func is not None:
tracked = self._output_func(_out)
key = (
"cpu"
if not tracked.is_cuda
else "cuda:{}".format(tracked.get_device())
)
self._tracked_output[key] = tracked
self._hook_handle = self._layer.register_forward_hook(_forward_hook)
def _disable_hooks(self):
if self._hook_handle is not None:
self._hook_handle.remove()
self._hook_handle = None
[docs]class LayerBoostResults(object):
"""
Results for a specific threshold set in a FATReLU layer.
:param name: the name of the layer the results are for
:param threshold: the threshold used in the FATReLU layer
:param boosted_as: the measured activation sparsity after threshold is applied
:param boosted_loss: the measured loss after threshold is applied
:param baseline_as: the measured activation sparsity before threshold is applied
:param baseline_loss: the measured loss before threshold is applied
"""
def __init__(
self,
name: str,
threshold: float,
boosted_as: Tensor,
boosted_loss: ModuleRunResults,
baseline_as: Tensor,
baseline_loss: ModuleRunResults,
):
self._name = name
self._threshold = threshold
self._boosted_as = boosted_as
self._boosted_loss = boosted_loss
self._baseline_as = baseline_as
self._baseline_loss = baseline_loss
@property
def name(self) -> str:
"""
:return: the name of the layer the results are for
"""
return self._name
@property
def threshold(self) -> float:
"""
:return: the threshold used in the FATReLU layer
"""
return self._threshold
@property
def boosted_as(self) -> Tensor:
"""
:return: the measured activation sparsity after threshold is applied
"""
return self._boosted_as
@property
def boosted_loss(self) -> ModuleRunResults:
"""
:return: the measured loss after threshold is applied
"""
return self._boosted_loss
@property
def baseline_as(self) -> Tensor:
"""
:return: the measured activation sparsity before threshold is applied
"""
return self._baseline_as
@property
def baseline_loss(self) -> ModuleRunResults:
"""
:return: the measured loss before threshold is applied
"""
return self._baseline_loss
[docs]class ModuleASOneShootBooster(object):
"""
Implementation class for boosting the activation sparsity in a given module
using FATReLUs.
Programmatically goes through and figures out the best thresholds to limit loss
based on provided parameters.
:param module: the module to boost
:param device: the device to run the analysis on; ex [cpu, cuda, cuda:1]
:param dataset: the dataset used to evaluate the boosting on
:param batch_size: the batch size to run through the module in test mode
:param loss: the loss function to use for calculations
:param data_loader_kwargs: any keyword arguments to supply to a the
DataLoader constructor
"""
def __init__(
self,
module: Module,
device: str,
dataset: Dataset,
batch_size: int,
loss: LossWrapper,
data_loader_kwargs: Dict,
):
self._module = module
self._device = device
self._dataset = dataset
self._batch_size = batch_size
self._loss = loss
self._dataloader_kwargs = data_loader_kwargs if data_loader_kwargs else {}
[docs] def run_layers(
self,
layers: List[str],
max_target_metric_loss: float,
metric_key: str,
metric_increases: bool,
precision: float = 0.001,
) -> Dict[str, LayerBoostResults]:
"""
Run the booster for the specified layers.
:param layers: names of the layers to run boosting on
:param max_target_metric_loss: the max loss in the target metric that
can happen while boosting
:param metric_key: the name of the metric to evaluate while boosting;
ex: [__loss__, top1acc, top5acc]. Must exist in the LossWrapper
:param metric_increases: True if the metric increases for worse loss such as in
a CrossEntropyLoss, False if the metric decreases for worse such as in
accuracy
:param precision: the precision to check the results to. Larger values here will
give less precise results but won't take as long
:return: The results for the boosting
"""
fat_relus = convert_relus_to_fat(
self._module, inplace=True
) # type: Dict[str, FATReLU]
for layer in layers:
if layer not in fat_relus:
raise KeyError(
(
"layer {} was specified in the config but is not a "
"boostable layer in the module (ie not a relu)"
).format(layer)
)
module, device, device_ids = model_to_device(self._module, self._device)
results = {}
min_thresh = 0.0
max_thresh = 1.0
baseline_res, _ = self._measure_layer(None, module, device, "baseline loss run")
for layer in layers:
results[layer] = self._binary_search_fat(
layer,
module,
device,
min_thresh,
max_thresh,
max_target_metric_loss,
metric_key,
metric_increases,
precision,
)
boosted_res, _ = self._measure_layer(None, module, device, "boosted loss run")
results["__module__"] = LayerBoostResults(
"__module__",
-1.0,
torch.tensor(-1.0),
boosted_res,
torch.tensor(-1.0),
baseline_res,
)
return results
def _binary_search_fat(
self,
layer: str,
module: Module,
device: str,
min_thresh: float,
max_thresh: float,
max_target_metric_loss: float,
metric_key: str,
metric_increases: bool,
precision: float = 0.001,
):
print(
"\n\n\nstarting binary search for layer {} between ({}, {})...".format(
layer, min_thresh, max_thresh
)
)
base_res, base_as = self._measure_layer(
layer, module, device, "baseline for layer: {}".format(layer)
)
fat_relu = get_layer(layer, module) # type: FATReLU
init_thresh = fat_relu.get_threshold()
if min_thresh > init_thresh:
min_thresh = init_thresh
while True:
thresh = ModuleASOneShootBooster._get_mid_point(min_thresh, max_thresh)
fat_relu.set_threshold(thresh)
thresh_res, thresh_as = self._measure_layer(
layer,
module,
device,
"threshold for layer: {} @ {:.4f} ({:.4f}, {:.4f})".format(
layer, thresh, min_thresh, max_thresh
),
)
if ModuleASOneShootBooster._passes_loss(
base_res,
thresh_res,
max_target_metric_loss,
metric_key,
metric_increases,
):
min_thresh = thresh
print(
"loss check passed for max change: {:.4f}".format(
max_target_metric_loss
)
)
print(
" current loss: {:.4f} baseline loss: {:.4f}".format(
thresh_res.result_mean(metric_key),
base_res.result_mean(metric_key),
)
)
print(
" current AS: {:.4f} baseline AS: {:.4f}".format(
thresh_as, base_as
)
)
else:
max_thresh = thresh
print(
"loss check failed for max change: {:.4f}".format(
max_target_metric_loss
)
)
print(
" current loss: {:.4f} baseline loss: {:.4f}".format(
thresh_res.result_mean(metric_key),
base_res.result_mean(metric_key),
)
)
print(
" current AS: {:.4f} baseline AS: {:.4f}".format(
thresh_as, base_as
)
)
if max_thresh - min_thresh <= precision:
break
print("completed binary search for layer {}")
print(" found threshold: {}".format(thresh))
print(
" AS delta: {:.4f} ({:.4f} => {:.4f})".format(
thresh_as - base_as, base_as, thresh_as
)
)
return LayerBoostResults(
layer, thresh, thresh_as, thresh_res, base_as, base_res
)
def _measure_layer(
self, layer: Union[str, None], module: Module, device: str, desc: str
) -> Tuple[ModuleRunResults, Tensor]:
layer = get_layer(layer, module) if layer else None
as_analyzer = None
if layer:
as_analyzer = ModuleASAnalyzer(layer, dim=None, track_outputs_sparsity=True)
as_analyzer.enable()
tester = ModuleTester(module, device, self._loss)
data_loader = DataLoader(
self._dataset, self._batch_size, **self._dataloader_kwargs
)
results = tester.run(
data_loader, desc=desc, show_progress=True, track_results=True
)
if as_analyzer:
as_analyzer.disable()
return results, as_analyzer.outputs_sparsity_mean if as_analyzer else None
@staticmethod
def _get_mid_point(start: float, end: float) -> float:
return (end - start) / 2.0 + start
@staticmethod
def _passes_loss(
base_res: ModuleRunResults,
thresh_res: ModuleRunResults,
max_target_metric_loss: float,
metric_key: str,
metric_increases: bool,
) -> bool:
diff = (
thresh_res.result_mean(metric_key) - base_res.result_mean(metric_key)
if metric_increases
else base_res.result_mean(metric_key) - thresh_res.result_mean(metric_key)
)
return diff < max_target_metric_loss