Shreyu is a fully featured admin and dashboard template.
Shreyu comes with tones of well designed & ready to use
UI elements, components, widgets and
pages.
Multiple navigation layouts and navigation color schemes are available to cater need of any modern web
application.
We understand that having only html bundle is not enough and so we have developed the
React, Angular, Vue and Laravel versions as well.
Fully responsive and resuable widgets covering statistics, user profile, team, chat, tasks, etc.
Here are some of the basic types of questions for our customers. For
more
information please contact us.
Yup, the marketplace license allows you to use this theme in any end product. For more information on licenses, please refer here.
Use our dedicated support email<EMAIL_ADDRESS>to send your issues or feedback. We are here to help anytime.
No. This is a HTML template. It won't work directly with wordpress. However you can convert this into wordpress compatible theme.
Yes, We will update the Shreyu regularly. All the future updates would be available without any cost.


This is the first in a series of team building guides. This guide will focus on the popular Perfect Attack / Critical Chance (PA/crit) team. PA/Crit is the most commonly recommended early team composition, but it took me a while to understand why this is the case. This guide will address the following areas:
PA/Crit is a highly offensive team that works by killing the enemies before they can kill (or even hit) you.
Perfect Attack adds up all damage from your team and applies it to all or one of the enemies on the map. This damage is not modified by passives that increase “attack” or elemental damage types, but it can still do a critical hit for 3x damage. By combining buffs to PA damage and crit chance, this type of team can put out extremely high damage numbers consistently enough to win PVP and clear other challenging content.
PA/Crit is the most popular beginner team for a number of reasons.
One of the advantages of a PA/Crit team is that it only really needs a few pieces to get started. There are now PA boosters of every element, of which you only really need one. There’s a starter hero with a crit boost (Akayuki). Ann the Witch’s Disciple is available at 3*, and so is easily accessible to new players.
Perfect Attack and Crit buffs don’t rely on specific attack type strategies, either, so you can easily bring new 6* characters into the fold while you’re collecting pieces of your team.
There’s nothing magical about PA/Crit that allows it to advance faster, but it is one of the few team types that can easily utilize 1 character for each element type, which DOES allow it to advance faster. The two main reasons for this are:
PA/Crit team also is easily constructed without a Story Hero backbone, meaning your awakening costs can be kept to a minimum. Furthermore, because the 4* awakenings (dash bonus upgrade) don’t affect PA damage, you have a little more flexibility in how you order your awakening goals.
This is the real strength of the PA/Crit team. Let’s start with a few facts about PA:


Background
- I am passionate about teaching young girls to code, and a life-long learner relentlessly pursuing new skills.
- I've lived in six different states, visited seven different countries, and worked a wide variety of jobs from yarn shop afficionado, to barista, and most recently - software developer!
- I earned my Bachelor's Degree in Anthropology and Art History in 2013. After bouncing around to various careers, I found my true passion in creating fantastic looking and delightfully functioning websites.
- To learn more, view my resume
Goals
I am actively working to continue to grow my knowledge, skills, and abilities in:
- HTML5
- CSS3
- WordPress
- Responsive Design
- Accessibility
- Git
- Terminal / Command Line
- Continuous Integration
- Agile Workflow
I am an ambitious and enthusiastic developer, who would love to work building delightful web experiences by creating accessible, responsive, beautiful websites.


| 010:109 Khan | : |
And (O Muhammad SAW), follow the inspiration sent unto you, and be patient till Allah gives judgement. And He is the Best of judges. |
| 010:109 Maulana | : |
And follow what is revealed to thee and be patient till Allah give judgment, and He is the Best of the judges. |
| 010:109 Pickthal | : |
And (O Muhammad) follow that which is inspired in thee, and forbear until Allah give judgment. And He is the Best of Judges. |
| 010:109 Rashad | : |
Follow what is revealed to you, and be patient until GOD issues His judgment; He is the best judge. |
| 010:109 Sarwar | : |
(Muhammad), follow what is revealed to you and have patience until God issues His Judgment; He is the best Judge. |
| 010:109 Shakir | : |
And follow what is revealed to you and be patient till Allah should give judgment, and He is the best of the judges. |
| 010:109 Sherali | : |
And follow that which is revealed to thee and be steadfast until ALLAH gives HIS judgment. And ALLAH is the Best of judges. |
| 010:109 Yusufali | : |
Follow thou the inspiration sent unto thee, and be patient and constant, till Allah do decide: for He is the best to decide. |
Concepts/Themes Covered: أركان الإسلام > التوحيد > توحيد الله تعالي > صفات الله تعالى > خير الحاكمين Pillars of Islam> Islamic> Oneness of Allah> His Glory's Characteristics> The Best to Judges أركان الإسلام > (محمد (صلى الله عليه وسلم > الوحي Pillars of Islam> The Blessed Muhammad(PBUH)> The Revelation الإنسان والعلاقات الأخلاقية > الأخلاق الحميدة > الصبر Man and The Moral Relations> Good Morals>Patience العلاقات السياسية والعامة > الحكم General and Political Relationships>The Judgement
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


Video: Fan meets Ronaldinho, trolls him by calling him the ‘Brazilian Bolasie’
by Magnus EriksenA fan met Ronaldinho outside a club but was not particularly starstruck by the Barcelona and Brazil legend.
You can see their little chat in the short video clip below.
However, in a follow-up tweet, this fan mocks Ronaldinho by calling him the ‘Brazilian Bolasie’, rather than a real star like Neymar.
This is brutal disrespect to a modern great, though that’s not to say step-over king Bolasie was a bad player by any means! ?


Constructor
new Video(hash, test)
Create a Video Instance.
Parameters:
| Name | Type | Description |
|---|---|---|
hash |
string | the hash for this video, returned by rest api when taking a video. |
test |
object | an AutomatedTest object that represents a test currently running. |
Methods
(async) getInfo() → {object}
Calls out to the api to get updated info for this video.
Returns:
Object with all of the info for a specific video.
- Type
- object
(async) saveLocally(location)
Save all videos locally.
Parameters:
| Name | Type | Description |
|---|---|---|
location |
string | Save videos to specified location. |
setDescription(description)
Sets the description for this video.
Parameters:
| Name | Type | Description |
|---|---|---|
description |
string | Set the description for the video. |
stopRecording()
Sends the command to stop a video recording.


Bot Bot Server
+
Choose a session
Back
|
Refresh
Export as CSV
|
|
Records of session:
| Session state:
Add a new record after
After
Before Entry No.
 All the records inside the session will be deleted.


| Module | ActiveRecord::Acts::List::InstanceMethods |
| In: |
vendor/rails/activerecord/lib/active_record/acts/list.rb
|
All the methods available to a record that has had acts_as_list specified. Each method works by assuming the object to be the item in the list, so chapter.move_lower would move that chapter lower in the list of all chapters. Likewise, chapter.first? would return true if that chapter is the first in the list of all chapters.
Decrease the position of this item without adjusting the rest of the list.
# File vendor/rails/activerecord/lib/active_record/acts/list.rb, line 133 133: def decrement_position 134: return unless in_list? 135: update_attribute position_column, self.send(position_column).to_i - 1 136: end
Return true if this object is the first in the list.
# File vendor/rails/activerecord/lib/active_record/acts/list.rb, line 139 139: def first? 140: return false unless in_list? 141: self.send(position_column) == 1 142: end
Return the next higher item in the list.
# File vendor/rails/activerecord/lib/active_record/acts/list.rb, line 151 151: def higher_item 152: return nil unless in_list? 153: acts_as_list_class.find(:first, :conditions => 154: "#{scope_condition} AND #{position_column} = #{(send(position_column).to_i - 1).to_s}" 155: ) 156: end
# File vendor/rails/activerecord/lib/active_record/acts/list.rb, line 166 166: def in_list? 167: !send(position_column).nil? 168: end
Increase the position of this item without adjusting the rest of the list.
# File vendor/rails/activerecord/lib/active_record/acts/list.rb, line 127 127: def increment_position 128: return unless in_list? 129: update_attribute position_column, self.send(position_column).to_i + 1 130: end
# File vendor/rails/activerecord/lib/active_record/acts/list.rb, line 78 78: def insert_at(position = 1) 79: insert_at_position(position) 80: end
Return true if this object is the last in the list.
# File vendor/rails/activerecord/lib/active_record/acts/list.rb, line 145 145: def last? 146: return false unless in_list? 147: self.send(position_column) == bottom_position_in_list 148: end
Return the next lower item in the list.
# File vendor/rails/activerecord/lib/active_record/acts/list.rb, line 159 159: def lower_item 160: return nil unless in_list? 161: acts_as_list_class.find(:first, :conditions => 162: "#{scope_condition} AND #{position_column} = #{(send(position_column).to_i + 1).to_s}" 163: ) 164: end
Swap positions with the next higher item, if one exists.
# File vendor/rails/activerecord/lib/active_record/acts/list.rb, line 93 93: def move_higher 94: return unless higher_item 95: 96: acts_as_list_class.transaction do 97: higher_item.increment_position 98: decrement_position 99: end 100: end
Swap positions with the next lower item, if one exists.
# File vendor/rails/activerecord/lib/active_record/acts/list.rb, line 83 83: def move_lower 84: return unless lower_item 85: 86: acts_as_list_class.transaction do 87: lower_item.decrement_position 88: increment_position 89: end 90: end
Move to the bottom of the list. If the item is already in the list, the items below it have their position adjusted accordingly.
# File vendor/rails/activerecord/lib/active_record/acts/list.rb, line 104 104: def move_to_bottom 105: return unless in_list? 106: acts_as_list_class.transaction do 107: decrement_positions_on_lower_items 108: assume_bottom_position 109: end 110: end
Move to the top of the list. If the item is already in the list, the items above it have their position adjusted accordingly.
# File vendor/rails/activerecord/lib/active_record/acts/list.rb, line 114 114: def move_to_top 115: return unless in_list? 116: acts_as_list_class.transaction do 117: increment_positions_on_higher_items 118: assume_top_position 119: end 120: end


the blog
tales from DBC
previous entries
- first
- second
- third
- fourth
- fifth
- sixth
- seventh
- eigth
- ninth
- ten
- eleven
- twelve
- thirteen
- fourteen
- fifteen
- sixteen
May 9th - Conflict
- Discuss a time you had a conflict. What was it about? What happened?
- What was the source of the conflict?
- What basic emotions did you feel upon analyzing the conflict?
- What actions did you take to resolve your conflict?
- If you could go back, what would you do differently, if anything?
- What did you learn from this experience?
1. I had a conflict with a pairing partner over whether to use divs or unordered lists. He presented the former, I countered with the latter.
2. The source of the conflict was over which ideas we presented, and more essentially, pride over which idea was correct.
3. Upon analyzing the conflict I realized I felt frustrated, because I knew that in this particular situation, that my idea made more sense. I also felt anxious, because I worried that my partner would be defensive if I insisted on my idea.
4. In order to resolve the conflict, I presented my reasoning. I kept the issue centered on me: "Well, to me it makes sense because..." rather than focusing on his idea.
5. I don't think I would go back to try anything different on this conflict. By suggesting my reasoning, my partner saw my point of view, and we eventually ended up doing it my way. I felt good about it, not because I was "right," but because the conflict was resolved amicably.
6. I learned that, often, presenting your side of an idea without adding judgment value - i.e. "I'm right, you're wrong" - can be a valuable technique in a conflict.


Kollam is a city in the state of Kerala, on India's Malabar Coast. It’s known as a trade hub and for its beaches, like lively Kollam and secluded Thirumullavaram. Sardar Vallabhbhai Patel Police Museum has artifacts tracing the history of the police force. Nearby, Ashtamudi Lake is a gateway to the Kerala backwaters, a network of waterways rich with vegetation. The striped 1902 Tangasseri Lighthouse has ocean views
Kollam is an ancient trading town – trading with Romans, Chinese, Arabs and other Orientals – mentioned in historical citations dating back to Biblical times and the reign of Solomon, connecting with Red Sea ports of the Arabian Sea (supported by a find of ancient Roman coins).There was also internal trade through the Aryankavu Pass in Schenkottah Gap connecting the ancient town to Tamil Nadu.
A place of great historic importance, Thevally Palace is situated on the banks of Ashtamude Lake. Once served as the home of Maharaja of Travancore, it was constructed under the rule of Gauri Parvathi Bai between 1800 and 1819.
Lying at a distance of just 2 km from kollam town is Mahatma Gandhi Beach and Park which is quite popular as a picnic spot among locals and tourists.
A gorgeous waterfall located on the Kollam-Shencottah Road at Palaruvi is lying at an altitude of 300 feet; the ideal time to enjoy the freshness of the waterfall is from June to January.


Drawing by: Valia Dempsey
About Inktober
Every October, artists from all over the world participate in the month long drawing challenge by doing one ink drawing a day the entire month. There is a prompt for each day of the challenge that outlines a theme for the participant can use to base their drawings. Inktober started in 2009 created by Jake Parker, an illustrator whose work includes animated films, comics, and picture books.
Inktober helps artist improve design skills, develop positive drawing habits, and boost creativity. Thousands of artists take on the challenge each year, which has helped contributed to almost 4 million #inktober posts on instagram, and over 150,000 followers on Instagram and Twitter.
You don’t have to be an artist to do Inktober, just pick up a pen and start drawing!
Rules
- Make a drawing in ink
- Post it online
- Hashtag it with #inktober and #inktober2017
- Repeat everyday for the month of October
Drawing by: Katie Pikes
Drawing by: Emily Jiménez
Tips
- You don’t have to follow the prompts, but they help
- Give each drawing a short description
- Browse the hashtag, see what others are drawing and engage with them
- Keep your tools on you wherever you go
- To avoid smudging, ink from left to right
- Pick an overall theme for all your drawings
- If you have time, try and draw ahead of time
- Have fun!
Prompts
- Swift
- Divided
- Poison
- Underwater
- Long
- Sword
- Shy
- Crooked
- Screech
- Gigantic
- Run
- Shattered
- Teeming
- Fierce
- Mysterious
- Fat
- Graceful
- Filthy
- Cloud
- Deep
- Furious
- Trail
- Juicy
- Blind
- Ship
- Squeak
- Climb
- Fall
- United
- Found
- Mask


{% include "includes/header.html" %} This comic wasn't found One of the following errors could happend: You put letters instead of numbers You searched an unexisting copy of the comic {% include "includes/footer.html" %}


{% if completed_applications %}
| Date Submitted | Application To | Submitted By | Assigned To | Action(s) |
|---|---|---|---|---|
|
{{application.request_date | date:"Y-m-d"}} {{application.request_date | date:"F d, Y"}} |
{{application.template}} | {{application.request_user}} | {% if application.response_user %} {{application.response_user}} {% else %} Assign self {% endif %} | View Application |
No applications found.
{% endif %}


I'm Casey, a software developer located in Seattle, WA. I consider myself a lifelong learner, and am always searching for new, interesting technologies to make software that is easy to use and intuitive.
Outside of developing software, I enjoy playing video games, binge-watching Netflix shows with my significant other, and spending time with my cats: Maru, KitKit, and Kenji.
A breakout style game with invaders! Control the paddle with your mouse to hit the ball at the invaders while avoiding being hit by the bullets.
Play NowA simplistic Youtube clone, without the clutter of Youtube. Made with React.
OpenA JavaFX appointment scheduling application that connects to MySQL database. Contains a log-in, calendar, tracking for user log-ins, and various reports for the user.
GithubAn application for WGU students to track their term progress. Allows students to add and remove terms and courses, change course statuses, add assessments to courses, and keep notes on both courses and assessments.
GithubA game backlog app with React frontend and Firebase backend.
Github


[
home
/
boards
/
overboard
/
help
]
Account
Logged in as:
Global Management
Moderation Manual
Settings
E-mail:
Always use role signature
Lock account for 24 hours after too many failed login attempts
If you entered an email you will receive a link to unlock it immediately
Password Change
Current Password:
New Password:
Confirm New Password:
Owned Boards
Volunteered Boards
Create Board
Board URI:
Board Name:
Board Description:
no cookies?


In this demonstration, a more elaborate linear shift-invariant system is studied. In this system, the output y(n) (shown in blue below) is a linear combination of the previous 32 inputs x(n), x(n-1), ... x(n-31). Notice that even with this more elaborate system, a sinusoidal input still yields a sinusoidal output.
In the above plot, the input sinusoid is at 440 Hz, and the output sinusoid is only slightly attenuated. The sample rate is again 8kHz. In this demonstration, if we vary the frequency of the input sine wave above about 800 Hz, the amplitude of the output drops off markedly. The amplitude response is shown below in blue, with the red spike again indicating the frequency of the input (440 Hz).
The frequency scale is unfortunately not correctly labeled. It ranges from 0 to 64, which corresponds to frequencies from 0 to 2 kHz. This filter is called a low-pass filter. Frequencies below about 800 Hz (approximately 25 on the horizontal scale) pass through the system with only slight attenuation or slight gain. The gain is near unity in this "passband". Frequencies above 800 Hz are attenuated to less than about 0.1 of their original amplitude.
As explained above, each output sample y(n) is a weighted linear combination of 32 input samples. The choice of weights determines the frequency response of the system, and is a topic of EE123.


Snow Falling on Cedars (1999) by John Sylva Rating: A
Too many films today rely solely on dialogue to tell their story, as nothing is left for the imagination or mind to devour, but only for the ears to enjoy. "Snow Falling On Cedars," Australian director Scott Hicks' follow up to 1996's heart warming "Shine," is almost dialogue free, relying on magnificent shots and settings to tell the thoughtful story on their own. This clever tactic succeeds triumphantly, telling a complex story with deep meaning without a hint of wear and tear, delivering some of the most powerful, heart wrenching scenes in a motion picture this year, many without a word of dialogue. Hicks co-adapts "Snow" with Ronald Bass from the best selling novel of the same name, penned by David Guterson. If it wasn't for the stunning visuals, "Snow" could have been a bumbling mess of a film, but instead is one of the year's strongest.
The hypnotic, overwhelming picture of prejudice, truth, love, and war opens just north of Puget Sound, where a fisherman is savagely murdered by the suspected Japanese fisherman Kazuo Miyamoto (Rick Yune), who is charged for murder and put on trial. From this sequence, "Snow" has already wrapped you in its artistic ways, leaving you spellbound in its beauty for the entire course of the film. "Snow" tells its story during the World War II era, in a time where racial ties between the Chinese and American cultures weren't particularly strong, a fact which later serves as a subplot between two central characters. Defending Miyamoto is Nels Gudmundsson (Max von Sydow), an elderly, caring man, prosecuting him Alvin Hooks (James Rebhorn), an efficient, serious man. As the trial unfolds, so does the deep plot in form of flashback, mainly focusing on the romance between Ishmael Chambers (Ethan Hawke), newspaper journalist covering the trial, and Hatsue Miyamoto (Youki Kudoh), who later became wife to the convicted murderer. We learn Ishmael and Hatsue had a childhood love affair throughout their younger years, but were separated by the war, in which Hatsue, along with her family, ended up in a camp, and Ishmael was sent to battle, in which he'd lose an arm.
The acting is up to par all around, mainly in supporting areas, where Kudoh steals the show as her troubled, generally sad character. Ethan Hawke may be the main focus of the film, but is, for the majority of the film, silent. Kudoh and Hawke have wonderful on screen chemistry together, most of the time tense and unstable, without a word being spoken, which adds to the realness of the situations presented to the viewer. The two particularly shine in the final, unspeakably emotional final shots, which will entrance every bone in your body with their sheer power. Also of note is Max von Sydow, who delivers a well executed performance in some of the film's most memorable scenes.
Appearing at first to be simply a murder mystery, "Snow Falling on Cedars" tells multiple, enchanting stories throughout the course of the trial, all connecting somehow to the characters within the courtroom. The film is captivating in a way which films rarely are, blinding you with its blistering intelligence and stunning visuals. "Snow" is a miraculous picture, an absorbing, one of a kind thriller, that shows even more promise coming from director Scott Hicks. The characters within are real, strongly written souls with much background to prove themselves worthy of their personalities. The film moves at a deliberately slow pace, building its story to a stronger level with each passing minute, until everything about the plot becomes crystal clear. Hicks' direction has got to be the best in a film this year, pacing the film in such a way to make the viewer anxious as to what will occur in the coming moments. The film transfers between war stories and love stories, all which polish off this professional, unforgettable work of art. "Snow" is excitingly clever in the way which it tells its compelling story, always presenting every image, from a dying fish to a pine tree, with artistic, beautiful compassion. Also worth praising is that "Snow" depicts the era in which it is set realistically, revealing the awful things the U.S. did to Japanese Americans as a result of the bombing of Pearl Harbor. Provocative is the best word to describe the atmospheric film, whose structure is so well planned and thoughtful, it's hard to decipher how one could be so talented to put this film together. The rich musical score serves as a perfect backdrop for the real star of the show, the setting, playing out loud, melodic pieces to aid the moving story.
"Snow Falling on Cedars" is a rare gem, that doesn't follow the simple path most courtroom thrillers take. If this route was taken, every ounce of beauty and cleverness would be sucked dry from the film, as the originality of the script is what makes "Snow" glisten in so many departments. Many will dislike the film for its choice of narrative structure, but to some, "Snow" should undoubtedly stand as one of the year's best, most breathtaking films. Words can't describe the lush settings of "Snow," or the captivating story, so to experience what the film has to offer, it's best to travel to your theater, kick back with your popcorn, and embrace the power and beauty that is, "Snow Falling on Cedars."
The Bottom Line: "Snow Falling on Cedars" is a rich, beautiful, compassionate film with heavy subject matter, that unfolds flawlessly, against eye popping, mind blowing backdrops. A triumph.
Film reviewed January 10th, 1999.
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


Use a cloud
There are many variations of passages going to use passage anything.
Cloud in a box
There are many variations of passages going to use passage anything.


YEAR
{{msgInfo.Year}}
DELIYEARABLES
{{msgInfo.Deliverables}}
TEAM
{{msgInfo.Team}}
{{msgInfo.Description}}
PROJECT
PORTFOLIO PROJECT #1
This portfolio is the best way to show my work, you can see here a big range of my work.
Website Projects
This is my portfolio, you can click different project!
Demo Reel
I occasionally take on freelance opportunities. Have an exciting project where you need some help? Send me over a message, and let's chat.
contact me
Download Resume


Christophe Ramsamy
How did we get here?
var http = require('http');
var app = function (req, res) {
res.writeHead(200, {
'Content-Type': 'application/json'
});
res.end(JSON.stringify({"payload":"Hello World"}));
};
var server = http.createServer(app);
server.listen(1337);
$server = stream_socket_server('tcp://<IP_ADDRESS>:1337');
while ($conn = stream_socket_accept($server,-1)){
fwrite($conn, "HTTP/1.1 200 OK\n");
fwrite($conn, "Content-Length: 24\n\n");
fwrite($conn, '{"payload": "Hello world"}');
fclose($conn);
}
Many approaches and solutions have been implemented
Simplest way is via pecl.
$ sudo pecl install swoole
In ubuntu 16.04 LTS
$ sudo apt install php-pear
$ sudo apt install php7.0-dev
$ sudo pecl install swoole
$http = new swoole_http_server("<IP_ADDRESS>", 1337, SWOOLE_BASE);
$data = ['payload' => 'Hello World'];
$http->on('request', function ($request, swoole_http_response $response) use($data) {
$response->header('Content-Type', 'application/json');
$response->end(json_encode($data));
});
$http->start();
What about performance?
Not to mention, that's a lot of talk and not much code, just saying...
You can:
Have any questions?


Information for teachers
This section contains answers to questions frequently asked by teachers.
Parents are also encouraged to read this section to gain further knowledge
of the capabilites og the teacher or tutor.
What should I look for in the Classroom
It is common for specific learning disabilities to be overlooked.
Teachers and parents often mistakenly
assume that because the
isn't succeeding they just aren't very bright.This is made more likely
by the
fact that learning disabilities commonly co-occur. Research suggests
that 50% of children with dyscalculia
will also have dyslexia, and 20% ADHD (attentional deficit and hyperactivity disorder).
In addition learning
disabilities can cause children to become frustrated and develop behavioural problems,
which then become
the focus of any intervention, leaving the underlying cause unaddressed.
If in doubt, refer a child for assessment. A trained specialist will run tests for IQ, maths,
reading and attention,
and will be able to figure out if the problem is a general or
specific one.Even if the problem is a general one,
the child is just as entitled to extra help!
The following is a list of key dyscalculia symptoms to look for
(see the Symptoms section for an in depth discussion)Seems to have little "number sense" Trouble with
counting,
memorising arithmetical facts, following procedures, or executing strategies - inaccurate, slow
or both.
Exhibits dislike of or anxiety towards maths, and/or avoidance behaviours
General Principles
- Allow enough time for pupils to master a basic concept before moving on.
- Work throughout the concept or maths problems with manipulatives before
writing answers or progressing to written problems.Never insist everything
is written.Practical concrete experience with manipulatives should come first.
- Playing mathematical games are an essential part of learning
- Make math active and fun
- Allow mastery to foster a positive attitude towards math
Strategies to Build Students’ Number Sense
- Have class discussions about strategies for computing
- Make estmation an integral part of computing.
- Model different methods for computing
- Question students about how they reason numerically.


The Project.meta file¶
What is the Project.meta file¶
The Project.meta file is bake’s configuration file.
Every project has a Project.meta file in the project root directory.
A Project.meta file contains one or more build configurations.
A build configuration consists of toolchain settings, files to build, custom steps, etc.
Example¶
Project.meta file of Main project |
Project.meta file of Sub project |
|---|---|
Project {
ExecutableConfig Debug {
Dependency Sub, config: Debug
Files "**/*.cpp"
IncludeDir "include"
DefaultToolchain GCC {
Compiler CPP {
Flags "-Wall"
}
}
PostSteps {
CommandLine "echo $(ArtifactName) built."
}
}
}
|
Project {
LibraryConfig Debug {
Files "**/*.cpp"
IncludeDir "include"
IncludeDir "Main/include"
ExternalLibrarySearchPath "lib"
ExternalLibrary "a"
ExternalLibrary "b"
Toolchain {
Compiler CPP {
Flags add: "-g3"
}
}
}
}
|
Let’s assume that Main and Sub are located in the same workspace root. To build the executable, bake can be called from the Main directory.
User@Host:~/my_project$ bake -b Debug
What happens now?
Reading Project.meta of Main
Reading Project.meta of dependencies (Sub)
- Compiling sources of Sub, e.g.:
User@Host:~$ g++ -c -Wall -g3 -Iinclude -I../Main/include -o Debug_Main/src/xy.o src/xy.cpp
Wall is taken from the DefaultToolchain and -g3 is added by the toolchain of the Sub project.
The include path to Main is automatically adjusted.
The order of includes is the same as in Project.meta.
g++, -c and -I are used, because GCC was specified in the DefaultToolchain.
Archiving the library, e.g.:
User@Host:~$ ar -rc Debug_Main/libSub.a Debug_Main/src/xy.o
Compiling sources of Main, e.g.:
User@Host:~$ g++ -c -Wall -Iinclude -o Debug/src/main.o src/main.cpp
Linking executable, e.g.:
User@Host:~$ g++ -o Debug/Main.exe Debug/src/main.o ../Sub/Debug_Main/libSub.a -L../Sub/lib -la -lb
The library search paths and libraries are added in the specified order.
Executing the post step
User@Host:~$ echo Main.exe built.The variable was automatically substituted.


@@include('../partials/head/head.html')
@@include('../partials/components/header.html') @@include('../partials/components/vue-app.html')
@@include('../partials/scripts/vue-embed.html') @@include('../partials/scripts/common.html')


Before Change
self._beatsync_features = self.compute_beat_sync_features(pad)
// Choose features based on type (beatsync or framesync)
self._features = self._beatsync_features \
if self.beat_sync else self._framesync_features
return self._features
def compute_features(self):
After Change
import pdb; pdb.set_trace() // XXX BREAKPOINT
// Choose features based on type
if self.feat_type is FeatureTypes.framesync:
self._features = self._framesync_features
elif self.feat_type is FeatureTypes.est_beatsync:
self._features = self._est_beatsync_features
elif self.feat_type is FeatureTypes.ann_beatsync:
if self._ann_beatsync_features is None:
// TODO: Improve error checking
logging.warning("NO ANNOTATED BEATS!")
self._features = self._est_beatsync_features
else:
self._features = self._ann_beatsync_features
// TODO: What if feat_type is wrong?
return self._features
def compute_features(self):
raise NotImplementedError("This method must contain the actual "


Soy Cristian Cala desarro......
This is a wider card with supporting text below as a natural lead-in to
additional content. This content is a little bit longer.
CONOCIMIENTOS
Jose Sierra
Desarrollador
Soy Jose Sierra desarro......
This is a wider card with supporting text below as a natural lead-in to
additional content. This content is a little bit longer.


T.R.I.A.D and Ushra'Khan have a long and rich history heavily interwoven with the lore of EVE. We have been one of the core entities in Minmatar faction warfare for several years.
We offer regular gang and fleet ops; in fact, there's an alliance fleet up almost 24/7.
Ushra'Khan owns one system in sov null sec. We are recruiting pvp, ratting, mining, and industrialist pilots interested in helping us establish these operations.
There's lots of opportunities to make isk and shoot things, while being part of a team working together on common goals.


Copyright (c) 2003 Joćo Neto
UN is played on the following board:
|
| An example The neutral stone was dropped in the middle cell (the marked white stone). The numbers indicate the game moves. |
| An example In this position, the next player loses the game. Whatever he does, the other player will stalemate him (moving to one of the red dots). |
Bill Taylor and Richard Rognlie extended the concept to square boards (with diagonals, which gives the game a greater depth) and to multiple heads (increase the tactical element). The idea behind multiple heads is that each sliding will create a new head until a maximum number is achieved. Bill called these multiple head variants Hydra for hexagons and Medusa for squares. Un, in this context, is Hydra(1). Here is an opening example of a Hydra(4) game:
| 4 heads A position of Hydra(4) after six moves. The first four moves created a new head. Now each player must manage those heads until all are stalemated. |
Related games: Slimetrail and Snailtrail.


| [ < ] | [ > ] | [ << ] | [ Up ] | [ >> ] | [Top] | [Contents] | [Index] | [ ? ] |
srfi-43
- ベクタライブラリこのモジュールはベクタ用のライブラリ関数を提供します。 SRFI-43のいくつかの関数は組み込みになっています。ベクタを見てく ださい。
[SRFI-43]
[SRFI-43]
[SRFI-43]
[SRFI-43] Returns a newly allocated vector whose contents are concatenation of elements of vec in order.
[SRFI-43]
Acts like (apply vector-append list-of-vectors)
, though
this may be more efficient.
[SRFI-43]
Returns #t
if vec’s length is zero, and
#f
if vec’s length is more than zero.
Signals an error if vec is not a vector.
[SRFI-43]
Compares vecs element-wise, using given predicate elt=.
Returns #t
iff lengths of all the vectors are the same,
and every corresponding elements are equal by elt=.
Elt= is always called with two arguments and must
return #t
iff two are the same.
[SRFI-43]
Kons is a procedure that takes n+2 arguments, where
n is the number of given vectors. For each element of the
given vectors, kons is called as
(kons i seed e_1i e_2i …)
,
where i is the index, and e_ni is the i-th element
of the vector n. If the lengths of the vectors differ,
iteration stops when the shortest vector is exhausted.
The initial value of seed is knil, and the return value
from kons is used as the next seed value. The last return value
of kons is returned from vector-fold
.
The iteration is strictly left to right.
Note that the seed value precedes elements, which is opposite to
fold
(See section コレクションに対するマッピング). It’s an unfortunate
historical glitch; vector-fold-left
would be more consistent
name.
[SRFI-43]
Like vector-fold
, but iterates right to left.
[SRFI-43]
The argument f is a procedure that takes n+1 arguments where
n is the number of given vectors. These procedures call f
for each element of the given vectors as
(f i e_1i e_2i …)
,
where i is the index, and e_ni is the i-th element
of the vector n. If the lengths of the vectors differ, iteration
only covers the shortest vector.
vector-map
creates a fresh vector out of the result of applications
of f and returns it.
vector-map!
reuses vec1 to
store the result and returns vec1; hence vec1 must be mutable.
vector-for-each
is for side-effects. It discards the result of
f.
vector-count
counts the number of times f returned a true value.
(vector-map list '#(a b c)) ⇒ #((0 a) (1 b) (2 c)) (vector-map list '#(a b c) '#(d e f g)) ⇒ #((0 a d) (1 b e) (2 c f)) (vector-count = '#(0 2 2 4 4)) ⇒ 3 |
Note: The generic map
and for-each
in gauche.collection
can be used
on vectors, but the procedure is called without index, and the result
is returned as a list.
(vector-map f vec1 vec2 …)
is operationally equivalent to
(map-to-with-index <vector> f vec1 vec2 …)
.
See gauche.collection
- コレクションフレームワーク and gauche.sequence
- シーケンスフレームワーク.
[SRFI-43]
Returns the index of the first or the last elements in vec1
vec2 … that satisfy pred, respectively.
Returns #f
if no elements satisfy pred.
In vector-index
, comparison ends at the end of the shortest vector.
For vector-index-right
, all the vectors must have the same length.
[SRFI-43]
Like vector-index
and vector-index-right
, except that
the result of pred is negated. That is, returns the index
of the first or the last elements that don’t sastisfy pred.
[SRFI-43+]
Look for value in a vector vec, and returns its
index if it is found, or #f
if it is not found.
Comparison of value and an element in vec is
done by a procedure cmp, which takes two arguments,
and should return a negative integer if the first argument is less than the
second, 0 if they are the same, and a positive integer if the first
is greater than tne second.
Elements in vec must be ordered from smaller to greater w.r.t. cmp. Using that fact, this procedure performs binary search instead of linear search.
The optional arguments start and end are an extention to SRFI-43, and can be used to limit the range of the search in start-th element (inclusive) to end-th element (exclusive).
[SRFI-43]
Applies pred on each corresponding elements
of vec1 vec2 … left to right, and
as soon as pred returns non-#f
value,
the procedure stops iteration and returns the value.
If no elements that satisfy pred are found, it returns #f
.
Vectors can have different lengths. Iteration stops at the end of the shortest.
[SRFI-43]
Applies pred on each corresponding elements
of vec1 vec2 … left to right.
If all the elements (when the lengths of vectors differ, the
first N elements where N is the length of the shortest) satisfy
pred, returns the last result of pred. Otherwise
returns #t
.
[SRFI-43]
Swaps vector vec’s i
-th and j
-th elements.
[SRFI-43]
[SRFI-43]
[SRFI-43]
[SRFI-43]
[SRFI-43]
| [ < ] | [ > ] | [ << ] | [ Up ] | [ >> ] |
This document was generated by Shiro Kawai on May 28, 2012 using texi2html 1.82.


This week's project entailed creating six shapes from a selection of almost 50 designs.
After completing the first shape, I felt like I was starting to refamiliarize myself with programs like Fusion 360.
Link to design #1 Link to design #32 Link to design #41


"I have not failed.
I’ve just found 10,000 ways that won't work."

Learn as if you were to live forever."
Mahatma Gandhi
"No one can make you feel inferior without your consent."
Eleanor Roosevelt
"You have to learn the rules of the game, and then you have to play better than anyone else."
Albert Einstein
"Don't let the fear of losing be greater than the excitement of winning."
Robert Kiyosaki
"The question isn't who is going to let me;
it's who is going to stop me."
Ayn Rand
Vertical Blinds - Quotations
by
6th August 2014
A second responsive vertical scrolling template with overlapping sections.
Works in all the latest browsers and OS, including IE7+, Android and Windows 8 smartphones.
COMMENTS


The GitHub username of the user
Returns all commit contributions by year for user. Null is returned if user with given username was not found.
NOTE:
Might take several seconds to fetch data, as data has to be fetched serially month by month. This is due to GitHub's requirement of not making requests for a single user concurrently. This results in slower performance, but avoids failures. See: https://developer.github.com/v3/guides/best-practices-for-integrators/#dealing-with-abuse-rate-limits
Might include contributions to private repositories depending on GitHub settings (see: https://help.github.com/en/articles/publicizing-or-hiding-your-private-contributions-on-your-profile) and access token scopes (see: https://developer.github.com/apps/building-oauth-apps/understanding-scopes-for-oauth-apps/)
The GitHub username of the user
Returns all years in which the user has contributed code in repositories on GitHub – e.g. [2019, 2018, 2016, 2015, 2011]. Null is returned if user with given username was not found.
The GitHub username of the user
Returns all issue contributions from user for a specific month. Null is returned if user with given username was not found.
NOTE: Might include contributions to private repositories depending on GitHub settings (see: https://help.github.com/en/articles/publicizing-or-hiding-your-private-contributions-on-your-profile) and access token scopes (see: https://developer.github.com/apps/building-oauth-apps/understanding-scopes-for-oauth-apps/)
The GitHub username of the user
Returns all issue contributions from user for a specific year. Null is returned if user with given username was not found.
NOTE:
Might take several seconds to fetch data, as data has to be fetched serially month by month. This is due to GitHub's requirement of not making requests for a single user concurrently. This results in slower performance, but avoids failures. See: https://developer.github.com/v3/guides/best-practices-for-integrators/#dealing-with-abuse-rate-limits
Might include contributions to private repositories depending on GitHub settings (see: https://help.github.com/en/articles/publicizing-or-hiding-your-private-contributions-on-your-profile) and access token scopes (see: https://developer.github.com/apps/building-oauth-apps/understanding-scopes-for-oauth-apps/)
The GitHub username of the user
Calendar year to gather contributions from
Returns the organizations that the user is member of. Null is returned if user with given username was not found.
The GitHub username of the user
Returns user profile. Null is returned if user with given username was not found.
The GitHub username of the user
Returns public gists that the user has owns. Null is returned if user with given username was not found.
The GitHub username of the user
Returns public repositories that the user owns. Null is returned if user with given username was not found.
The GitHub username of the user
Returns all pull request contributions from user for a specific month. Null is returned if user with given username was not found.
NOTE: Might include contributions to private repositories depending on GitHub settings (see: https://help.github.com/en/articles/publicizing-or-hiding-your-private-contributions-on-your-profile) and access token scopes (see: https://developer.github.com/apps/building-oauth-apps/understanding-scopes-for-oauth-apps/)
The GitHub username of the user
Returns all pull request contributions from user for a specific year. Null is returned if user with given username was not found.
NOTE:
Might take several seconds to fetch data, as data has to be fetched serially month by month. This is due to GitHub's requirement of not making requests for a single user concurrently. This results in slower performance, but avoids failures. See: https://developer.github.com/v3/guides/best-practices-for-integrators/#dealing-with-abuse-rate-limits
Might include contributions to private repositories depending on GitHub settings (see: https://help.github.com/en/articles/publicizing-or-hiding-your-private-contributions-on-your-profile) and access token scopes (see: https://developer.github.com/apps/building-oauth-apps/understanding-scopes-for-oauth-apps/)
The GitHub username of the user
Returns all pull request reviews contributions from user for a specific month. Null is returned if user with given username was not found.
NOTE: Might include contributions to private repositories depending on GitHub settings (see: https://help.github.com/en/articles/publicizing-or-hiding-your-private-contributions-on-your-profile) and access token scopes (see: https://developer.github.com/apps/building-oauth-apps/understanding-scopes-for-oauth-apps/)
The GitHub username of the user
Returns all pull request reviews contributions from user for a specific year. Null is returned if user with given username was not found.
NOTE:
Might take several seconds to fetch data, as data has to be fetched serially month by month. This is due to GitHub's requirement of not making requests for a single user concurrently. This results in slower performance, but avoids failures. See: https://developer.github.com/v3/guides/best-practices-for-integrators/#dealing-with-abuse-rate-limits
Might include contributions to private repositories depending on GitHub settings (see: https://help.github.com/en/articles/publicizing-or-hiding-your-private-contributions-on-your-profile) and access token scopes (see: https://developer.github.com/apps/building-oauth-apps/understanding-scopes-for-oauth-apps/)
The GitHub username of the user
Generated using TypeDoc
Returns all commit contributions from user for a specific month. Null is returned if user with given username was not found.
NOTE: Might include contributions to private repositories depending on GitHub settings (see: https://help.github.com/en/articles/publicizing-or-hiding-your-private-contributions-on-your-profile) and access token scopes (see: https://developer.github.com/apps/building-oauth-apps/understanding-scopes-for-oauth-apps/)


Always provide 2DP and round (even if answer is 1.5 put 1.50)! Assume a perfectly competitive market.
If you don't like the values you get, refresh!


This record stores information about the SQL query string that retrieves external data for a PivotTable. The record is followed by SXSTRING records that contain the SQL strings and then by a SXSTRING record that contains the SQL server connection string.
Note: PARAMQRY has the same record number as SXEXT . This has no adverse ramifications in a BIFF file because PARAMQRY always occurs in conjunction with an SXEXT record.
Record Data — BIFF8
|
Offset |
Name |
Size |
Contents |
|
4 |
grbit |
2 |
Options flags; see following table |
|
6 |
cparams |
2 |
Number of parameter strings |
|
8 |
cstQuery |
2 |
Number of strings for SQL statement or URL |
|
10 |
cstWebPost |
2 |
Number of strings for post method of Web query |
|
12 |
cstSQLSav |
2 |
Number of strings for SQL statement for server-based page fields |
|
14 |
cstOdbcConn |
2 |
Number of strings for ODBC connection string |
The grbit field contains the following flags.
|
Bits |
Mask |
Name |
Contents |
|
2–0 |
0007h |
dbt |
=1 ODBC data source XL9: 5= OLE database XL9: 6= Text query XL9: 7= ADO query |
|
3 |
0008h |
fOdbcConn |
=1 for ODBC connection |
|
4 |
0010h |
fSql |
=1 for ODBC connection |
|
5 |
0020h |
fSqlSav |
=1 for server-based page fields |
|
6 |
0040h |
fWeb |
=1 for a Web (WWW) query |
|
7 |
0080h |
fSavePwd |
=1 if the Save Password option is on |
|
8 |
0100h |
fTablesOnlyHTML |
=1 if the Save Tables in HTML Only option is on |
|
15–9 |
FE00h |
(Reserved) |
|
The following records occur after a SXEXT record:
|
Record name |
Contents |
|
SXSTRING |
Collection of cstQuery SXSTRING records to concatenate to give the URL (Web query), SQL string (ODBC query) or parameterized SQL string (for server-based page field) |
|
SXSTRING |
Collection of cstOdbcConn SXSTRING records to concatenate to give the ODBC connection string (ODBC queries only) |
|
SXSTRING |
Collection of cstWebPost SXSTRING records to concatenate to give the post method data (Web query only, optional) |
|
PARAMQRY |
Collection of cparams PARAMQRY parameter definition records |
|
SXSTRING |
Collection of cstSQLSav SXSTRING records to concatenate to give the original SQL string for an ODBC query with server-based page fields |
Record Data — BIFF7 and earlier
|
Offset |
Name |
Size |
Contents |
|
4 |
id |
2 |
Connection ID of the SQL server |
|
6 |
fError |
2 |
=1 if an error occurred during the last attempt to communicate with the server |
|
8 |
cstSQL |
2 |
Number of SXSTRING records that follow |


this
or class
expressions.
The reported constructs include synchronized
blocks and calls to wait()
,
notify()
or notifyAll()
.
There are several reasons synchronization on this
or class
expressions may be a bad idea:
As an alternative, consider synchronizing on a private final
lock object, access to which can be completely controlled.
Example:
public void print() {
synchronized(this) { // warning: Lock operations on 'this' may have unforeseen side-effects
System.out.println("synchronized");
}
}


torch.fx¶
Overview¶
This feature is under a Beta release and its API may change.
FX is a toolkit for capturing and transforming functional PyTorch programs. It
consists of GraphModule and a corresponding intermediate representation (IR). When GraphModule is constructed
with an nn.Module
instance as its argument, GraphModule will trace through the computation of that Module’s
forward
method symbolically and record those operations in the FX intermediate representation.
import torch
import torch.fx
class MyModule(torch.nn.Module):
def __init__(self):
super().__init__()
self.param = torch.nn.Parameter(torch.rand(3, 4))
self.linear = torch.nn.Linear(4, 5)
def forward(self, x):
return torch.topk(torch.sum(self.linear(x + self.linear.weight).relu(), dim=-1), 3)
m = MyModule()
gm = torch.fx.symbolic_trace(m)
The Intermediate Representation centers around a 5-opcode format:
print(gm.graph)
graph(x):
%linear_weight : [#users=1] = self.linear.weight
%add_1 : [#users=1] = call_function[target=operator.add](args = (%x, %linear_weight), kwargs = {})
%linear_1 : [#users=1] = call_module[target=linear](args = (%add_1,), kwargs = {})
%relu_1 : [#users=1] = call_method[target=relu](args = (%linear_1,), kwargs = {})
%sum_1 : [#users=1] = call_function[target=torch.sum](args = (%relu_1,), kwargs = {dim: -1})
%topk_1 : [#users=1] = call_function[target=torch.topk](args = (%sum_1, 3), kwargs = {})
return topk_1
The Node semantics are as follows:
placeholder
represents a function input. Thename
attribute specifies the name this value will take on.target
is similarly the name of the argument.args
holds either: 1) nothing, or 2) a single argument denoting the default parameter of the function input.kwargs
is don’t-care. Placeholders correspond to the function parameters (e.g.x
) in the graph printout.get_attr
retrieves a parameter from the module hierarchy.name
is similarly the name the result of the fetch is assigned to.target
is the fully-qualified name of the parameter’s position in the module hierarchy.args
andkwargs
are don’t-carecall_function
applies a free function to some values.name
is similarly the name of the value to assign to.target
is the function to be applied.args
andkwargs
represent the arguments to the function, following the Python calling conventioncall_module
applies a module in the module hierarchy’sforward()
method to given arguments.name
is as previous.target
is the fully-qualified name of the module in the module hierarchy to call.args
andkwargs
represent the arguments to invoke the module on, including the self argument.call_method
calls a method on a value.name
is as similar.target
is the string name of the method to apply to theself
argument.args
andkwargs
represent the arguments to invoke the module on, including the self argumentoutput
contains the output of the traced function in itsargs[0]
attribute. This corresponds to the “return” statement in the Graph printout.
GraphModule automatically generates Python code for the operations it symbolically observed:
print(gm.code)
import torch
def forward(self, x):
linear_weight = self.linear.weight
add_1 = x + linear_weight; x = linear_weight = None
linear_1 = self.linear(add_1); add_1 = None
relu_1 = linear_1.relu(); linear_1 = None
sum_1 = torch.sum(relu_1, dim = -1); relu_1 = None
topk_1 = torch.topk(sum_1, 3); sum_1 = None
return topk_1
Because this code is valid PyTorch code, the resulting GraphModule
can be used in any context another
nn.Module
can be used, including in TorchScript tracing/compilation.
Limitations of Symbolic Tracing¶
TODO
Writing Transformations¶
TODO
Debugging Transformations¶
TODO
API Reference¶
-
torch.fx.
symbolic_trace
(root)[source]¶ Symbolic tracing API
Given an
nn.Module
or function instanceroot
, this function will return aGraphModule
constructed by recording operations seen while tracing throughroot
.- Parameters
root (Union[torch.nn.Module, Callable]) – Module or function to be traced and converted into a Graph representation.
- Returns
a Module created from the recorded operations from
root
.- Return type
-
torch.fx.
wrap
(fn_or_name)[source]¶ This function can be called at module-level scope to register fn_or_name as a “leaf function”. A “leaf function” will be preserved as a CallFunction node in the FX trace instead of being traced through:
# foo/bar/baz.py def my_custom_function(x, y): return x * x + y * y torch.fx.wrap('my_custom_function') def fn_to_be_traced(x, y): # When symbolic tracing, the below call to my_custom_function will be inserted into # the graph rather than tracing it. return my_custom_function(x, y)
This function can also equivalently be used as a decorator:
# foo/bar/baz.py @torch.fx.wrap def my_custom_function(x, y): return x * x + y * y
A wrapped function can be thought of a “leaf function”, analogous to the concept of “leaf modules”, that is, they are functions that are left as calls in the FX trace rather than traced through.
- Parameters
fn_or_name (Union[str, Callable]) – The function or name of the global function to insert into the graph when it’s called
-
class
torch.fx.
GraphModule
(root, graph)[source]¶ GraphModule is an nn.Module generated from an fx.Graph. Graphmodule has a
graph
attribute, as well ascode
andforward
attributes generated from thatgraph
.Warning
When
graph
is reassigned,code
andforward
will be automatically regenerated. However, if you edit the contents of thegraph
without reassigning thegraph
attribute itself, you must callrecompile()
to update the generated code.-
__init__
(root, graph)[source]¶ Construct a GraphModule.
- Parameters
root (Union[torch.nn.Module, Dict[str, Any]) –
root
can either be an nn.Module instance or a Dict mapping strings to any attribute type. In the case thatroot
is a Module, any references to Module-based objects (via qualified name) in the Graph’s Nodes’target
field will be copied over from the respective place withinroot
’s Module hierarchy into the GraphModule’s module hierarchy. In the case thatroot
is a dict, the qualified name found in a Node’starget
will be looked up directly in the dict’s keys. The object mapped to by the Dict will be copied over into the appropriate place within the GraphModule’s module hierarchy.graph (Graph) –
graph
contains the nodes this GraphModule should use for code generation
-
property
code
¶ Return the Python code generated from the
Graph
underlying thisGraphModule
.
-
property
graph
¶ Return the
Graph
underlying thisGraphModule
-
recompile
()[source]¶ Recompile this GraphModule from its
graph
attribute. This should be called after editing the containedgraph
, otherwise the generated code of thisGraphModule
will be out of date.
-
to_folder
(folder, module_name='FxModule')[source]¶ Dumps out module to
folder
withmodule_name
so that it can be imported withfrom <folder> import <module_name>
- Parameters
folder (Union[str, os.PathLike]) – The folder to write the code out to
module_name (str) – Top-level name to use for the
Module
while writing out the code
-
-
class
torch.fx.
Graph
[source]¶ Graph
is the main data structure used in the FX Intermediate Representation. It consists of a series ofNode
s, each representing callsites (or other syntactic constructs). The list ofNode
s, taken together, constitute a valid Python function.For example, the following code
import torch import torch.fx class MyModule(torch.nn.Module): def __init__(self): super().__init__() self.param = torch.nn.Parameter(torch.rand(3, 4)) self.linear = torch.nn.Linear(4, 5) def forward(self, x): return torch.topk(torch.sum(self.linear(x + self.linear.weight).relu(), dim=-1), 3) m = MyModule() gm = torch.fx.symbolic_trace(m)
Will produce the following Graph:
print(gm.graph)
graph(x): %linear_weight : [#users=1] = self.linear.weight %add_1 : [#users=1] = call_function[target=operator.add](args = (%x, %linear_weight), kwargs = {}) %linear_1 : [#users=1] = call_module[target=linear](args = (%add_1,), kwargs = {}) %relu_1 : [#users=1] = call_method[target=relu](args = (%linear_1,), kwargs = {}) %sum_1 : [#users=1] = call_function[target=torch.sum](args = (%relu_1,), kwargs = {dim: -1}) %topk_1 : [#users=1] = call_function[target=torch.topk](args = (%sum_1, 3), kwargs = {}) return topk_1
For the semantics of operations represented in the
Graph
, please seeNode
.-
call_function
(the_function, args=None, kwargs=None, type_expr=None)[source]¶ Insert a
call_function
Node
into theGraph
. Acall_function
node represents a call to a Python callable, specified bythe_function
.the_function
can be- Parameters
the_function (Callable[.., Any]) – The function to be called. Can be any PyTorch operator, Python function, or member of the
builtins
oroperator
namespaces.args (Optional[Tuple[Argument, ..]]) – The positional arguments to be passed to the called function.
kwargs (Optional[Dict[str, Argument]]) – The keyword arguments to be passed to the called function
type_expr (Optional[Any]) – an optional type annotation representing the Python type the output of this node will have.
Returns
The newly created and inserted
call_function
node.Note
The same insertion point and type expression rules apply for this method as
Graph.create_node()
.
-
call_method
(method_name, args=None, kwargs=None, type_expr=None)[source]¶ Insert a
call_method
Node
into theGraph
. Acall_method
node represents a call to a given method on the 0th element ofargs
.- Parameters
method_name (str) – The name of the method to apply to the self argument. For example, if args[0] is a
Node
representing aTensor
, then to callrelu()
on thatTensor
, passrelu
tomethod_name
.args (Optional[Tuple[Argument, ..]]) – The positional arguments to be passed to the called method. Note that this should include a
self
argument.kwargs (Optional[Dict[str, Argument]]) – The keyword arguments to be passed to the called method
type_expr (Optional[Any]) – an optional type annotation representing the Python type the output of this node will have.
- Returns
The newly created and inserted
call_method
node.
Note
The same insertion point and type expression rules apply for this method as
Graph.create_node()
.
-
call_module
(module_name, args=None, kwargs=None, type_expr=None)[source]¶ Insert a
call_module
Node
into theGraph
. Acall_module
node represents a call to the forward() function of aModule
in theModule
hierarchy.- Parameters
module_name (str) – The qualified name of the
Module
in theModule
hierarchy to be called. For example, if the tracedModule
has a submodule namedfoo
, which has a submodule namedbar
, the qualified namefoo.bar
should be passed asmodule_name
to call that module.args (Optional[Tuple[Argument, ..]]) – The positional arguments to be passed to the called method. Note that this should not include a
self
argument.kwargs (Optional[Dict[str, Argument]]) – The keyword arguments to be passed to the called method
type_expr (Optional[Any]) – an optional type annotation representing the Python type the output of this node will have.
- Returns
The newly-created and inserted
call_module
node.
Note
The same insertion point and type expression rules apply for this method as
Graph.create_node()
.
-
create_node
(op, target, args=None, kwargs=None, name=None, type_expr=None)[source]¶ Create a
Node
and add it to theGraph
at the current insert-point. Note that the current insert-point can be set viaGraph.inserting_before()
andGraph.inserting_after()
.- Parameters
op (str) – the opcode for this Node. One of ‘call_function’, ‘call_method’, ‘get_attr’, ‘call_module’, ‘placeholder’, or ‘output’. The semantics of these opcodes are described in the
Graph
docstring.args (Optional[Tuple[Argument, ..]]) – is a tuple of arguments to this node.
kwargs (Optional[Dict[str, Argument]]) – the kwargs of this Node
name (Optional[str]) – an optional string name for the
Node
. This will influence the name of the value assigned to in the Python generated code.type_expr (Optional[Any]) – an optional type annotation representing the Python type the output of this node will have.
- Returns
The newly-created and inserted node.
-
erase_node
(to_erase)[source]¶ Erases a
Node
from theGraph
. Throws an exception if there are still users of that node in theGraph
.- Parameters
to_erase (Node) – The
Node
to erase from theGraph
.
-
get_attr
(qualified_name, type_expr=None)[source]¶ Insert a
get_attr
node into the Graph. Aget_attr
Node
represents the fetch of an attribute from theModule
hierarchy.- Parameters
qualified_name (str) – the fully-qualified name of the attribute to be retrieved. For example, if the traced Module has a submodule named
foo
, which has a submodule namedbar
, which has an attribute namedbaz
, the qualified namefoo.bar.baz
should be passed asqualified_name
.type_expr (Optional[Any]) – an optional type annotation representing the Python type the output of this node will have.
- Returns
The newly-created and inserted
get_attr
node.
Note
The same insertion point and type expression rules apply for this method as
Graph.create_node
.
-
graph_copy
(g, val_map)[source]¶ Copy all nodes from a given graph into
self
.- Parameters
- Returns
The value in
self
that is now equivalent to the output value ing
, ifg
had anoutput
node.None
otherwise.
-
inserting_after
(n=None)[source]¶ Set the point at which create_node and companion methods will insert into the graph. When used within a ‘with’ statement, this will temporary set the insert point and then restore it when the with statement exits:
with g.inserting_after(n): ... # inserting after node n ... # insert point restored to what it was previously g.inserting_after(n) # set the insert point permanently
- Parameters
n (Optional[Node]) – The node before which to insert. If None this will insert after the beginning of the entire graph.
- Returns
A resource manager that will restore the insert point on
__exit__
.
-
inserting_before
(n=None)[source]¶ Set the point at which create_node and companion methods will insert into the graph. When used within a ‘with’ statement, this will temporary set the insert point and then restore it when the with statement exits:
with g.inserting_before(n): ... # inserting before node n ... # insert point restored to what it was previously g.inserting_before(n) # set the insert point permanently
- Parameters
n (Optional[Node]) – The node before which to insert. If None this will insert before the beginning of the entire graph.
- Returns
A resource manager that will restore the insert point on
__exit__
.
-
lint
(root=None)[source]¶ Runs various checks on this Graph to make sure it is well-formed. In particular: - Checks Nodes have correct ownership (owned by this graph) - Checks Nodes appear in topological order - If
root
is provided, checks that targets exist inroot
- Parameters
root (Optional[torch.nn.Module]) – The root module with which to check for targets. This is equivalent to the
root
argument that is passed when constructing aGraphModule
.
-
node_copy
(node, arg_transform=<function Graph.<lambda>>)[source]¶ Copy a node from one graph into another.
arg_transform
needs to transform arguments from the graph of node to the graph of self. Example:# Copying all the nodes in `g` into `new_graph` g : torch.fx.Graph = ... new_graph = torch.fx.graph() value_remap = {} for node in g.nodes: value_remap[node] = new_graph.node_copy(node, lambda n : value_remap[n])
- Parameters
node (Node) – The node to copy into
self
.arg_transform (Callable[[Node], Argument]) – A function that transforms
Node
arguments in node’sargs
andkwargs
into the equivalent argument inself
. In the simplest case, this should retrieve a value out of a table mapping Nodes in the original graph toself
.
-
property
nodes
¶ Get the list of Nodes that constitute this Graph.
Note that this
Node
list representation is a doubly-linked list. Mutations during iteration (e.g. delete a Node, add a Node) are safe.- Returns
A doubly-linked list of Nodes. Note that
reversed
can be called on this list to switch iteration order.
-
output
(result, type_expr=None)[source]¶ Insert an
output
Node
into theGraph
. Anoutput
node represents areturn
statement in Python code.result
is the value that should be returned.- Parameters
result (Argument) – The value to be returned.
type_expr (Optional[Any]) – an optional type annotation representing the Python type the output of this node will have.
Note
The same insertion point and type expression rules apply for this method as
Graph.create_node
.
-
placeholder
(name, type_expr=None)[source]¶ Insert a
placeholder
node into the Graph. Aplaceholder
represents a function input.- Parameters
name (str) – A name for the input value. This corresponds to the name of the positional argument to the function this
Graph
represents.type_expr (Optional[Any]) – an optional type annotation representing the Python type the output of this node will have. This is needed in some cases for proper code generation (e.g. when the function is used subsequently in TorchScript compilation).
Note
The same insertion point and type expression rules apply for this method as
Graph.create_node
.
-
-
class
torch.fx.
Node
(graph, name, op, target, args, kwargs, type=None)[source]¶ Node
is the data structure that represents individual operations within aGraph
. For the most part, Nodes represent callsites to various entities, such as operators, methods, and Modules (some exceptions include nodes that specify function inputs and outputs). EachNode
has a function specified by itsop
property. TheNode
semantics for each value ofop
are as follows:placeholder
represents a function input. Thename
attribute specifies the name this value will take on.target
is similarly the name of the argument.args
holds either: 1) nothing, or 2) a single argument denoting the default parameter of the function input.kwargs
is don’t-care. Placeholders correspond to the function parameters (e.g.x
) in the graph printout.get_attr
retrieves a parameter from the module hierarchy.name
is similarly the name the result of the fetch is assigned to.target
is the fully-qualified name of the parameter’s position in the module hierarchy.args
andkwargs
are don’t-carecall_function
applies a free function to some values.name
is similarly the name of the value to assign to.target
is the function to be applied.args
andkwargs
represent the arguments to the function, following the Python calling conventioncall_module
applies a module in the module hierarchy’sforward()
method to given arguments.name
is as previous.target
is the fully-qualified name of the module in the module hierarchy to call.args
andkwargs
represent the arguments to invoke the module on, including the self argument.call_method
calls a method on a value.name
is as similar.target
is the string name of the method to apply to theself
argument.args
andkwargs
represent the arguments to invoke the module on, including the self argumentoutput
contains the output of the traced function in itsargs[0]
attribute. This corresponds to the “return” statement in the Graph printout.
-
property
all_input_nodes
¶ Return all Nodes that are inputs to this Node. This is equivalent to iterating over
args
andkwargs
and only collecting the values that are Nodes.- Returns
List of
Nodes
that appear in theargs
andkwargs
of thisNode
, in that order.
-
append
(x)[source]¶ Insert x after this node in the list of nodes in the graph. Equvalent to
self.next.prepend(x)
- Parameters
x (Node) – The node to put after this node. Must be a member of the same graph.
-
property
args
¶ The tuple of arguments to this
Node
. The interpretation of arguments depends on the node’s opcode. See theNode
docstring for more information.Assignment to this property is allowed. All accounting of uses and users is updated automatically on assignment.
-
property
kwargs
¶ The dict of keyword arguments to this
Node
. The interpretation of arguments depends on the node’s opcode. See theNode
docstring for more information.Assignment to this property is allowed. All accounting of uses and users is updated automatically on assignment.
-
property
next
¶ Returns the next
Node
in the linked list of Nodes.- Returns
The next
Node
in the linked list of Nodes.
-
prepend
(x)[source]¶ Insert x before this node in the list of nodes in the graph. Example:
Before: p -> self bx -> x -> ax After: p -> x -> self bx -> ax
- Parameters
x (Node) – The node to put before this node. Must be a member of the same graph.
-
property
prev
¶ Returns the previous
Node
in the linked list of Nodes.- Returns
The previous
Node
in the linked list of Nodes.
-
class
torch.fx.
Tracer
[source]¶ Tracer
is the class that implements the symbolic tracing functionality oftorch.fx.symbolic_trace
. A call tosymbolic_trace(m)
is equivalent toTracer().trace(m)
.Tracer can be subclassed to override various behaviors of the tracing process. The different behaviors that can be overridden are described in the docstrings of the methods on this class.
-
call_module
(m, forward, args, kwargs)[source]¶ Method that specifies the behavior of this
Tracer
when it encounters a call to annn.Module
instance.By default, the behavior is to check if the called module is a leaf module via
is_leaf_module
. If it is, emit acall_module
node referring tom
in theGraph
. Otherwise, call theModule
normally, tracing through the operations in itsforward
function.This method can be overridden to–for example–create nested traced GraphModules, or any other behavior you would want while tracing across
Module
boundaries.Module
boundaries.- Parameters
m (Module) – The module for which a call is being emitted
forward (Callable) – The forward() method of the
Module
to be invokedargs (Tuple) – args of the module callsite
kwargs (Dict) – kwargs of the module callsite
- Returns
The return value from the Module call. In the case that a
call_module
node was emitted, this is aProxy
value. Otherwise, it is whatever value was returned from theModule
invocation.
-
create_arg
(a)[source]¶ A method to specify the behavior of tracing when preparing values to be used as arguments to nodes in the
Graph
.By default, the behavior includes:
Iterate through collection types (e.g. tuple, list, dict) and recursively call
create_args
on the elements.Given a Proxy object, return a reference to the underlying IR
Node
Given a non-Proxy Tensor object, emit IR for various cases:
For a Parameter, emit a
get_attr
node referring to that ParameterFor a non-Parameter Tensor, store the Tensor away in a special attribute referring to that attribute.
This method can be overridden to support more types.
- Parameters
a (Any) – The value to be emitted as an
Argument
in theGraph
.- Returns
The value
a
converted into the appropriateArgument
-
create_args_for_root
(root_fn, is_module)[source]¶ Create
placeholder
nodes corresponding to the signature of theroot
Module. This method introspects root’s signature and emits those nodes accordingly, also supporting*args
and**kwargs
.
-
is_leaf_module
(m, module_qualified_name)[source]¶ A method to specify whether a given
nn.Module
is a “leaf” module.Leaf modules are the atomic units that appear in the IR, referenced by
call_module
calls. By default, Modules in the PyTorch standard library namespace (torch.nn) are leaf modules. All other modules are traced through and their constituent ops are recorded, unless specified otherwise via this parameter.- Parameters
-
path_of_module
(mod)[source]¶ Helper method to find the qualified name of
mod
in the Module hierarchy ofroot
. For example, ifroot
has a submodule namedfoo
, which has a submodule namedbar
, passingbar
into this function will return the string “foo.bar”.- Parameters
mod (str) – The
Module
to retrieve the qualified name for.
-
trace
(root)[source]¶ Trace
root
and return the corresponding FXGraph
representation.root
can either be annn.Module
instance or a Python callable.- Parameters
root (Union[Module, Callable]) – Either a
Module
or a function to be traced through.- Returns
A
Graph
representing the semantics of the passed-inroot
.
-
-
class
torch.fx.
Proxy
(node, tracer=None)[source]¶ Proxy
objects areNode
wrappers that flow through the program during symbolic tracing and record all the operations (torch
function calls, method calls, operators) that they touch into the growing FX Graph.If you’re doing graph transforms, you can wrap your own
Proxy
method around a rawNode
so that you can use the overloaded operators to add additional things to aGraph
.


Show Setup?
Setup
Hide Setup
Config Players
Export Setup
Dudes (csv NO SPACES between players):
Gals (csv):
Update Order
start voices
next
pause
resume
restart song
nice play
good eye
Say it
we are the champions
Now Playing:
ugh


article 1 article 1 article 1 article 1 article 1 ...
article 2 article 2 article 2 article 2 article 2 ...


Webpack Starter Template
Getting Started
This website skeleton is build based on npm and Webpack. Modules are installed thrugh npm and later on all files are compiled through Webpack. I decided to keep the html files minimal and focused on making it flexible and
Prerequisites
Before you install this template, you will need node and npm installed on your machine
Installing
In order to install the template, you have to navigate to the root of the project's folder in your terminal and then run:
npm install
At this point, npm should install all modules necessary to run this example. You can add/remove modules in the package.js file.
How this template works
Thanks to the use of Webpack and npm modules, there are lots of features you might want to incorporate into your web workflow:
- Development folder for building your app- /src
- Production folder for compiling the app- /dist
- Minification plugins to make your html/css/js files minified.
- Code documentation with JSDoc module.- /docs
- Jquery already included.
- Bootstrap included.
- Mustache.js enabled.
- Dist and Docs folders rebuild every time you run prod script
Development
Development enviroment can be run by:
npm run dev
Once app compiles, you will be able to access the code by going to http://localhost:8080 in your browser.This command uses webpack-dev-server and doesn't write any new files to the disk. While webpack-dev-server runs, you can modify your css/js and html files. Localhost website you're working on will be refreshed every time you save your progress.
Deployment
Deployment is as easy as running npm run dev command in your terminal window.
npm run dev
Once the code compiles, all files will be stored in the distribution /dist folder. Javascript will be bundled into one file and minified. SCSS files will be converted to CSS, combined and minified as well. HTML files will be minified. Separate /img and /font folders will be added. Alongside adding the /dist folder, Webpack will run JSDoc plugin and create /docs folder with updated documentation for javascript. Also, this README file will be added to the front page of the documentation.
Packages and Modules
The goal of this template was to automate as many tedious "behind the scene" processes as possible. In order to understand development and deployment processes, take a look at project.json and webpack.config.js.
Authors
- (Michal Lichwa)[http://michallichwa.com]
License
This project is licensed under the MIT License - see the LICENSE.md file for details
Acknowledgments
- I used Academind Webpack Tutorial while creating this template.


August 30
But the fruit of the Spirit is love, joy, peace, longsuffering, gentleness, goodness, faith, meekness, temperance: against such there is no law. Galatians 5:22-23
So many believers think of the fruit of the Spirit as little more than a passive list of pleasant qualities that can help improve their personalities. But they're far greater than that! They're pure spiritual power.
Love is so powerful, the scripture says, that it never fails. Patience is so powerful it cannot be stopped. No matter what the circumstances, it will not quit.
The fruits of the Spirit are not weak; they're strong. So strong all the demons of hell can't stop them. So strong that if you'll let them flow out of you, they'll correct the problems in your life. They'll keep you steadfast when all the people around you are falling down. They'll keep you on your feet when governments fail and when the storms of life come.
We are living in dangerous days. There's only one way you can make it through in victory. You must begin to release those powerful fruits of the Spirit God has placed inside you. Believe me, if you're born again, they are there. Learn to yield to them and as 2 Peter 1:10 promised, you shall never fall!
Scripture Reading: 2 Peter 1:1-10


WITNESS LIST Education Committee April 4, 2001 - 9:00A HB 1212 Registering, but not testifying: On: Miller, Roger (Texas State Teachers Association), Austin, TX HB 1753 FOR: Casso, Dr. Ramiro Vice President (South Texas Community College), Mc Allen, TX ON: Arevalo, Rodolfo University Administrator (University of Texas Pan American), Edinburg, TX Flack, Teri Deputy Commissioner (Texas Higher Education Coordinating Board), Austin, TX Providing written testimony: For: Tupper, Ron Assoc. Professor and Director (Texas A&M University Health Science Center), Mc Allen, TX SB 641 Registering, but not testifying: On: Brown, Martha Governmental Relations (Texas Tech University System), Lubbock, TX Cole, Jeff (State Comptroller's Office), Austin, TX SB 724 FOR: Rostellini, David Business Manager (New Braunfels I.S.D.), New Braunfels, TX Registering, but not testifying: For: Biggadike, Bill (New Braunfels I.S.D.), New Braunfels, TX Reaves, Ron Superintendent (New Braunfels I.S.D.), New Braunfels, TX Spain, Bette (New Braunfels I.S.D. School Board), New Braunfels, TX SB 752 FOR: Dukes, Dawnna State Representative (Self), Austin, TX Forgione, Dr. Pat Superintendent (Austin I.S.D.), Austin, TX Gohl, Daniel Educational Administrator (Austin I.S.D.), Austin, TX AGAINST: Bender, Betsy Hall (Self), Austin, TX Cox, Deborah Parent (Self), Austin, TX McDougal, Marty Parent (Austin Magnet Parents), Austin, TX McLeroy, Jamie Attorney (Self), Austin, TX Pigman, Kathryn (Self), Austin, TX Roeder, Patrick Architect (Friends of the Liberal Arts Academy, Johnson High School), Austin, TX Solis, Maria (Self), Austin, TX Tulis, Jeffrey Professor (Friends of Liberal Arts Academy, Johnson High School), Austin, TX Walter, Philip Human Resources (Self), Austin, TX Registering, but not testifying: For: De Leon, Marty Lobbyist (Texas Association of School Boards), Austin, TX Duty, David Administration (Austin I.S.D.), Austin, TX Flores, Steve Governmental Relations (Texas Association of School Administrators), Austin, TX Against: Solis, Erica Student (Self), Austin, TX SB 914 FOR: Cryan, Charles Director of Fiscal Services (City of College Station), College Station, TX Winn, Gerald Buddy Tax Assessor - Collector (City of College Station and Brazos County), College Station, TX AGAINST: Bradley, Scott Attorney (Mayor of Westlake), Westlake, TX Frame, Kellie Student (Texas Student Housing Corporation), College Station, TX Moffett, Jimmy Student (Texas Student Housing Corporation), College Station, TX Petty, Trent Town Manager (Town of Westlake), Westlake, TX Simmons, Emily Student (Texas Student Housing Corporation), College Station, TX ON: Holtz, Cynthia homemaker (Texas Student Housing Scholarship), Southlake, TX McDonald, Carol Association Executive (Independent Colleges and Universities of Texas, Inc.), Austin, TX Renken, Jennifer EMT and Student (Texas Student Housing Scholarship Students), Bryan, TX Registering, but not testifying: Against: Arnett, Keith (Self), Keller, TX Carter, Jim County Commissioner (Texas Student Housing), Fort Worth, TX Weber III, Carl Student, Texas A&M (Texas Student Housing Corporation), College Station, TX Whitley, Glen Tarrat County Commissioner (Tarrant County), Hurst, TX On: Dempsey, Denise Texas A&M University student (Texas Student Housing Corporation), College Station, TX Holtz, Bryan Student (Cit of Westlake/Texas Student Housing Corporation), College Station, TX Thomasson, James Assistant Attorney General (Office of the Attorney General), Austin, TX SB 1102 FOR: Lara, Rene Legislative Liaison (Texas Federation of Teachers), Austin, TX Ramos, Vincent Executive Director (TX LULAC), Austin, TX ON: Romero, Anna Alicia Education Assistant (Intercultural Development Research Association), San Antonio, TX Registering, but not testifying: For: Escobar, Felicia Policy Analyst (National Council of La Raza), Austin, TX SB 1155 Registering, but not testifying: For: Scott, Randolph Associate Dean for Management (University of Texas Health Science Center at Houston), Houston, TX SB 1180 FOR: Carpenter, Bill Governmental Relations (Houston I.S.D.), Houston, TX SB 1190 FOR: Armstrong, Anne (Texas A&M University System), Kingsville, TX Nance, David CEO (Introgen Therapeutics, Inc.), Austin, TX ON: Guckian, Dr. James Vice Chancellor Health Affairs (University of Texas System), Austin, TX Young, Terry Executive Director, Tech. Licensing Ofc. (Texas A&M University System), College Station, TX Registering, but not testifying: For: Kessler, Ron Attorney (American Electronic Association), Austin, TX Kowalski, Tom (Texas Healthcare and Bioscience Institute), Austin, TX SB 1260 ON: Ressel, Betty Manager, TX School Performance Review (Comptroller of Public Accounts), Austin, TX SB 1472 Registering, but not testifying: On: Jackson, Frank Special Asst. to President (Prarie View A&M University), Prairie View, TX SB 1543 ON: Nelson, Jim Commissioner of Education (Texas Education Agency), Austin, TX Registering, but not testifying: For: De Leon, Marty Asst. Director (Texas Association of School Boards), Austin, TX Flores, Steve Governmental Relations (Texas Association of School Administrators), Austin, TX Smith, Lauren (Association of Texas Professional Educators), Austin, TX SB 1735 FOR: Hollingsworth, Lonnie Attorney (TCTA), Austin, TX Registering, but not testifying: On: Anderson, David Lawyer (Texas Education Agency), Austin, TX Lenz, Gene Division Director (Texas Education Agency), Austin, TX SB 1785 FOR: Hagood, Walt Farmer (Friendship I.S.D. Board Member), Wolfforth, TX Hinojosa, Michael Superintendent (Fast Growth School Coalition), Austin, TX Registering, but not testifying: For: Carpenter, Bill (Texas School Alliance), Houston, TX Casey, Daniel Partner; Moak, Casey and Assoc. (Fast Growth School Coalition), Austin, TX Dunn, David Director of Governmental Relations (Texas Association of School Boards), Austin, TX Flores, Steve Governmental Relations (Texas Association of School Administrators), Austin, TX Thomas, John Superintendent (Friendship I.S.D.), Wolfforth, TX


---
layout: page
title: Xu Li (李旭)
subtitle: Ph.D. in Speech Processing
use-site-title: true
---
Biography
Xu Li is currently a senior researcher at Tencent ARC Lab, working on speech processing and machine learning.
He obtained the Ph.D. degree in Department of Systems Engineering & Engineering Management at The Chinese University of Hong Kong (CUHK), advised by Prof. Helen Meng.
Before that, he obtained the B.E. degree in Information Science and Technology at University of Science and Technology of China in 2017.
The Chinese University of Hong Kong, August 2017 - July 2021
Ph.D. in Dept. of Systems Engineering and Engineering Management
University of Science and Technology of China, July 2013 - June 2017
B.E. in Dept. of Information Science and Technology
Research Interests
Speech Synthesis and Voice Conversion
Speaker Recognition and Voiceprint Anti-Spoofing Countermeasures
Mispronunciation Detection and Diagnosis
Machine Learning Algorithms
Journal Papers
Improving the Adversarial Robustness for Speaker Verification by Self-Supervised Learning
Xu Li*, Haibin Wu*, Andy T. Liu, Zhiyong Wu, Helen Meng and Hung-yi Lee
in IEEE/ACM Transactions on Audio Speech and Language Processing, 2021
Automatic Lexical Stress and Pitch Accent Detection for L2 English Speech using Multi-distribution Deep Neural Networks
Kun Li, Shaoguang Mao, Xu Li, Zhiyong Wu, Helen Meng
in Speech Communication, 2018
Conference Papers
A Hierarchical Speaker Representation Framework for One-shot Singing Voice Conversion
Xu Li, Shansong Liu and Ying Shan
in the Proceedings of Interspeech, 2022
Channel-wise Gated Res2Net: Towards Robust Detection of Synthetic Speech Attacks
Xu Li, Xixin Wu, Hui Lu, Xunying Liu and Helen Meng
in the Proceedings of Interspeech, 2021
[Code]
Replay and Synthetic Speech Detection with Res2Net Architecture
Xu Li, Na Li, Chao Weng, Xunying Liu, Dan Su, Dong Yu and Helen Meng
in IEEE ICASSP, 2021
[Code]
Adversarial Defense for Automatic Speaker Verification by Cascaded Self-supervised Learning Models
Xu Li*, Haibin Wu*, Andy T. Liu, Zhiyong Wu, Helen Meng and Hung-yi Lee
in IEEE ICASSP, 2021
Investigating Robustness of Adversarial Samples Detection for Automatic Speaker Verification
Xu Li, Na Li, Jinghua Zhong, Xixin Wu, Xunying Liu, Dan Su, Dong Yu and Helen Meng
in the Proceedings of Interspeech, 2020
Adversarial Attacks on GMM i-vector based Speaker Verification Systems
Xu Li, Jinghua Zhong, Xixin Wu, Jianwei Yu, Xunying Liu and Helen Meng
in IEEE ICASSP, 2020
[Code],
[Demo]
Bayesian x-vector: Bayesian Neural Network based x-vector System for Speaker Verification
Xu Li, Jinghua Zhong, Jianwei Yu, Shoukang Hu, Xixin Wu, Xunying Liu and Helen Meng
in Speaker Odyssey, 2020
Unsupervised Discovery of Non-native Phonetic Patterns in L2 English Speech for Mispronunciation Detection and Diagnosis
Xu Li, Shaoguang Mao, Xixin Wu, Kun Li, Xunying Liu and Helen Meng
in the Proceedings of Interspeech, 2018
Preprints
Deep Segmental Phonetic Posterior-grams based Discovery of Non-categories in L2 English Speech
Xu Li, Xixin Wu, Xunying Liu and Helen Meng
arXiv preprint arXiv:2002.00205 (2020)
[Demo]
Professional Activities
Journal Reviewer of Transactions on Audio, Speech, and Language Processing; IEEE Transactions on Human-Machine Systems; Journal of Intelligent & Fuzzy Systems
Conference Reviewer of ICME 2019; Interspeech 2020; APSIPA ASC 2019, 2020 and 2021; ICASSP 2022
Concat Info: xuliustc1306 [at] gmail.com
Last Updated: Aug. 2nd, 2022


Add Income/Expenses
Amount
Date
Description
Income
Expense
Add
Income Statement
Amount
Date
Description
Edit
Delete
Expense Statement
Amount
Date
Description
Edit
Delete


Apache Netbeans 11 2 Features
Downloading Apache Netbeans Incubating 11 0
Apache Netbeans Incubating 11 0 Features
Apache Netbeans Download 2021 Latest For Windows 10 8 7
Jdk 13 Text Block In Apache Netbeans 11 2 Youtube
Apache Netbeans 11 2 Released
Getting Started With The Apache Netbeans Platform Apache Netbeans
Apache Netbeans 12 0 Features
Apache Netbeans 12 1 Releases Integrated Development Environment For Java Infotech News
Apache Netbeans 11 3 Features
Apache Netbeans Download Free For Windows Latest Update 2020
Apache Netbeans For Mac Download Free 2021 Latest Version
Download Apache Netbeans Ide 12 3
Apache Netbeans 11 2 Ide 8 2 0 Win Image By Anymdaft
Apache Netbeans Incubating 9 0 Features
Apply Dark Theme On Apache Netbeans 11 1 Youtube
2rz1piorgeun M
Netbeans 12 3 Free Download Linux Icewalkers
Apache Netbeans Ide 11 3 Free Download Freewarefiles Com Programming Category
Apache Netbeans 11 2 Crack Patch And Serial Key Free
Apache Netbeans 11 3 Jdk 14 Preview Features Dark Mode Jaxenter
Nb Springboot Netbeans Plugin Detail
Netbeans 11 Page 1 Line 17qq Com
Apache Netbeans 11 1 Payara Java Ee 8 Youtube
Install Apache Netbeans For Linux Using The Snap Store Snapcraft


Up: Introduction to MPI
Next: MPI Terms and Conventions
Previous: What Is Not Included In The Standard?
The following is a list of the remaining chapters in this document, along with
a brief description of each.
- Chapter MPI Terms and Conventions
, MPI Terms and Conventions,
explains notational terms and conventions used
throughout the MPI document.
- Chapter Point-to-Point Communication
, Point to Point Communication,
defines the basic, pairwise communication subset of MPI. send
and receive are found here, along with many associated functions
designed to make basic communication powerful and efficient.
- Chapter Collective Communication
, Collective Communications, defines
process-group collective communication operations. Well known
examples of this are barrier and broadcast over a group of processes (not
necessarily all the processes).
- Chapter Groups, Contexts, and Communicators
, Groups, Contexts, and Communicators,
shows how groups of processes are formed and manipulated, how unique
communication contexts are obtained, and how the two are bound together
into a communicator.
- Chapter Process Topologies
, Process Topologies, explains a set
of utility functions meant to assist in the mapping of process
groups (a linearly ordered set) to richer topological structures
such as multi-dimensional grids.
- Chapter MPI Environmental Management
, MPI Environmental Management, explains
how the programmer can manage and make inquiries of the current MPI environment.
These functions are needed for the writing of correct, robust programs,
and are especially important for the construction of highly-portable
message-passing programs.
- Chapter Profiling Interface
, Profiling Interface, explains a simple
name-shifting convention that any MPI implementation must support.
One motivation for this is the ability to put performance profiling
calls into MPI without the need for access to the MPI source code. The
name shift is merely an interface, it says nothing about how the actual
profiling should be done and in fact, the name shift can
be useful for other purposes.
- Annex Language Binding
, Language Bindings,
gives specific syntax in Fortran 77 and C, for all MPI functions,
constants, and types.
- The MPI Function Index is a simple index showing the location of
the precise definition of each MPI function, together with both C and
Fortran bindings.
Up: Introduction to MPI
Next: MPI Terms and Conventions
Previous: What Is Not Included In The Standard?
Return to MPI 1.1 Standard Index
Return to MPI-2 Standard Index
Return to MPI Forum Home Page
MPI-1.1 of June 12, 1995
HTML Generated on August 6, 1997


--- layout: archive title: Zulip Chat Archive permalink: /stream/113489-new-members/topic/Rec_on.20arguments.html ---
I'm confused about the behavior of rec_on
. Specifically, in the example below, I'm trying to prove something is true for both instances of my inductive definition mult_3
, which only has two cases, but I'm getting three new goal states. In term mode, I understand that rec_on
takes in three args, but isn't the goal state here the "first" of those three? The first goal I get when I do this looks identical to the original goal state as well, which doesn't seem right.
import data.nat.basic import data.set open nat inductive mult_3 : set ℕ | mult_3_O : mult_3 0 | mult_3_SSS : ∀ n, mult_3 n → mult_3 (n + 3) example (n k : ℕ) : n = 3*k → mult_3 n := begin intro h, cases h with k hk, apply mult_3.rec_on, end
don't use rec_on
in tactic mode. Instead, use induction
if you want to keep the orders of the arguments when using apply
, use fapply
also try minimize the number of lines by using apply mult_3.rec_on hk
instead
but preferably use induction hk
It seems like induction
defaults to the type of the variable I apply it to. Is there a way to tell induction
that I want it to work on the cases of mult_3
instead of the cases of nat
, even though everything in hk
is a nat
?
If you have some hyp : mult_3 n
then induction hyp
should perform structural induction on mult_3
instead of ordinary induction on n
.
it looks like I misread the whole thing. The instance of mult_3
is in your goal, not your hypothesis.
so 1. mult_3.rec_on
will never work because it is used for destructing an instance of mult_3
in your hypothesis, and 2. you should induct on k
instead
Donald Sebastian Leung said:
If you have some
hyp : mult_3 n
theninduction hyp
should perform structural induction onmult_3
instead of ordinary induction onn
.
Interesting. That makes sense, and seems to be working for me, but it feels weird to have to make something of that type just to tell induction to act on it.
Kenny Lau said:
it looks like I misread the whole thing. The instance of
mult_3
is in your goal, not your hypothesis.
Yeah I'm trying to show mult_3 n
.
Kenny Lau said:
so 1.
mult_3.rec_on
will never work because it is used for destructing an instance ofmult_3
in your hypothesis, and 2. you should induct onk
instead
I tried inducting on k and got stuck here. My thinking was that this was tricky because I should have been exploiting the structure of mult_3 more directly, but maybe there's a way forward I'm not seeing?
example (n k : ℕ) : n = 3*k → mult_3 n := begin intro h, induction k with l hl, rw mul_zero at h, rw h, apply mult_3.mult_3_O, rw succ_eq_add_one at h, end
Edit: copied the wrong code initially and had to modify.
This is no good -- your induction hypothesis is useless.
You need to do induction before the intro. You need to think carefully about precisely which statement you need to prove by induction.
actually, rewrite, and then induct on k
to prove mult_3 (3 * k)
Even better.
Kenny Lau said:
actually, rewrite, and then induct on
k
to provemult_3 (3 * k)
This seems a lot better but I'm still getting stuck at the end with my index off by one.
example (n k : ℕ) : n = 3*k → mult_3 n := begin intro h, rw h, induction k with l hl, rw mul_zero, apply mult_3.mult_3_O, rw succ_eq_add_one, rw succ_eq_add_one at h, rw mul_add at h, rw mul_one at h, rw mul_add, apply mult_3.mult_3_SSS, apply hl, end
you need to delete hypothesis h
before the induction, or else it will get automatically pulled into the induction hypothesis making it useless
alternatively you can use induction k with l hl generalizing n
, but the variable n
is already useless by that point so there is no reason to
The formalisation of the question itself is bad
n plays no role and is now screwing you up
Just prove mult_3 (3*k) and drop the n
You don't want a function which demands n as an input and then immediately demands a proof that it's equal to something else
Kevin Buzzard said:
Just prove mult_3 (3*k) and drop the n
So the larger proof I'm trying to write uses def div3 (n:ℕ) := ∃ (k : ℕ), n = 3*k
, and the question would be stated as div n \r mult_3 n
but I felt like that would have cluttered this example. I agree this formalism is bad.
You can do the small amount of logical glue to connect mult_3 (3*k)
to 3 \| n -> mult_3 n
in the proof of the latter
This is how I was ultimately able to do it. I kept get stuck not generalizing my n properly at the end with the induction on k, but induction on hyp : mult_3 n
worked. Maybe I'm missing something.
import data.nat.basic import data.set open nat inductive mult_3 : set ℕ | mult_3_O : mult_3 0 | mult_3_SSS : ∀ n, mult_3 n → mult_3 (n + 3) def div3 (n:ℕ) := ∃ (k : ℕ), n = 3*k lemma p0 : mult_3 0 := mult_3.mult_3_O lemma div3_imp_p (n:ℕ) {hyp : mult_3 n}: div3 n → mult_3 n := begin rw div3, induction hyp, intro h, exact p0, intro h, apply mult_3.mult_3_SSS, exact hyp_a, end
The statement of div3_imp_p
is nonsense; you can prove it by exact hyp
on the first line
you've assumed what you wanted to prove
This is a totally unfair proof since you probably haven't seen most of these tricks but fwiw
lemma div3_imp_p (n:ℕ) : div3 n → mult_3 n := begin rintro ⟨k, rfl⟩, induction k; constructor, assumption, end
or the one liner version
lemma div3_imp_p : ∀ {n}, div3 n → mult_3 n | _ ⟨k, rfl⟩ := by induction k; constructor; assumption
Cool! Yeah I'm not too familiar with most of those tactics so I'll read up some more.
Here is the same proof but being more explicit about the changes
lemma div3_imp_p {n} (h : div3 n) : mult_3 n := begin unfold div3 at h, cases h with k e, subst e, induction k with k IH, { rw mul_zero, exact mult_3.mult_3_O }, { change 3 * succ k with 3 * k + 3, apply mult_3.mult_3_SSS, exact IH } end
The unfold
, rw mul_zero
and change
steps are optional because they make definitionally equal changes to the goal
@Mario Carneiro feel free to post your short solutions here
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


wod_build
Syntax
[wod] = wod_build(wod_dir,variable_list)
Description
wod_build(wod_dir,variable_list)
loads profiles in path wod_dir
into the struct wod
with all variables specified in variable_list
. Variables lon, lat, date, z are included automatically.
wod_dir
is a character array search path with wildcards. The search path should be the path to the netcdf files themselves, not their directory.
wod
is a uniform struct containing data from profiles in the path. Some data is included automatically while some must be specified. The variables lon, lat, date, and z are included automatically. Additional variables must be specified in variable_list
, a cell array where each element is the string name of a variable.
Example 1
% wod_build
% Get variable information:
wod_dir = '/Users/lnferris/Documents/GitHub/ocean_data_tools/data/wod/*.nc'; % included
listing = dir(wod_dir));
ncdisp([listing(1).folder '/' listing(1).name]) % Peek at netCDF header info to inform choice of variable_list.
% Load data in path:
variable_list = {'Temperature','Salinity'}; % Variables to read (besides lon, lat, date, z).
[wod] = wod_build(wod_dir,variable_list);
% Plot profiles:
general_profiles(wod,'Temperature','depth')