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Text Generation is a task in Natural Language Processing (NLP) in which text is generated with some constraints such as initial characters or initial words. We come across this task in our day-to-day applications such as character/word/sentence predictions while typing texts in Gmail, Google Docs, Smartphone keyboard, and chatbot. Understanding of text generation forms the base to advanced NLP tasks such as Neural Machine Translation.
Read more: https://analyticsindiamag.com/beginners-guide-to-text-generation-with-rnns/
#nlp #machine-learning #ai
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Text Generation is a task in Natural Language Processing (NLP) in which text is generated with some constraints such as initial characters or initial words. We come across this task in our day-to-day applications such as character/word/sentence predictions while typing texts in Gmail, Google Docs, Smartphone keyboard, and chatbot. Understanding of text generation forms the base to advanced NLP tasks such as Neural Machine Translation.
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This article discusses the text generation task to predict the next character given its previous characters. It employs a recurrent neural network with LSTM layers to achieve the task. The deep learning process will be carried out using TensorFlow’s Keras, a high-level API.
Let’s dive deeper into hands-on learning.
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1650870267
In the previous chapters you've learnt how to select individual elements on a web page. But there are many occasions where you need to access a child, parent or ancestor element. See the JavaScript DOM nodes chapter to understand the logical relationships between the nodes in a DOM tree.
DOM node provides several properties and methods that allow you to navigate or traverse through the tree structure of the DOM and make changes very easily. In the following section we will learn how to navigate up, down, and sideways in the DOM tree using JavaScript.
You can use the firstChild
and lastChild
properties of the DOM node to access the first and last direct child node of a node, respectively. If the node doesn't have any child element, it returns null
.
<div id="main">
<h1 id="title">My Heading</h1>
<p id="hint"><span>This is some text.</span></p>
</div>
<script>
var main = document.getElementById("main");
console.log(main.firstChild.nodeName); // Prints: #text
var hint = document.getElementById("hint");
console.log(hint.firstChild.nodeName); // Prints: SPAN
</script>
Note: The
nodeName
is a read-only property that returns the name of the current node as a string. For example, it returns the tag name for element node,#text
for text node,#comment
for comment node,#document
for document node, and so on.
If you notice the above example, the nodeName
of the first-child node of the main DIV element returns #text instead of H1. Because, whitespace such as spaces, tabs, newlines, etc. are valid characters and they form #text nodes and become a part of the DOM tree. Therefore, since the <div>
tag contains a newline before the <h1>
tag, so it will create a #text node.
To avoid the issue with firstChild
and lastChild
returning #text or #comment nodes, you could alternatively use the firstElementChild
and lastElementChild
properties to return only the first and last element node, respectively. But, it will not work in IE 9 and earlier.
<div id="main">
<h1 id="title">My Heading</h1>
<p id="hint"><span>This is some text.</span></p>
</div>
<script>
var main = document.getElementById("main");
alert(main.firstElementChild.nodeName); // Outputs: H1
main.firstElementChild.style.color = "red";
var hint = document.getElementById("hint");
alert(hint.firstElementChild.nodeName); // Outputs: SPAN
hint.firstElementChild.style.color = "blue";
</script>
Similarly, you can use the childNodes
property to access all child nodes of a given element, where the first child node is assigned index 0. Here's an example:
<div id="main">
<h1 id="title">My Heading</h1>
<p id="hint"><span>This is some text.</span></p>
</div>
<script>
var main = document.getElementById("main");
// First check that the element has child nodes
if(main.hasChildNodes()) {
var nodes = main.childNodes;
// Loop through node list and display node name
for(var i = 0; i < nodes.length; i++) {
alert(nodes[i].nodeName);
}
}
</script>
The childNodes
returns all child nodes, including non-element nodes like text and comment nodes. To get a collection of only elements, use children
property instead.
<div id="main">
<h1 id="title">My Heading</h1>
<p id="hint"><span>This is some text.</span></p>
</div>
<script>
var main = document.getElementById("main");
// First check that the element has child nodes
if(main.hasChildNodes()) {
var nodes = main.children;
// Loop through node list and display node name
for(var i = 0; i < nodes.length; i++) {
alert(nodes[i].nodeName);
}
}
</script>
1599552549
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Calyx provides a simple API for generating text with declarative recursive grammars.
gem install calyx
gem 'calyx'
The best way to get started quickly is to install the gem and run the examples locally.
Requires Roda and Rack to be available.
gem install roda
Demonstrates how to use Calyx to construct SVG graphics. Any Gradient generates a rectangle with a linear gradient of random colours.
Run as a web server and preview the output in a browser (http://localhost:9292
):
ruby examples/any_gradient.rb
Or generate SVG files via a command line pipe:
ruby examples/any_gradient > gradient1.xml
Requires the Twitter client gem and API access configured for a specific Twitter handle.
gem install twitter
Demonstrates how to use Calyx to make a minimal Twitter bot that periodically posts unique tweets. See @tiny_woodland on Twitter and the writeup here.
TWITTER_CONSUMER_KEY=XXX-XXX
TWITTER_CONSUMER_SECRET=XXX-XXX
TWITTER_ACCESS_TOKEN=XXX-XXX
TWITTER_CONSUMER_SECRET=XXX-XXX
ruby examples/tiny_woodland_bot.rb
Faker is a popular library for generating fake names and associated sample data like internet addresses, company names and locations.
This example demonstrates how to use Calyx to reproduce the same functionality using custom lists defined in a YAML configuration file.
ruby examples/faker.rb
Require the library and inherit from Calyx::Grammar
to construct a set of rules to generate a text.
require 'calyx'
class HelloWorld < Calyx::Grammar
start 'Hello world.'
end
To generate the text itself, initialize the object and call the generate
method.
hello = HelloWorld.new
hello.generate
# > "Hello world."
Obviously, this hardcoded sentence isn’t very interesting by itself. Possible variations can be added to the text by adding additional rules which provide a named set of text strings. The rule delimiter syntax ({}
) can be used to substitute the generated content of other rules.
class HelloWorld < Calyx::Grammar
start '{greeting} world.'
greeting 'Hello', 'Hi', 'Hey', 'Yo'
end
Each time #generate
runs, it evaluates the tree and randomly selects variations of rules to construct a resulting string.
hello = HelloWorld.new
hello.generate
# > "Hi world."
hello.generate
# > "Hello world."
hello.generate
# > "Yo world."
By convention, the start
rule specifies the default starting point for generating the final text. You can start from any other named rule by passing it explicitly to the generate method.
class HelloWorld < Calyx::Grammar
hello 'Hello world.'
end
hello = HelloWorld.new
hello.generate(:hello)
As an alternative to subclassing, you can also construct rules unique to an instance by passing a block when initializing the class:
hello = Calyx::Grammar.new do
start '{greeting} world.'
greeting 'Hello', 'Hi', 'Hey', 'Yo'
end
hello.generate
Basic rule substitution uses single curly brackets as delimiters for template expressions:
fruit = Calyx::Grammar.new do
start '{colour} {fruit}'
colour 'red', 'green', 'yellow'
fruit 'apple', 'pear', 'tomato'
end
6.times { fruit.generate }
# => "yellow pear"
# => "red apple"
# => "green tomato"
# => "red pear"
# => "yellow tomato"
# => "green apple"
Rules are recursive. They can be arbitrarily nested and connected to generate larger and more complex texts.
class HelloWorld < Calyx::Grammar
start '{greeting} {world_phrase}.'
greeting 'Hello', 'Hi', 'Hey', 'Yo'
world_phrase '{happy_adj} world', '{sad_adj} world', 'world'
happy_adj 'wonderful', 'amazing', 'bright', 'beautiful'
sad_adj 'cruel', 'miserable'
end
Nesting and hierarchy can be manipulated to balance consistency with novelty. The exact same word atoms can be combined in a variety of ways to produce strikingly different resulting texts.
module HelloWorld
class Sentiment < Calyx::Grammar
start '{happy_phrase}', '{sad_phrase}'
happy_phrase '{happy_greeting} {happy_adj} world.'
happy_greeting 'Hello', 'Hi', 'Hey', 'Yo'
happy_adj 'wonderful', 'amazing', 'bright', 'beautiful'
sad_phrase '{sad_greeting} {sad_adj} world.'
sad_greeting 'Goodbye', 'So long', 'Farewell'
sad_adj 'cruel', 'miserable'
end
class Mixed < Calyx::Grammar
start '{greeting} {adj} world.'
greeting 'Hello', 'Hi', 'Hey', 'Yo', 'Goodbye', 'So long', 'Farewell'
adj 'wonderful', 'amazing', 'bright', 'beautiful', 'cruel', 'miserable'
end
end
By default, the outcomes of generated rules are selected with Ruby’s built-in pseudorandom number generator (as seen in methods like Kernel.rand
and Array.sample
). To seed the random number generator, pass in an integer seed value as the first argument to the constructor:
grammar = Calyx::Grammar.new(seed: 12345) do
# rules...
end
Alternatively, you can pass a preconfigured instance of Ruby’s stdlib Random
class:
random = Random.new(12345)
grammar = Calyx::Grammar.new(rng: random) do
# rules...
end
When a random seed isn’t supplied, Time.new.to_i
is used as the default seed, which makes each run of the generator relatively unique.
Choices can be weighted so that some rules have a greater probability of expanding than others.
Weights are defined by passing a hash instead of a list of rules where the keys are strings or symbols representing the grammar rules and the values are weights.
Weights can be represented as floats, integers or ranges.
The following definitions produce an equivalent weighting of choices:
Calyx::Grammar.new do
start 'heads' => 1, 'tails' => 1
end
Calyx::Grammar.new do
start 'heads' => 0.5, 'tails' => 0.5
end
Calyx::Grammar.new do
start 'heads' => 1..5, 'tails' => 6..10
end
Calyx::Grammar.new do
start 'heads' => 50, 'tails' => 50
end
There’s a lot of interesting things you can do with this. For example, you can model the triangular distribution produced by rolling 2d6:
Calyx::Grammar.new do
start(
'2' => 1,
'3' => 2,
'4' => 3,
'5' => 4,
'6' => 5,
'7' => 6,
'8' => 5,
'9' => 4,
'10' => 3,
'11' => 2,
'12' => 1
)
end
Or reproduce Gary Gygax’s famous generation table from the original Dungeon Master’s Guide (page 171):
Calyx::Grammar.new do
start(
:empty => 0.6,
:monster => 0.1,
:monster_treasure => 0.15,
:special => 0.05,
:trick_trap => 0.05,
:treasure => 0.05
)
empty 'Empty'
monster 'Monster Only'
monster_treasure 'Monster and Treasure'
special 'Special'
trick_trap 'Trick/Trap.'
treasure 'Treasure'
end
Dot-notation is supported in template expressions, allowing you to call any available method on the String
object returned from a rule. Formatting methods can be chained arbitrarily and will execute in the same way as they would in native Ruby code.
greeting = Calyx::Grammar.new do
start '{hello.capitalize} there.', 'Why, {hello} there.'
hello 'hello', 'hi'
end
4.times { greeting.generate }
# => "Hello there."
# => "Hi there."
# => "Why, hello there."
# => "Why, hi there."
You can also extend the grammar with custom modifiers that provide useful formatting functions.
Filters accept an input string and return the transformed output:
greeting = Calyx::Grammar.new do
filter :shoutycaps do |input|
input.upcase
end
start '{hello.shoutycaps} there.', 'Why, {hello.shoutycaps} there.'
hello 'hello', 'hi'
end
4.times { greeting.generate }
# => "HELLO there."
# => "HI there."
# => "Why, HELLO there."
# => "Why, HI there."
The mapping shortcut allows you to specify a map of regex patterns pointing to their resulting substitution strings:
green_bottle = Calyx::Grammar.new do
mapping :pluralize, /(.+)/ => '\\1s'
start 'One green {bottle}.', 'Two green {bottle.pluralize}.'
bottle 'bottle'
end
2.times { green_bottle.generate }
# => "One green bottle."
# => "Two green bottles."
In order to use more intricate rewriting and formatting methods in a modifier chain, you can add methods to a module and embed it in a grammar using the modifier
classmethod.
Modifier methods accept a single argument representing the input string from the previous step in the expression chain and must return a string, representing the modified output.
module FullStop
def full_stop(input)
input << '.'
end
end
hello = Calyx::Grammar.new do
modifier FullStop
start '{hello.capitalize.full_stop}'
hello 'hello'
end
hello.generate
# => "Hello."
To share custom modifiers across multiple grammars, you can include the module in Calyx::Modifiers
. This will make the methods available to all subsequent instances:
module FullStop
def full_stop(input)
input << '.'
end
end
class Calyx::Modifiers
include FullStop
end
Alternatively, you can combine methods from existing Gems that monkeypatch String
:
require 'indefinite_article'
module FullStop
def full_stop
self << '.'
end
end
class String
include FullStop
end
noun_articles = Calyx::Grammar.new do
start '{fruit.with_indefinite_article.capitalize.full_stop}'
fruit 'apple', 'orange', 'banana', 'pear'
end
4.times { noun_articles.generate }
# => "An apple."
# => "An orange."
# => "A banana."
# => "A pear."
Rule expansions can be ‘memoized’ so that multiple references to the same rule return the same value. This is useful for picking a noun from a list and reusing it in multiple places within a text.
The @
sigil is used to mark memoized rules. This evaluates the rule and stores it in memory the first time it’s referenced. All subsequent references to the memoized rule use the same stored value.
# Without memoization
grammar = Calyx::Grammar.new do
start '{name} <{name.downcase}>'
name 'Daenerys', 'Tyrion', 'Jon'
end
3.times { grammar.generate }
# => Daenerys <jon>
# => Tyrion <daenerys>
# => Jon <tyrion>
# With memoization
grammar = Calyx::Grammar.new do
start '{@name} <{@name.downcase}>'
name 'Daenerys', 'Tyrion', 'Jon'
end
3.times { grammar.generate }
# => Tyrion <tyrion>
# => Daenerys <daenerys>
# => Jon <jon>
Note that the memoization symbol can only be used on the right hand side of a production rule.
Rule expansions can be marked as ‘unique’, meaning that multiple references to the same rule always return a different value. This is useful for situations where the same result appearing twice would appear awkward and messy.
Unique rules are marked by the $
sigil.
grammar = Calyx::Grammar.new do
start "{$medal}, {$medal}, {$medal}"
medal 'Gold', 'Silver', 'Bronze'
end
grammar.generate
# => Silver, Bronze, Gold
Template expansions can be dynamically constructed at runtime by passing a context map of rules to the #generate
method:
class AppGreeting < Calyx::Grammar
start 'Hi {username}!', 'Welcome back {username}...', 'Hola {username}'
end
context = {
username: UserModel.username
}
greeting = AppGreeting.new
greeting.generate(context)
In addition to defining grammars in pure Ruby, you can load them from external JSON and YAML files:
hello = Calyx::Grammar.load('hello.yml')
hello.generate
The format requires a flat map with keys representing the left-hand side named symbols and the values representing the right hand side substitution rules.
In JSON:
{
"start": "{greeting} world.",
"greeting": ["Hello", "Hi", "Hey", "Yo"]
}
In YAML:
---
start: "{greeting} world."
greeting:
- Hello
- Hi
- Hey
- Yo
Calling #evaluate
on the grammar instance will give you access to the raw generated tree structure before it gets flattened into a string.
The tree is encoded as an array of nested arrays, with the leading symbols labeling the choices and rules selected, and the trailing terminal leaves encoding string values.
This may not make a lot of sense unless you’re familiar with the concept of s-expressions. It’s a fairly speculative feature at this stage, but it leads to some interesting possibilities.
grammar = Calyx::Grammar.new do
start 'Riddle me ree.'
end
grammar.evaluate
# => [:start, [:choice, [:concat, [[:atom, "Riddle me ree."]]]]]
Rough plan for stabilising the API and features for a 1.0
release.
Version | Features planned |
---|---|
0.6 | |
0.7 | |
0.8 | |
0.9 |
|
0.10 | |
0.11 | |
0.12 | |
0.13 | |
0.14 | |
0.15 | |
0.16 | |
0.17 |
|
Author: Maetl
Source Code: https://github.com/maetl/calyx
License: MIT license
1617779520
The annual Analytics India Salary report presented by AIM and AnalytixLabs is the only annual study in India that delves into salary trends and provides a comprehensive view of the changing landscape of analytics salaries. The report, now in its seventh year, look at the distribution of average salaries across several categories including years of experience, metropolitan regions, industries, education levels, gender, tools, and skills.
The Data Analytics function is experiencing significant growth and development in terms of skills, capabilities, and funding. Last year, despite the pandemic, the Indian start-up industry witnessed $836.3 million investment, almost a 10% (9.7%) increase than the previous year. Also, more than one in five (21%) analytics teams across firms in India witnessed a growth in the last 12 months and the post-pandemic job market saw an upswing of data science jobs. The development of the data science domain is evidenced by the high salaries drawn by analytics professionals across the organization, with Analytics professionals doing relatively well in spite of the pandemic.
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