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hands-on | repository contains project models for hands on lab sessions | Learning library

 by   elasticsearchfr Java Version: Current License: No License

 by   elasticsearchfr Java Version: Current License: No License

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kandi X-RAY | hands-on Summary

hands-on is a Java library typically used in Tutorial, Learning applications. hands-on has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.
This repository contains project models for hands on lab sessions about elasticsearch.
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Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • hands-on has a low active ecosystem.
  • It has 39 star(s) with 26 fork(s). There are 8 watchers for this library.
  • It had no major release in the last 12 months.
  • hands-on has no issues reported. There are 3 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of hands-on is current.
hands-on Support
Best in #Learning
Average in #Learning
hands-on Support
Best in #Learning
Average in #Learning

quality kandi Quality

  • hands-on has 0 bugs and 0 code smells.
hands-on Quality
Best in #Learning
Average in #Learning
hands-on Quality
Best in #Learning
Average in #Learning

securitySecurity

  • hands-on has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • hands-on code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
hands-on Security
Best in #Learning
Average in #Learning
hands-on Security
Best in #Learning
Average in #Learning

license License

  • hands-on does not have a standard license declared.
  • Check the repository for any license declaration and review the terms closely.
  • Without a license, all rights are reserved, and you cannot use the library in your applications.
hands-on License
Best in #Learning
Average in #Learning
hands-on License
Best in #Learning
Average in #Learning

buildReuse

  • hands-on releases are not available. You will need to build from source code and install.
  • Build file is available. You can build the component from source.
  • Installation instructions, examples and code snippets are available.
  • hands-on saves you 295 person hours of effort in developing the same functionality from scratch.
  • It has 711 lines of code, 41 functions and 10 files.
  • It has medium code complexity. Code complexity directly impacts maintainability of the code.
hands-on Reuse
Best in #Learning
Average in #Learning
hands-on Reuse
Best in #Learning
Average in #Learning
Top functions reviewed by kandi - BETA

Coming Soon for all Libraries!

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kandi's functional review helps you automatically verify the functionalities of the libraries and avoid rework.

hands-on Key Features

Hands On Lab

Optional

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curl -OL -k http://download.elasticsearch.org/elasticsearch/elasticsearch/elasticsearch-1.0.1.zip

Download the project

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git clone https://github.com/elasticsearchfr/hands-on.git

Compile the project

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mvn compile

Run tests

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mvn test

Test 0: just start a node

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Thread.sleep(120000);

ValueError: Unexpected result of `train_function` (Empty logs). for RNN

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import tensorflow as tf
import numpy as np

shakespeare_url = 'https://homl.info/shakespeare'
filepath = tf.keras.utils.get_file('shakespeare.txt', shakespeare_url)
with open(filepath) as f:
    shakespeare_text = f.read()

# Let's tokenize the text at characters level
tokenizer = tf.keras.preprocessing.text.Tokenizer(char_level=True)
tokenizer.fit_on_texts([shakespeare_text])

# Number of distinct characters
max_id = len(tokenizer.word_index)
# total number of characters

# Lets encode the full text and substract 1 to have a range of 0-38 instead of 1-39
[encoded] = np.array(tokenizer.texts_to_sequences([shakespeare_text])) - 1

# Let's use the first 90% of the data to train the model
dataset_size = encoded.shape[0]
train_size = dataset_size * 90 // 100
dataset = tf.data.Dataset.from_tensor_slices(encoded[:train_size])

n_steps = 100
window_length = n_steps + 1 # 100 steps plus the target
dataset = dataset.window(window_length, shift=1, drop_remainder=True)
# Let's flat our windows dataset into tensors to pass to the model 
dataset = dataset.flat_map(lambda window: window.batch(window_length))
# Let's shuffle the windows
batch_size = 32
dataset = dataset.shuffle(10000).batch(batch_size)
dataset = dataset.map(lambda windows: (windows[:, :-1], windows[:, 1:]), num_parallel_calls=tf.data.AUTOTUNE)
# Encoding the categories as one-hot encoding since the categories are relatively few (39)
dataset = dataset.map(lambda x_batch, y_batch: (tf.one_hot(x_batch, depth=max_id), y_batch), num_parallel_calls=tf.data.AUTOTUNE)
dataset = dataset.prefetch(tf.data.AUTOTUNE)

model = tf.keras.Sequential([
    tf.keras.layers.GRU(128, return_sequences=True, input_shape=[None, max_id], dropout=0.2, recurrent_dropout=0.2),
    tf.keras.layers.GRU(128, return_sequences=True, dropout=0.2, recurrent_dropout=0.2),
    tf.keras.layers.TimeDistributed(tf.keras.layers.Dense(max_id, activation='softmax'))
])
print(model.summary())
model.compile(loss='sparse_categorical_crossentropy', optimizer='adam', metrics=['sparse_categorical_crossentropy'])

history = model.fit(dataset, epochs=20)

How to change base url of create react app?

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{
  "name": "cau-burger-online-order-system",
  "version": "0.1.0",
  "private": true,
  "dependencies": {
    ....
  },
  "scripts": {
    ...
  },
  ...,
  "homepage": "https://hy57in.github.io/2021-Industry-Hands-On-Project"
}
{
  "name": "cau-burger-online-order-system",
  "version": "0.1.0",
  "private": true,
  "dependencies": {
    ...
  },
  "scripts": {
    ...
  },
  ...,
  "homepage": "./"
}
-----------------------
{
  "name": "cau-burger-online-order-system",
  "version": "0.1.0",
  "private": true,
  "dependencies": {
    ....
  },
  "scripts": {
    ...
  },
  ...,
  "homepage": "https://hy57in.github.io/2021-Industry-Hands-On-Project"
}
{
  "name": "cau-burger-online-order-system",
  "version": "0.1.0",
  "private": true,
  "dependencies": {
    ...
  },
  "scripts": {
    ...
  },
  ...,
  "homepage": "./"
}

v2 to v3 Transition for Form Recognizer

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const poller = await client.beginRecognizeInvoices(inputs);
const invoices = await poller.pollUntilDone();

const table = invoices[0].pages[0].tables[0];

How to Use Correlation Against the Output in Spark using Scala

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coeff_matrix.rowIter.toSeq.last.toDense.toArray.sorted.reverse foreach println
1.0
0.6880752079585478
0.13415311380656308
0.10562341249320993
0.06584265057005646
-0.024649678888894886
-0.04596661511797852
-0.14416027687465932
-----------------------
coeff_matrix.rowIter.toSeq.last.toDense.toArray.sorted.reverse foreach println
1.0
0.6880752079585478
0.13415311380656308
0.10562341249320993
0.06584265057005646
-0.024649678888894886
-0.04596661511797852
-0.14416027687465932

Online newspaper data scraping with R, 'rvest' package

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library(rvest)
library(RSelenium)
url = 'https://en.trend.az/archive/2021-11-02'
driver = rsDriver(browser = c("firefox"))
remDr <- driver[["client"]]
remDr$navigate(url)
#click outside in an empty space
remDr$findElement(using = "xpath", value = '/html/body/div[1]/div/div[1]/h1')$clickElement()

webElem <- remDr$findElement("css", "body")
#scrolling to the end of webpage, to load all articles 
for (i in 1:17){
  Sys.sleep(2)
  webElem$sendKeysToElement(list(key = "end"))
} 
remDr$getPageSource()[[1]] %>% 
  read_html() %>%
html_nodes('.category-article') %>% html_nodes('.article-title') %>% 
  html_text()
[1] "Chelsea defeats Malmö with minimum score"                                                                                                 
 [2] "Iran’s import of COVID-19 vaccine exceeds 146mn doses: IRICA"                                                                             
 [3] "Sadyr Zhaparov, Fumio Kishida discuss topical issues of Kyrgyz-Japanese relations"                                                        
 [4] "We will definitely see new names at World Championships and World Age Group Competitions in Trampoline Gymnastics in Baku - Farid Gayibov"
 [5] "Declaration on forest protection, land use adopted by 105 countries"                                                                      
 [6] "Russian Security Council's chief, CIA director meet in Moscow"                                                                            
 [7] "Israel to exhibit for 1st time at Dubai Airshow"                                                                                          
 [8] "Azerbaijan's General Prosecutor's Office continues to take measures on appeal against Armenia"                                            
 [9] "Azerbaijani, Russian FMs discuss activity of working group for restoration of communications in South Caucasus"                           
[10] "Russia holds tenth meeting of joint Azerbaijani-Russian Demarcation Commission"                                                           
[11] "Only external reasons cause inflation in Azerbaijan - Gazprombank"                                                                        
[12] "State Oil Fund of Azerbaijan launches tender for technical vendor support"   


    
lin = remDr$getPageSource()[[1]] %>% 
  read_html() %>% html_nodes('.category-news-wrapper') %>% html_nodes('.article-link')
remDr$getPageSource()[[1]] %>% 
  read_html() %>%  
  html_nodes('.category-article') %>% html_nodes('.article-meta') %>% 
  html_text()
 [1] "\n                Other News\n                2 November 23:55\n            "
 [2] "\n                Society\n                2 November 23:14\n            "   
 [3] "\n                Kyrgyzstan\n                2 November 22:55\n            "
 [4] "\n                Society\n                2 November 22:51\n            "   
 [5] "\n                Other News\n                2 November 22:26\n            "
 [6] "\n                Russia\n                2 November 21:50\n            "    
 [7] "\n                Israel\n                2 November 21:24\n            "    
 [8] "\n                Politics\n                2 November 20:50\n            "  
 [9] "\n                Politics\n                2 November 20:25\n            "  
[10] "\n                Politics\n                2 November 20:16\n            "  
-----------------------
library(rvest)
library(RSelenium)
url = 'https://en.trend.az/archive/2021-11-02'
driver = rsDriver(browser = c("firefox"))
remDr <- driver[["client"]]
remDr$navigate(url)
#click outside in an empty space
remDr$findElement(using = "xpath", value = '/html/body/div[1]/div/div[1]/h1')$clickElement()

webElem <- remDr$findElement("css", "body")
#scrolling to the end of webpage, to load all articles 
for (i in 1:17){
  Sys.sleep(2)
  webElem$sendKeysToElement(list(key = "end"))
} 
remDr$getPageSource()[[1]] %>% 
  read_html() %>%
html_nodes('.category-article') %>% html_nodes('.article-title') %>% 
  html_text()
[1] "Chelsea defeats Malmö with minimum score"                                                                                                 
 [2] "Iran’s import of COVID-19 vaccine exceeds 146mn doses: IRICA"                                                                             
 [3] "Sadyr Zhaparov, Fumio Kishida discuss topical issues of Kyrgyz-Japanese relations"                                                        
 [4] "We will definitely see new names at World Championships and World Age Group Competitions in Trampoline Gymnastics in Baku - Farid Gayibov"
 [5] "Declaration on forest protection, land use adopted by 105 countries"                                                                      
 [6] "Russian Security Council's chief, CIA director meet in Moscow"                                                                            
 [7] "Israel to exhibit for 1st time at Dubai Airshow"                                                                                          
 [8] "Azerbaijan's General Prosecutor's Office continues to take measures on appeal against Armenia"                                            
 [9] "Azerbaijani, Russian FMs discuss activity of working group for restoration of communications in South Caucasus"                           
[10] "Russia holds tenth meeting of joint Azerbaijani-Russian Demarcation Commission"                                                           
[11] "Only external reasons cause inflation in Azerbaijan - Gazprombank"                                                                        
[12] "State Oil Fund of Azerbaijan launches tender for technical vendor support"   


    
lin = remDr$getPageSource()[[1]] %>% 
  read_html() %>% html_nodes('.category-news-wrapper') %>% html_nodes('.article-link')
remDr$getPageSource()[[1]] %>% 
  read_html() %>%  
  html_nodes('.category-article') %>% html_nodes('.article-meta') %>% 
  html_text()
 [1] "\n                Other News\n                2 November 23:55\n            "
 [2] "\n                Society\n                2 November 23:14\n            "   
 [3] "\n                Kyrgyzstan\n                2 November 22:55\n            "
 [4] "\n                Society\n                2 November 22:51\n            "   
 [5] "\n                Other News\n                2 November 22:26\n            "
 [6] "\n                Russia\n                2 November 21:50\n            "    
 [7] "\n                Israel\n                2 November 21:24\n            "    
 [8] "\n                Politics\n                2 November 20:50\n            "  
 [9] "\n                Politics\n                2 November 20:25\n            "  
[10] "\n                Politics\n                2 November 20:16\n            "  
-----------------------
library(rvest)
library(RSelenium)
url = 'https://en.trend.az/archive/2021-11-02'
driver = rsDriver(browser = c("firefox"))
remDr <- driver[["client"]]
remDr$navigate(url)
#click outside in an empty space
remDr$findElement(using = "xpath", value = '/html/body/div[1]/div/div[1]/h1')$clickElement()

webElem <- remDr$findElement("css", "body")
#scrolling to the end of webpage, to load all articles 
for (i in 1:17){
  Sys.sleep(2)
  webElem$sendKeysToElement(list(key = "end"))
} 
remDr$getPageSource()[[1]] %>% 
  read_html() %>%
html_nodes('.category-article') %>% html_nodes('.article-title') %>% 
  html_text()
[1] "Chelsea defeats Malmö with minimum score"                                                                                                 
 [2] "Iran’s import of COVID-19 vaccine exceeds 146mn doses: IRICA"                                                                             
 [3] "Sadyr Zhaparov, Fumio Kishida discuss topical issues of Kyrgyz-Japanese relations"                                                        
 [4] "We will definitely see new names at World Championships and World Age Group Competitions in Trampoline Gymnastics in Baku - Farid Gayibov"
 [5] "Declaration on forest protection, land use adopted by 105 countries"                                                                      
 [6] "Russian Security Council's chief, CIA director meet in Moscow"                                                                            
 [7] "Israel to exhibit for 1st time at Dubai Airshow"                                                                                          
 [8] "Azerbaijan's General Prosecutor's Office continues to take measures on appeal against Armenia"                                            
 [9] "Azerbaijani, Russian FMs discuss activity of working group for restoration of communications in South Caucasus"                           
[10] "Russia holds tenth meeting of joint Azerbaijani-Russian Demarcation Commission"                                                           
[11] "Only external reasons cause inflation in Azerbaijan - Gazprombank"                                                                        
[12] "State Oil Fund of Azerbaijan launches tender for technical vendor support"   


    
lin = remDr$getPageSource()[[1]] %>% 
  read_html() %>% html_nodes('.category-news-wrapper') %>% html_nodes('.article-link')
remDr$getPageSource()[[1]] %>% 
  read_html() %>%  
  html_nodes('.category-article') %>% html_nodes('.article-meta') %>% 
  html_text()
 [1] "\n                Other News\n                2 November 23:55\n            "
 [2] "\n                Society\n                2 November 23:14\n            "   
 [3] "\n                Kyrgyzstan\n                2 November 22:55\n            "
 [4] "\n                Society\n                2 November 22:51\n            "   
 [5] "\n                Other News\n                2 November 22:26\n            "
 [6] "\n                Russia\n                2 November 21:50\n            "    
 [7] "\n                Israel\n                2 November 21:24\n            "    
 [8] "\n                Politics\n                2 November 20:50\n            "  
 [9] "\n                Politics\n                2 November 20:25\n            "  
[10] "\n                Politics\n                2 November 20:16\n            "  
-----------------------
library(rvest)
library(RSelenium)
url = 'https://en.trend.az/archive/2021-11-02'
driver = rsDriver(browser = c("firefox"))
remDr <- driver[["client"]]
remDr$navigate(url)
#click outside in an empty space
remDr$findElement(using = "xpath", value = '/html/body/div[1]/div/div[1]/h1')$clickElement()

webElem <- remDr$findElement("css", "body")
#scrolling to the end of webpage, to load all articles 
for (i in 1:17){
  Sys.sleep(2)
  webElem$sendKeysToElement(list(key = "end"))
} 
remDr$getPageSource()[[1]] %>% 
  read_html() %>%
html_nodes('.category-article') %>% html_nodes('.article-title') %>% 
  html_text()
[1] "Chelsea defeats Malmö with minimum score"                                                                                                 
 [2] "Iran’s import of COVID-19 vaccine exceeds 146mn doses: IRICA"                                                                             
 [3] "Sadyr Zhaparov, Fumio Kishida discuss topical issues of Kyrgyz-Japanese relations"                                                        
 [4] "We will definitely see new names at World Championships and World Age Group Competitions in Trampoline Gymnastics in Baku - Farid Gayibov"
 [5] "Declaration on forest protection, land use adopted by 105 countries"                                                                      
 [6] "Russian Security Council's chief, CIA director meet in Moscow"                                                                            
 [7] "Israel to exhibit for 1st time at Dubai Airshow"                                                                                          
 [8] "Azerbaijan's General Prosecutor's Office continues to take measures on appeal against Armenia"                                            
 [9] "Azerbaijani, Russian FMs discuss activity of working group for restoration of communications in South Caucasus"                           
[10] "Russia holds tenth meeting of joint Azerbaijani-Russian Demarcation Commission"                                                           
[11] "Only external reasons cause inflation in Azerbaijan - Gazprombank"                                                                        
[12] "State Oil Fund of Azerbaijan launches tender for technical vendor support"   


    
lin = remDr$getPageSource()[[1]] %>% 
  read_html() %>% html_nodes('.category-news-wrapper') %>% html_nodes('.article-link')
remDr$getPageSource()[[1]] %>% 
  read_html() %>%  
  html_nodes('.category-article') %>% html_nodes('.article-meta') %>% 
  html_text()
 [1] "\n                Other News\n                2 November 23:55\n            "
 [2] "\n                Society\n                2 November 23:14\n            "   
 [3] "\n                Kyrgyzstan\n                2 November 22:55\n            "
 [4] "\n                Society\n                2 November 22:51\n            "   
 [5] "\n                Other News\n                2 November 22:26\n            "
 [6] "\n                Russia\n                2 November 21:50\n            "    
 [7] "\n                Israel\n                2 November 21:24\n            "    
 [8] "\n                Politics\n                2 November 20:50\n            "  
 [9] "\n                Politics\n                2 November 20:25\n            "  
[10] "\n                Politics\n                2 November 20:16\n            "  

How to use the R environment and the globalenv() function

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deal <- function(){
  card <- deck[1,]
  assign("deck", deck[-1,], envir = globalenv())
  card
}
deal <- function(){
  card <- deck[1,]
  deck <- deck[-1,]
  card
}
card <- deck[1,]
-----------------------
deal <- function(){
  card <- deck[1,]
  assign("deck", deck[-1,], envir = globalenv())
  card
}
deal <- function(){
  card <- deck[1,]
  deck <- deck[-1,]
  card
}
card <- deck[1,]
-----------------------
deal <- function(){
  card <- deck[1,]
  assign("deck", deck[-1,], envir = globalenv())
  card
}
deal <- function(){
  card <- deck[1,]
  deck <- deck[-1,]
  card
}
card <- deck[1,]

How can I debug some Rust code to find out why the &quot;if&quot; statement doesn't run?

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enter = enter.trim().to_lowercase();
-----------------------
for key in &key_list {
    if dbg!(key) == dbg!(&enter) {
        valid = true
    }
};
Please enter the key
1
[src/main.rs:10] key = "1"
[src/main.rs:10] &enter = "1\n"
[src/main.rs:10] key = "2"
[src/main.rs:10] &enter = "1\n"
[src/main.rs:10] key = "3"
[src/main.rs:10] &enter = "1\n"
pub fn trim(&self) -> &str
pub fn to_lowercase(&self) -> String
let enter = enter.trim().to_lowercase();
-----------------------
for key in &key_list {
    if dbg!(key) == dbg!(&enter) {
        valid = true
    }
};
Please enter the key
1
[src/main.rs:10] key = "1"
[src/main.rs:10] &enter = "1\n"
[src/main.rs:10] key = "2"
[src/main.rs:10] &enter = "1\n"
[src/main.rs:10] key = "3"
[src/main.rs:10] &enter = "1\n"
pub fn trim(&self) -> &str
pub fn to_lowercase(&self) -> String
let enter = enter.trim().to_lowercase();
-----------------------
for key in &key_list {
    if dbg!(key) == dbg!(&enter) {
        valid = true
    }
};
Please enter the key
1
[src/main.rs:10] key = "1"
[src/main.rs:10] &enter = "1\n"
[src/main.rs:10] key = "2"
[src/main.rs:10] &enter = "1\n"
[src/main.rs:10] key = "3"
[src/main.rs:10] &enter = "1\n"
pub fn trim(&self) -> &str
pub fn to_lowercase(&self) -> String
let enter = enter.trim().to_lowercase();
-----------------------
for key in &key_list {
    if dbg!(key) == dbg!(&enter) {
        valid = true
    }
};
Please enter the key
1
[src/main.rs:10] key = "1"
[src/main.rs:10] &enter = "1\n"
[src/main.rs:10] key = "2"
[src/main.rs:10] &enter = "1\n"
[src/main.rs:10] key = "3"
[src/main.rs:10] &enter = "1\n"
pub fn trim(&self) -> &str
pub fn to_lowercase(&self) -> String
let enter = enter.trim().to_lowercase();
-----------------------
for key in &key_list {
    if dbg!(key) == dbg!(&enter) {
        valid = true
    }
};
Please enter the key
1
[src/main.rs:10] key = "1"
[src/main.rs:10] &enter = "1\n"
[src/main.rs:10] key = "2"
[src/main.rs:10] &enter = "1\n"
[src/main.rs:10] key = "3"
[src/main.rs:10] &enter = "1\n"
pub fn trim(&self) -> &str
pub fn to_lowercase(&self) -> String
let enter = enter.trim().to_lowercase();

Kotlin/JS, Gradle Plugin : Unable to load '@webpack-cli/serve' command

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rootProject.plugins.withType(org.jetbrains.kotlin.gradle.targets.js.nodejs.NodeJsRootPlugin::class.java) {  
    rootProject.the<org.jetbrains.kotlin.gradle.targets.js.nodejs.NodeJsRootExtension>().versions.webpackCli.version = "4.9.0"
}
-----------------------
kotlin.js.webpack.major.version=4

Type List&lt;dynamic&gt; is not a subtype of type Map&lt;String dynamic&gt;

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  static getBooksAll() async {
    var bookURL =
        "https://raw.githubusercontent.com/dineshnagarajandev/samplejson/main/books.json";
    var response = await http.get(Uri.parse(bookURL));
    var listToPass = jsonDecode(response.body);
    List<BookData> bookData =
        List<BookData>.from(listToPass.map((i) => BookData.fromJson(i)));
    print(bookData);
  }
this.id = json["_id"] == null ? null : Id.fromJson(json["_id"]);
class BookData {
  int? id;
  String? title;
  String? isbn;
  int? pageCount;
  PublishedDate? publishedDate;
  String? thumbnailUrl;
  String? shortDescription;
  String? longDescription;
  String? status;
  List<dynamic>? authors;
  List<dynamic>? categories;

  BookData(
      {this.id,
      this.title,
      this.isbn,
      this.pageCount,
      this.publishedDate,
      this.thumbnailUrl,
      this.shortDescription,
      this.longDescription,
      this.status,
      this.authors,
      this.categories});

  BookData.fromJson(Map<String, dynamic> json) {
    this.id = json["_id"] == null ? null : json["_id"];
    this.title = json["title"];
    this.isbn = json["isbn"];
    this.pageCount = json["pageCount"];
    this.publishedDate = json["publishedDate"] == null
        ? null
        : PublishedDate.fromJson(json["publishedDate"]);
    this.thumbnailUrl = json["thumbnailUrl"];
    this.shortDescription = json["shortDescription"];
    this.longDescription = json["longDescription"];
    this.status = json["status"];
    this.authors = json["authors"] ?? [];
    this.categories = json["categories"] ?? [];
  }

  Map<String, dynamic> toJson() {
    final Map<String, dynamic> data = new Map<String, dynamic>();
    if (this.id != null) data["_id"] = this.id;
    data["title"] = this.title;
    data["isbn"] = this.isbn;
    data["pageCount"] = this.pageCount;
    if (this.publishedDate != null)
      data["publishedDate"] = this.publishedDate?.toJson();
    data["thumbnailUrl"] = this.thumbnailUrl;
    data["shortDescription"] = this.shortDescription;
    data["longDescription"] = this.longDescription;
    data["status"] = this.status;
    if (this.authors != null) data["authors"] = this.authors;
    if (this.categories != null) data["categories"] = this.categories;
    return data;
  }
}

class PublishedDate {
  String? $date;

  PublishedDate({this.$date});

  PublishedDate.fromJson(Map<String, dynamic> json) {
    this.$date = json["${$date}"];
  }

  Map<String, dynamic> toJson() {
    final Map<String, dynamic> data = new Map<String, dynamic>();
    data["${$date}"] = this.$date;
    return data;
  }
}
-----------------------
  static getBooksAll() async {
    var bookURL =
        "https://raw.githubusercontent.com/dineshnagarajandev/samplejson/main/books.json";
    var response = await http.get(Uri.parse(bookURL));
    var listToPass = jsonDecode(response.body);
    List<BookData> bookData =
        List<BookData>.from(listToPass.map((i) => BookData.fromJson(i)));
    print(bookData);
  }
this.id = json["_id"] == null ? null : Id.fromJson(json["_id"]);
class BookData {
  int? id;
  String? title;
  String? isbn;
  int? pageCount;
  PublishedDate? publishedDate;
  String? thumbnailUrl;
  String? shortDescription;
  String? longDescription;
  String? status;
  List<dynamic>? authors;
  List<dynamic>? categories;

  BookData(
      {this.id,
      this.title,
      this.isbn,
      this.pageCount,
      this.publishedDate,
      this.thumbnailUrl,
      this.shortDescription,
      this.longDescription,
      this.status,
      this.authors,
      this.categories});

  BookData.fromJson(Map<String, dynamic> json) {
    this.id = json["_id"] == null ? null : json["_id"];
    this.title = json["title"];
    this.isbn = json["isbn"];
    this.pageCount = json["pageCount"];
    this.publishedDate = json["publishedDate"] == null
        ? null
        : PublishedDate.fromJson(json["publishedDate"]);
    this.thumbnailUrl = json["thumbnailUrl"];
    this.shortDescription = json["shortDescription"];
    this.longDescription = json["longDescription"];
    this.status = json["status"];
    this.authors = json["authors"] ?? [];
    this.categories = json["categories"] ?? [];
  }

  Map<String, dynamic> toJson() {
    final Map<String, dynamic> data = new Map<String, dynamic>();
    if (this.id != null) data["_id"] = this.id;
    data["title"] = this.title;
    data["isbn"] = this.isbn;
    data["pageCount"] = this.pageCount;
    if (this.publishedDate != null)
      data["publishedDate"] = this.publishedDate?.toJson();
    data["thumbnailUrl"] = this.thumbnailUrl;
    data["shortDescription"] = this.shortDescription;
    data["longDescription"] = this.longDescription;
    data["status"] = this.status;
    if (this.authors != null) data["authors"] = this.authors;
    if (this.categories != null) data["categories"] = this.categories;
    return data;
  }
}

class PublishedDate {
  String? $date;

  PublishedDate({this.$date});

  PublishedDate.fromJson(Map<String, dynamic> json) {
    this.$date = json["${$date}"];
  }

  Map<String, dynamic> toJson() {
    final Map<String, dynamic> data = new Map<String, dynamic>();
    data["${$date}"] = this.$date;
    return data;
  }
}
-----------------------
  static getBooksAll() async {
    var bookURL =
        "https://raw.githubusercontent.com/dineshnagarajandev/samplejson/main/books.json";
    var response = await http.get(Uri.parse(bookURL));
    var listToPass = jsonDecode(response.body);
    List<BookData> bookData =
        List<BookData>.from(listToPass.map((i) => BookData.fromJson(i)));
    print(bookData);
  }
this.id = json["_id"] == null ? null : Id.fromJson(json["_id"]);
class BookData {
  int? id;
  String? title;
  String? isbn;
  int? pageCount;
  PublishedDate? publishedDate;
  String? thumbnailUrl;
  String? shortDescription;
  String? longDescription;
  String? status;
  List<dynamic>? authors;
  List<dynamic>? categories;

  BookData(
      {this.id,
      this.title,
      this.isbn,
      this.pageCount,
      this.publishedDate,
      this.thumbnailUrl,
      this.shortDescription,
      this.longDescription,
      this.status,
      this.authors,
      this.categories});

  BookData.fromJson(Map<String, dynamic> json) {
    this.id = json["_id"] == null ? null : json["_id"];
    this.title = json["title"];
    this.isbn = json["isbn"];
    this.pageCount = json["pageCount"];
    this.publishedDate = json["publishedDate"] == null
        ? null
        : PublishedDate.fromJson(json["publishedDate"]);
    this.thumbnailUrl = json["thumbnailUrl"];
    this.shortDescription = json["shortDescription"];
    this.longDescription = json["longDescription"];
    this.status = json["status"];
    this.authors = json["authors"] ?? [];
    this.categories = json["categories"] ?? [];
  }

  Map<String, dynamic> toJson() {
    final Map<String, dynamic> data = new Map<String, dynamic>();
    if (this.id != null) data["_id"] = this.id;
    data["title"] = this.title;
    data["isbn"] = this.isbn;
    data["pageCount"] = this.pageCount;
    if (this.publishedDate != null)
      data["publishedDate"] = this.publishedDate?.toJson();
    data["thumbnailUrl"] = this.thumbnailUrl;
    data["shortDescription"] = this.shortDescription;
    data["longDescription"] = this.longDescription;
    data["status"] = this.status;
    if (this.authors != null) data["authors"] = this.authors;
    if (this.categories != null) data["categories"] = this.categories;
    return data;
  }
}

class PublishedDate {
  String? $date;

  PublishedDate({this.$date});

  PublishedDate.fromJson(Map<String, dynamic> json) {
    this.$date = json["${$date}"];
  }

  Map<String, dynamic> toJson() {
    final Map<String, dynamic> data = new Map<String, dynamic>();
    data["${$date}"] = this.$date;
    return data;
  }
}

How to use 'partitioning_func' in TimeScale DB

copy iconCopydownload iconDownload
CREATE OR REPLACE FUNCTION two_partition_fun(i anyelement) RETURNS integer AS \$\$
        BEGIN
                RETURN 1073741821 + i;
        END;
\$\$ LANGUAGE plpgsql IMMUTABLE;

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QUESTION

ValueError: Unexpected result of `train_function` (Empty logs). for RNN

Asked 2022-Mar-14 at 10:06

I am reproducing the examples of the chapter 16 of the book Hands-On Machine Learning of Aurélien Géron and found an error while trying to train a simple RNN model.

The error is the following:

ValueError: Unexpected result of `train_function` (Empty logs). Please use `Model.compile(..., run_eagerly=True)`, or `tf.config.run_functions_eagerly(True)` for more information of where went wrong, or file a issue/bug to `tf.keras`. 

The code used to retrieve the data and preprocess:

shakespeare_url = 'https://homl.info/shakespeare'
filepath = utils.get_file('shakespeare.txt', shakespeare_url)
with open(filepath) as f:
    shakespeare_text = f.read()

# Let's tokenize the text at characters level
tokenizer = preprocessing.text.Tokenizer(char_level=True)
tokenizer.fit_on_texts([shakespeare_text])

# Number of distinct characters
max_id = len(tokenizer.word_index)
# total number of characters
dataset_size = tokenizer.document_count

# Lets encode the full text and substract 1 to have a range of 0-38 instead of 1-39
[encoded] = np.array(tokenizer.texts_to_sequences([shakespeare_text])) - 1

# Let's use the first 90% of the data to train the model 
train_size = dataset_size * 90 // 100
dataset = tf.data.Dataset.from_tensor_slices(encoded[:train_size])

n_steps = 100
window_length = n_steps + 1 # 100 steps plus the target
dataset = dataset.window(window_length, shift=1, drop_remainder=True)
# Let's flat our windows dataset into tensors to pass to the model 
dataset = dataset.flat_map(lambda window: window.batch(window_length))
# Let's shuffle the windows
batch_size = 32
dataset = dataset.shuffle(10000).batch(batch_size)
dataset = dataset.map(lambda windows: (windows[:, :-1], windows[:, 1:]), num_parallel_calls=AUTOTUNE)
# Encoding the categories as one-hot encoding since the categories are relatively few (39)
dataset = dataset.map(lambda x_batch, y_batch: (tf.one_hot(x_batch, depth=max_id), y_batch), num_parallel_calls=AUTOTUNE)
dataset = dataset.prefetch(AUTOTUNE)

Here is the code of the model:

model = models.Sequential([
    layers.GRU(128, return_sequences=True, input_shape=[None, max_id], dropout=0.2, recurrent_dropout=0.2),
    layers.GRU(128, return_sequences=True, dropout=0.2, recurrent_dropout=0.2),
    layers.TimeDistributed(layers.Dense(max_id, activation='softmax'))
])

model.compile(loss='sparse_categorical_crossentropy', optimizer='adam', metrics=['sparse_categorical_crossentropy'])

history = model.fit(dataset, epochs=20)

Feel free to request more information if needed. Thanks in advance.

ANSWER

Answered 2022-Mar-14 at 10:06

The problem is that tokenizer.document_count considers the whole text as one data entry, which is why dataset_size equals 1 and train_size therefore equals 0, resulting in an empty data set. Try using the encoded array to get the true number of data entries:

import tensorflow as tf
import numpy as np

shakespeare_url = 'https://homl.info/shakespeare'
filepath = tf.keras.utils.get_file('shakespeare.txt', shakespeare_url)
with open(filepath) as f:
    shakespeare_text = f.read()

# Let's tokenize the text at characters level
tokenizer = tf.keras.preprocessing.text.Tokenizer(char_level=True)
tokenizer.fit_on_texts([shakespeare_text])

# Number of distinct characters
max_id = len(tokenizer.word_index)
# total number of characters

# Lets encode the full text and substract 1 to have a range of 0-38 instead of 1-39
[encoded] = np.array(tokenizer.texts_to_sequences([shakespeare_text])) - 1

# Let's use the first 90% of the data to train the model
dataset_size = encoded.shape[0]
train_size = dataset_size * 90 // 100
dataset = tf.data.Dataset.from_tensor_slices(encoded[:train_size])

n_steps = 100
window_length = n_steps + 1 # 100 steps plus the target
dataset = dataset.window(window_length, shift=1, drop_remainder=True)
# Let's flat our windows dataset into tensors to pass to the model 
dataset = dataset.flat_map(lambda window: window.batch(window_length))
# Let's shuffle the windows
batch_size = 32
dataset = dataset.shuffle(10000).batch(batch_size)
dataset = dataset.map(lambda windows: (windows[:, :-1], windows[:, 1:]), num_parallel_calls=tf.data.AUTOTUNE)
# Encoding the categories as one-hot encoding since the categories are relatively few (39)
dataset = dataset.map(lambda x_batch, y_batch: (tf.one_hot(x_batch, depth=max_id), y_batch), num_parallel_calls=tf.data.AUTOTUNE)
dataset = dataset.prefetch(tf.data.AUTOTUNE)

model = tf.keras.Sequential([
    tf.keras.layers.GRU(128, return_sequences=True, input_shape=[None, max_id], dropout=0.2, recurrent_dropout=0.2),
    tf.keras.layers.GRU(128, return_sequences=True, dropout=0.2, recurrent_dropout=0.2),
    tf.keras.layers.TimeDistributed(tf.keras.layers.Dense(max_id, activation='softmax'))
])
print(model.summary())
model.compile(loss='sparse_categorical_crossentropy', optimizer='adam', metrics=['sparse_categorical_crossentropy'])

history = model.fit(dataset, epochs=20)

Source https://stackoverflow.com/questions/71242821

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

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