Text Processing and Tokenization

/**
 * Iterator interface for sentence-level text processing
 * Provides sentence boundary detection and preprocessing
 */
public interface SentenceIterator {
    
    /**
     * Get next sentence or null if no more sentences available
     * @return Next sentence string, or null if iterator is exhausted
     */
    String nextSentence();
    
    /**
     * Check if more sentences are available
     * @return true if more sentences exist, false otherwise
     */
    boolean hasNext();
    
    /**
     * Reset iterator to beginning of data source
     * Allows multiple passes over the same data
     */
    void reset();
    
    /**
     * Clean up resources and close input streams
     * Should be called when iteration is complete
     */
    void finish();
    
    /**
     * Get current sentence preprocessor
     * @return SentencePreProcessor instance or null if none set
     */
    SentencePreProcessor getPreProcessor();
    
    /**
     * Set sentence preprocessor for text cleaning
     * @param preProcessor SentencePreProcessor for sentence-level cleaning
     */
    void setPreProcessor(SentencePreProcessor preProcessor);
}

/**
 * Sentence preprocessing interface for text normalization
 */
public interface SentencePreProcessor {
    /**
     * Preprocess sentence text
     * @param sentence Input sentence string
     * @return Preprocessed sentence string
     */
    String preProcess(String sentence);
}

/**
 * File-based sentence iterator reading from text files
 */
public class FileSentenceIterator implements SentenceIterator {
    // File-based sentence iteration with configurable encoding
}

/**
 * Line-based sentence iterator treating each line as a sentence
 */
public class LineSentenceIterator implements SentenceIterator {
    // Simple line-by-line sentence processing
}

/**
 * Collection-based sentence iterator for in-memory text collections
 */
public class CollectionSentenceIterator implements SentenceIterator {
    
    /**
     * Create iterator from string collection
     * @param sentences Collection of sentence strings
     */
    public CollectionSentenceIterator(Collection<String> sentences);
}

/**
 * Stream-based line iterator with configurable fetch size
 */
public class StreamLineIterator implements SentenceIterator {
    
    /**
     * Builder for StreamLineIterator configuration
     */
    public static class Builder {
        /**
         * Create builder with document iterator source
         * @param iterator DocumentIterator providing input documents
         */
        public Builder(DocumentIterator iterator);
        
        /**
         * Set fetch size for batched processing
         * @param fetchSize Number of lines to fetch at once
         * @return Builder instance for method chaining
         */
        public Builder setFetchSize(int fetchSize);
        
        /**
         * Build configured StreamLineIterator
         * @return StreamLineIterator instance
         */
        public StreamLineIterator build();
    }
}

/**
 * Thread-safe wrapper for sentence iterators
 */
public class SynchronizedSentenceIterator implements SentenceIterator {
    // Thread-safe sentence iteration wrapper
}

/**
 * Prefetching sentence iterator for improved performance
 */
public class PrefetchingSentenceIterator implements SentenceIterator {
    // Performance-optimized iterator with prefetching
}

/**
 * Multiple epochs sentence iterator for repeated data passes
 */
public class MutipleEpochsSentenceIterator implements SentenceIterator {
    // Iterator supporting multiple epochs over same data
}

/**
 * Aggregating iterator combining multiple sentence sources
 */
public class AggregatingSentenceIterator implements SentenceIterator {
    // Combines multiple SentenceIterator instances
}

/**
 * Label-aware sentence iterator interface for supervised learning
 */
public interface LabelAwareSentenceIterator extends SentenceIterator {
    /**
     * Get current sentence label
     * @return Label string for current sentence
     */
    String currentLabel();
    
    /**
     * Get labels source
     * @return LabelsSource containing available labels
     */
    LabelsSource getLabelsSource();
}

/**
 * File-based label-aware sentence iterator
 */
public class LabelAwareFileSentenceIterator implements LabelAwareSentenceIterator {
    // File-based iteration with label extraction from filenames or content
}

/**
 * List-based label-aware sentence iterator
 */
public class LabelAwareListSentenceIterator implements LabelAwareSentenceIterator {
    // In-memory iteration over labeled sentence collections
}

/**
 * Document iterator interface for document-level text processing
 * Provides InputStream access to document content
 */
public interface DocumentIterator extends Serializable {
    
    /**
     * Get next document as input stream
     * @return InputStream for next document content
     */
    InputStream nextDocument();
    
    /**
     * Check if more documents are available
     * @return true if more documents exist, false otherwise
     */
    boolean hasNext();
    
    /**
     * Reset iterator to beginning of document collection
     */
    void reset();
}

/**
 * File-based document iterator for file system traversal
 */
public class FileDocumentIterator implements DocumentIterator {
    // Iterate over files in directory structure
}

/**
 * Label-aware document iterator interface
 */
public interface LabelAwareDocumentIterator extends DocumentIterator {
    /**
     * Get labels for current document
     * @return List of label strings for current document
     */
    List<String> getLabels();
    
    /**
     * Check if iterator has labels
     * @return true if labels are available, false otherwise
     */
    boolean hasLabels();
}

/**
 * General label-aware iterator interface
 */
public interface LabelAwareIterator {
    /**
     * Get next labeled document
     * @return LabelledDocument instance
     */
    LabelledDocument nextDocument();
    
    /**
     * Check if more labeled documents available
     * @return true if more documents exist
     */
    boolean hasNext();
    
    /**
     * Reset to beginning of labeled data
     */
    void reset();
    
    /**
     * Get labels source
     * @return LabelsSource containing available labels
     */
    LabelsSource getLabelsSource();
}

/**
 * Basic implementation of label-aware iterator
 */
public class BasicLabelAwareIterator implements LabelAwareIterator {
    
    /**
     * Create iterator from labeled document collection
     * @param documents Collection of LabelledDocument instances
     */
    public BasicLabelAwareIterator(Collection<LabelledDocument> documents);
}

/**
 * File-based label-aware iterator
 */
public class FileLabelAwareIterator implements LabelAwareIterator {
    // File-based iteration with label extraction
}

/**
 * Filename-based label-aware iterator
 */
public class FilenamesLabelAwareIterator implements LabelAwareIterator {
    // Extract labels from filenames during iteration
}

/**
 * Simple label-aware iterator implementation
 */
public class SimpleLabelAwareIterator implements LabelAwareIterator {
    // Simple labeled document iteration
}

/**
 * Asynchronous label-aware iterator for performance
 */
public class AsyncLabelAwareIterator implements LabelAwareIterator {
    // Asynchronous processing of labeled documents
}

/**
 * Factory interface for creating tokenizers
 */
public interface TokenizerFactory {
    
    /**
     * Create tokenizer from string input
     * @param toTokenize String to be tokenized
     * @return Tokenizer instance for the input string
     */
    Tokenizer create(String toTokenize);
    
    /**
     * Create tokenizer from input stream
     * @param toTokenize InputStream to be tokenized
     * @return Tokenizer instance for the input stream
     */
    Tokenizer create(InputStream toTokenize);
    
    /**
     * Set token preprocessor for all created tokenizers
     * @param preProcessor TokenPreProcess instance for token cleaning
     */
    void setTokenPreProcessor(TokenPreProcess preProcessor);
    
    /**
     * Get current token preprocessor
     * @return TokenPreProcess instance or null if none set
     */
    TokenPreProcess getTokenPreProcessor();
}

/**
 * Default tokenizer factory implementation
 */
public class DefaultTokenizerFactory implements TokenizerFactory {
    // Standard tokenization with whitespace and punctuation handling
}

/**
 * N-gram tokenizer factory for n-gram generation
 */
public class NGramTokenizerFactory implements TokenizerFactory {
    // Creates n-gram tokens from input text
}

/**
 * Tokenizer interface for text tokenization
 */
public interface Tokenizer {
    /**
     * Get all tokens from input
     * @return List of token strings
     */
    List<String> getTokens();
    
    /**
     * Count total number of tokens
     * @return Number of tokens in input
     */
    int countTokens();
    
    /**
     * Get next token
     * @return Next token string or null if no more tokens
     */
    String nextToken();
    
    /**
     * Check if more tokens available
     * @return true if more tokens exist
     */
    boolean hasMoreTokens();
}

/**
 * Default tokenizer implementation
 */
public class DefaultTokenizer implements Tokenizer {
    // Standard tokenization with delimiter-based splitting
}

/**
 * Stream-based tokenizer for large inputs
 */
public class DefaultStreamTokenizer implements Tokenizer {
    // Memory-efficient tokenization of streams
}

/**
 * N-gram tokenizer for generating n-gram sequences
 */
public class NGramTokenizer implements Tokenizer {
    // Generates n-gram token sequences from input
}

/**
 * Token preprocessing interface
 */
public interface TokenPreProcess {
    /**
     * Preprocess token string
     * @param token Input token string
     * @return Preprocessed token string
     */
    String preProcess(String token);
}

/**
 * Common token preprocessing operations
 */
public class CommonPreprocessor implements TokenPreProcess {
    // Standard preprocessing: lowercasing, punctuation removal, etc.
}

/**
 * Lowercase token preprocessor
 */
public class LowCasePreProcessor implements TokenPreProcess {
    // Converts tokens to lowercase
}

/**
 * String cleaning preprocessor
 */
public class StringCleaning implements TokenPreProcess {
    // Comprehensive string cleaning and normalization
}

/**
 * Word ending preprocessor
 */
public class EndingPreProcessor implements TokenPreProcess {
    // Processes word endings and suffixes
}

import org.deeplearning4j.text.sentenceiterator.*;
import org.deeplearning4j.text.tokenization.tokenizerfactory.*;
import org.deeplearning4j.text.tokenization.tokenizer.preprocessor.*;

// Basic sentence iteration
Collection<String> sentences = Arrays.asList(
    "First sentence for processing.",
    "Second sentence with different content.",
    "Third sentence to complete the example."
);

SentenceIterator iterator = new CollectionSentenceIterator(sentences);
while (iterator.hasNext()) {
    String sentence = iterator.nextSentence();
    System.out.println("Processing: " + sentence);
}
iterator.finish();

// File-based sentence iteration
File textFile = new File("corpus.txt");
SentenceIterator fileIterator = new FileSentenceIterator(textFile);

// Configure tokenization with preprocessing
TokenizerFactory tokenizerFactory = new DefaultTokenizerFactory();
tokenizerFactory.setTokenPreProcessor(new CommonPreprocessor());

// Use tokenizer
Tokenizer tokenizer = tokenizerFactory.create("Sample text for tokenization!");
List<String> tokens = tokenizer.getTokens();
System.out.println("Tokens: " + tokens);

// Advanced preprocessing chain
TokenizerFactory advancedFactory = new DefaultTokenizerFactory();
advancedFactory.setTokenPreProcessor(new LowCasePreProcessor());

// Label-aware document processing
Collection<LabelledDocument> labeledDocs = Arrays.asList(
    new LabelledDocument("Positive review text", "positive"),
    new LabelledDocument("Negative review text", "negative")
);

LabelAwareIterator labelIterator = new BasicLabelAwareIterator(labeledDocs);
while (labelIterator.hasNext()) {
    LabelledDocument doc = labelIterator.nextDocument();
    System.out.println("Document: " + doc.getContent());
    System.out.println("Labels: " + doc.getLabels());
}

// Stream-based document processing
DocumentIterator docIterator = new FileDocumentIterator(new File("documents/"));
SentenceIterator streamIterator = new StreamLineIterator.Builder(docIterator)
    .setFetchSize(100)
    .build();

// Multi-threaded sentence processing
SentenceIterator syncIterator = new SynchronizedSentenceIterator(iterator);
// Use syncIterator in multi-threaded environment

/**
 * Converter between document iterator types
 */
public class DocumentIteratorConverter {
    // Converts between LabelAwareDocumentIterator and standard DocumentIterator
}

/**
 * Converter between sentence iterator types  
 */
public class SentenceIteratorConverter {
    // Converts between LabelAwareSentenceIterator and standard SentenceIterator
}