wordEncoding — Create a word encoding object that maps words to indices and back.
wordEncoding(documents) creates a RunMat wordEncoding compatibility object from tokenized documents. wordEncoding(words) creates one from a word vector.
Syntax
enc = wordEncoding(documents)
enc = wordEncoding(words)
enc = wordEncoding(documents, Name, Value)Inputs
| Name | Type | Required | Default | Description |
|---|---|---|---|---|
documentsOrWords | Any | Yes | — | tokenizedDocument object or word vector. |
NameValue | Any | Variadic | — | Name-value options: Order, MaxNumWords. |
Returns
| Name | Type | Description |
|---|---|---|
enc | Any | Word encoding compatibility object. |
Errors
| Identifier | When | Message |
|---|---|---|
RunMat:wordEncoding:InvalidInput | Inputs do not match a supported wordEncoding form. | wordEncoding received invalid input |
How wordEncoding works
documentsmust be a RunMattokenizedDocumentcompatibility object.wordsmay be a string scalar, string array, character vector, character matrix, or cell array of scalar text. A character vector is treated as one word.- The returned object exposes
NumWordsandVocabulary.Vocabularyis a 1-by-NumWords string array. Orderaccepts"first-seen"and"frequency"for tokenizedDocument input. The default is first-seen order.- For frequency ordering, RunMat sorts by descending total count and uses first-seen order as a deterministic tie-breaker.
MaxNumWordsaccepts a positive integer orInffor tokenizedDocument input. The option is applied after ordering.- RunMat rejects
OrderandMaxNumWordswhen the first input is a word vector, matching the documented MATLAB syntax. - First-class MATLAB object-array identity semantics are not required for this scalar model object and remain covered by the broader object infrastructure work.
GPU memory and residency
wordEncoding is host text/object metadata construction with no provider kernel.
Examples
Create Encoding From Documents
documents = tokenizedDocument(["alpha beta alpha"; "gamma beta"]);
enc = wordEncoding(documents)Expected output:
`enc.Vocabulary` is `["alpha" "beta" "gamma"]` for first-seen order.Sort By Frequency
enc = wordEncoding(documents, "Order", "frequency", "MaxNumWords", 2)Expected output:
`enc.Vocabulary` contains the two most frequent words.Using wordEncoding with coding agents
Open a RunMat example with live inputs, then ask the agent to explain how wordEncoding changes the result.
Run a small wordEncoding example, explain the result, then change one input and compare the output.
FAQ
Can the result be used with doc2sequence?⌄
Yes. doc2sequence(enc, documents) returns cell arrays of 1-by-S word-index vectors.
Does wordEncoding execute on the GPU?⌄
No. It constructs host text metadata and does not use provider kernels.
Related Strings functions
Text Analytics
addDependencyDetails · addEntityDetails · addLemmaDetails · addPartOfSpeechDetails · addSentenceDetails · addTypeDetails · bagOfNgrams · bagOfWords · cosineSimilarity · doc2sequence · encode · extractFileText · extractHTMLText · fastTextWordEmbedding · findElement · getAttribute · htmlTree · ind2word · isVocabularyWord · normalizeWords · readWordEmbedding · removeLongWords · removeShortWords · removeStopWords · removeWords · stopWords · tokenDetails · tokenizedDocument · trainWordEmbedding · vaderSentimentScores · vec2word · word2ind · word2vec · writeWordEmbedding
Transform
append · deblank · erase · eraseBetween · erasePunctuation · eraseURLs · extractAfter · extractBefore · extractBetween · insertAfter · insertBefore · join · lower · pad · replace · replaceBetween · reverse · split · splitlines · strcat · strip · strjoin · strjust · strrep · strsplit · strtrim · upper
Core
blanks · char · compose · convertCharsToStrings · convertContainedStringsToChars · convertStringsToChars · genvarname · int2str · isletter · isspace · isStringScalar · isstrprop · mat2str · native2unicode · newline · num2str · sprintf · sscanf · str2double · str2num · strcmp · strcmpi · string · string.empty · strings · strlength · strncmp · strncmpi · strtok · unicode2native
Search
contains · endsWith · matches · startsWith · strfind
Pattern
digitsPattern · lettersPattern · pattern · regexpPattern · textBoundary · wildcardPattern
Open-source implementation
Unlike proprietary runtimes, every RunMat function is open-source. Read exactly how wordEncoding is executed, line by line, in Rust.
- View the source for wordEncoding in Rust on GitHub
- Learn how the RunMat runtime works
- Found a bug? Open an issue with a minimal reproduction.
About RunMat
RunMat is an open-source runtime that executes MATLAB-syntax code blazing on any GPU. It is licensed under the Apache 2.0 license.
- RunMat automatically optimizes your math for GPU execution on Apple, Nvidia, and AMD hardware. No code changes needed. Simulations that took hours now take minutes.
- Start running code in seconds. RunMat runs in the browser, on the desktop, or from the CLI. No license server, no IT ticket.