Padding token

As explained in Deep Learning with R, Third Edition

A padding token is a placeholder token inserted to make sequences conform to a common length and carries no sequence content.

How Deep Learning with R, Third Edition covers it

How deep it goes

Explains placeholder placement, fixed-length packing, truncation, masking, and framework configuration without detailing mask propagation internals.

Examples

Demonstrates padded movie-review sequences, RoBERTa start-end packing, and batched token IDs paired with Boolean padding masks.

What it assumes

Assumes tokenization and integer token IDs, while demonstrating how padding and its mask enter preprocessing from that point.

What you can do after

Apply it via KerasHub’s StartEndPacker or Keras Embedding masking when preparing variable-length text for neural models.

How it connects

Connects padding tokens to tokenization, token packing, sequence length, padding masks, embeddings, and recurrent or Transformer models.

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Also explained in

• 

  liveBookmanning.com
  Natural Language Processing in Action, Second EditionA padding token is a special token used to extend shorter sequences to a common length within a batch.
• 

  liveBookmanning.com
  Build a Text-to-Image Generator (from Scratch)A padding token is a special marker appended to shorter sequences so that sequences in a batch have equal length.
• 

  liveBookmanning.com
  Hugging Face in ActionA padding token is a special token inserted into shorter sequences so batched sequences have a uniform length.

Compare how 4 books explain padding token →

Related concepts

• tokenkind of · A token is a discrete unit of text, such as a word, word fragment, character, or symbol, represented and processed as an element by a language model.
• batchingconfigures · Batching is the grouping of multiple data items, requests, or operations so they can be processed together as a unit.
• batch sizepart of · Batch size is the number of items grouped together for processing or computation as a single batch.
• attention_maskcontrasts with · An attention mask is a tensor or indicator structure specifying which sequence positions may participate in attention or other model computations, often excluding padding.
• Vectorization layerconfigured by · A Keras preprocessing layer that tokenizes text and converts it into numerical representations using a vocabulary and configurable encoding.
• paddingpart of · Padding is the addition of extra space, values, or data around or within a structure to satisfy size, alignment, layout, or processing requirements.

This explainer was generated by Manning's knowledge graph from the text of Deep Learning with R, Third Edition. The section links point to the parts of the book it draws on.