Implement a ByteTokenizer
Last updated: September 4, 2025
Quick Overview
Build a tokenizer that encodes and decodes text into byte-level tokens. Handle special characters and implement BPE-adjacent merge logic.
Perplexity
September 4, 202510
10
3,586 solved
Build a tokenizer that encodes and decodes text into byte-level tokens. Handle special characters and implement BPE-adjacent merge logic.
Directly tests understanding of how LLM tokenization works. This AI-specific coding challenge is reported in Perplexity's OA.
What the Interviewer Expects
- Implement byte-level encoding and decoding
- Handle UTF-8 multi-byte characters correctly
- Implement basic BPE merge operations
- Maintain a vocabulary with merge rules
- Write clean, well-documented code
Key Topics to Cover
How to Approach This
- Clarify input constraints and edge cases before writing code.
- Walk through your approach verbally and confirm with the interviewer before coding.
- Start with a brute force solution, then optimize. Mention time and space complexity.
- Test your solution with examples, including edge cases like empty input or duplicates.
- Consider common patterns: sliding window, two pointers, hash map, BFS/DFS, dynamic programming.
Possible Follow-up Questions
- How does BPE handle out-of-vocabulary words?
- What are the trade-offs between byte-level and word-level tokenization?
- How would you parallelize tokenization for large documents?
Sharpen Your Skills on Codemia
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Practice DSA ProblemsSample Answer
Byte-Level Encoding
```python class ByteTokenizer: def __init__(self): self.vocab = {i: bytes([i]) for i in range(256)} self.merges = {} # (token_a, ...
BPE Training
To learn merges: count all adjacent token pairs in the training corpus, find the most frequent pair, merge it into a new token, add to vocabulary, and...
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