Optimize LLM Encoding | Dataford Interview Questions

How would you optimize LLM encoding for performance and efficiency? Implement byte-pair encoding over an initial token sequence using merge priorities, always applying the lowest-priority adjacent pair and breaking ties from left to right. The function receives a list of token strings and an ordered list of merge rules, and returns the final merged token list. Use a data structure that avoids rescanning every adjacent pair after each merge.

Constraints

0 <= len(tokens) <= 5000
0 <= len(merge_rules) <= 5000
Each token is a non-empty string
Each merge rule contains exactly two non-empty strings
Merge rules are ordered from highest priority to lowest priority
A merge rule is applied only to adjacent tokens whose current strings exactly match the rule

Function Signature

def bpe_encode(tokens, merge_rules):

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Problem

Constraints

0 <= len(tokens) <= 5000
0 <= len(merge_rules) <= 5000
Each token is a non-empty string
Each merge rule contains exactly two non-empty strings
Merge rules are ordered from highest priority to lowest priority
A merge rule is applied only to adjacent tokens whose current strings exactly match the rule

Function Signature

def bpe_encode(tokens, merge_rules):

Your question is Optimize LLM Encoding. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.