Optimize Byte Tokenization and Estimate Token Count

Multi-Part Interview Task Part 0: Understand ByteTokenizer Reference Implementation Open the byte_tokenizer.py file and study the ByteTokenizer class and the slow_tokenize method in the starter code. Write a detailed natural language description that accurately explains how the algorithm operates, so it can be faithfully re-implemented by others. Part 1: Optimize ByteTokenizer Performance Develop a faster implementation in the tokenize method that returns identical results as slow_tokenize. Maintain performance: total test time should be under 10 seconds. Preprocessing logic may be implemented in the constructor and any helper functions can be added at will. Part 2: Estimate Token Count Implement the estimate_token_count method to estimate the number of tokens returned by self.tokenize(text). Meet accuracy expectations: returns accurate count when sample_size exceeds text length, otherwise estimates should have less than 20% error, and less than 5% when sample_size>10000. Example Input {"text": "This is a simple test text.", "sample_size": 1000}