Implement dynamic batching for token decoding

You are given a black-box “simulated language model” interface that can advance many sequences in a batch. ## Model interface - Tokens are integers. - `model_next(batch_prefixes) -> next_tokens` - `batch_prefixes` is a list of token lists, one per active sequence in the current batch. - `next_tokens` is a list of integers of the same length, where `next_tokens[i]` is the next generated token for `batch_prefixes[i]`. ## Requests Each request/sequence has: - `prompt_tokens`: initial prefix tokens - `max_tokens`: maximum number of *generated* tokens allowed (not counting the prompt) - A stopping rule: - either a `stop_token` (single token), or - a `stop_sequence` (a list of tokens that, when it appears as a suffix of the generated output, ends generation) - A callback to return the final generated tokens (or you may collect results to return at the end). ## Batch execution requirement Implement a decoding/sampling engine with **dynamic batching**: - There is a fixed batch capacity `B`. - Requests arrive in a waiting queue (you can assume they are all available initially, or you can model an input queue). - You repeatedly call `model_next` to advance active sequences. - Sequences may finish at different times due to: - reaching `max_tokens`, or - hitting the stop condition. - When a sequence finishes, its slot becomes free and should be **refilled** from the waiting queue if possible. - Near the end, the batch may be partially filled; your code must handle `len(active) < B` correctly. ## Correctness requirement Maintain a correct mapping between **batch slots** and **requests** so that tokens and final outputs are never mixed up after refilling (e.g., via a `slot_id -> request_id` mapping). ## Task Write a function (or class) that runs this dynamic-batching decoding loop until all requests are completed, and returns (or callbacks) the generated outputs per request. Clearly define: - your data structures (active slots, waiting queue, per-request state), - the main loop and termination condition, - how you detect stop conditions (especially `stop_sequence`), - and how you handle partially filled batches.