exo/test/test_tokenizers.py

from transformers import AutoTokenizer, AutoProcessor
from exo.models import model_base_shards


def test_tokenizer(name, tokenizer, verbose=False):
    print(f"--- {name} ({tokenizer.__class__.__name__}) ---")
    text = "Hello! How can I assist you today? Let me know if you need help with something or just want to chat."
    encoded = tokenizer.encode(text)
    decoded = tokenizer.decode(encoded)

    print(f"{encoded=}")
    print(f"{decoded=}")

    reconstructed = ""
    for token in encoded:
      if verbose:
        print(f"{token=}")
        print(f"{tokenizer.decode([token])=}")
      reconstructed += tokenizer.decode([token])
    print(f"{reconstructed=}")

    strip_tokens = lambda s: s.lstrip(tokenizer.decode([tokenizer.bos_token_id])).rstrip(tokenizer.decode([tokenizer.eos_token_id]))
    assert text == strip_tokens(decoded) == strip_tokens(reconstructed)

ignore = ["TriAiExperiments/SFR-Iterative-DPO-LLaMA-3-70B-R", "mlx-community/DeepSeek-Coder-V2-Lite-Instruct-4bit-mlx", "llava-hf/llava-1.5-7b-hf"]
models = [shard.model_id for shards in model_base_shards.values() for shard in shards.values() if shard.model_id not in ignore]

import os
verbose = os.environ.get("VERBOSE", "0").lower() == "1"
for m in models:
    # TODO: figure out why use_fast=False is giving inconsistent behaviour (no spaces decoding invididual tokens) for Mistral-Large-Instruct-2407-4bit
    # test_tokenizer(m, AutoProcessor.from_pretrained(m, use_fast=False), verbose)
    test_tokenizer(m, AutoProcessor.from_pretrained(m, use_fast=True), verbose)
    test_tokenizer(m, AutoTokenizer.from_pretrained(m), verbose)