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https://github.com/mii443/tokenizers.git
synced 2025-08-22 16:25:30 +00:00
Fixing benchmark2.
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@ -25,12 +25,12 @@ def format_byte_size(num_bytes: int) -> Tuple[str, str]:
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return f"{num_bytes_f:.2f} PB", "PB"
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def benchmark_batch(model: str, documents: list[str], num_threads: int) -> None:
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def benchmark_batch(model: str, documents: list[str], num_threads: int, document_length: float) -> None:
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os.environ["RAYON_NUM_THREADS"] = str(num_threads)
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num_bytes = sum(map(len, map(str.encode, documents)))
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readable_size, unit = format_byte_size(num_bytes)
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print(f"==============")
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print(f"num_threads: {num_threads}, data size: {readable_size}, documents: {len(documents)}")
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print(f"num_threads: {num_threads}, data size: {readable_size}, documents: {len(documents)} Avg Length: {document_length:.0f}")
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filename = hf_hub_download(MODEL_ID, "original/tokenizer.model")
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mergeable_ranks = load_tiktoken_bpe(filename)
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pat_str = r"(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+"
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@ -82,24 +82,30 @@ def benchmark_batch(model: str, documents: list[str], num_threads: int) -> None:
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def test(model: str, dataset: str, dataset_config: str, threads: List[int]):
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dataset_xnli = load_dataset(dataset, dataset_config)
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input_lengths = [(10, False), (10_000, False), (10_000, True)] # Example input lengths
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# input_lengths = [(10, False), (10_000, False), (10_000, True)] # Example input lengths
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input_lengths = [(10_000, False, True), (10_000, False, False)]
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for num_threads in threads:
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for length, fuse in input_lengths:
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for length, fuse, long in input_lengths:
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documents = []
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for i, item in enumerate(dataset_xnli["train"]):
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if i >= length:
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break
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documents.append("".join(item["premise"].values()))
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if long:
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documents.append("".join(item["premise"].values()))
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else:
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documents.append(item["premise"]["en"])
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if fuse:
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documents=["".join(documents)]
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document_length = sum(len(d) for d in documents) / len(documents)
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# Rayon thread pool is global to a process, we need to launch
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# separate processes in order to accurately use the correct number of threads.
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# Otherwise, we're simply running tokenizers in whatever tests comes first.
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# tokenizers does NOT provide a method to change the number of threads during
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# runtime.
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p = Process(target=benchmark_batch, args=(model, documents, num_threads))
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p = Process(target=benchmark_batch, args=(model, documents, num_threads, document_length))
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p.start()
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p.join()
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