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Fixing benchmark2.

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This commit is contained in:
Nicolas Patry
2024-08-01 11:31:31 +02:00
parent c6f2c0b057
commit 1df498a186
1 changed files with 12 additions and 6 deletions
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18
bindings/python/benches/test_tiktoken.py
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@ -25,12 +25,12 @@ def format_byte_size(num_bytes: int) -> Tuple[str, str]:
return f"{num_bytes_f:.2f} PB", "PB" return f"{num_bytes_f:.2f} PB", "PB"
def benchmark_batch(model: str, documents: list[str], num_threads: int) -> None: def benchmark_batch(model: str, documents: list[str], num_threads: int, document_length: float) -> None:
os.environ["RAYON_NUM_THREADS"] = str(num_threads) os.environ["RAYON_NUM_THREADS"] = str(num_threads)
num_bytes = sum(map(len, map(str.encode, documents))) num_bytes = sum(map(len, map(str.encode, documents)))
readable_size, unit = format_byte_size(num_bytes) readable_size, unit = format_byte_size(num_bytes)
print(f"==============") print(f"==============")
print(f"num_threads: {num_threads}, data size: {readable_size}, documents: {len(documents)}") print(f"num_threads: {num_threads}, data size: {readable_size}, documents: {len(documents)} Avg Length: {document_length:.0f}")
filename = hf_hub_download(MODEL_ID, "original/tokenizer.model") filename = hf_hub_download(MODEL_ID, "original/tokenizer.model")
mergeable_ranks = load_tiktoken_bpe(filename) mergeable_ranks = load_tiktoken_bpe(filename)
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+" 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+"
@ -82,24 +82,30 @@ def benchmark_batch(model: str, documents: list[str], num_threads: int) -> None:
def test(model: str, dataset: str, dataset_config: str, threads: List[int]): def test(model: str, dataset: str, dataset_config: str, threads: List[int]):
dataset_xnli = load_dataset(dataset, dataset_config) dataset_xnli = load_dataset(dataset, dataset_config)
input_lengths = [(10, False), (10_000, False), (10_000, True)] # Example input lengths # input_lengths = [(10, False), (10_000, False), (10_000, True)] # Example input lengths
input_lengths = [(10_000, False, True), (10_000, False, False)]
for num_threads in threads: for num_threads in threads:
for length, fuse in input_lengths: for length, fuse, long in input_lengths:
documents = [] documents = []
for i, item in enumerate(dataset_xnli["train"]): for i, item in enumerate(dataset_xnli["train"]):
if i >= length: if i >= length:
break break
documents.append("".join(item["premise"].values())) if long:
documents.append("".join(item["premise"].values()))
else:
documents.append(item["premise"]["en"])
if fuse: if fuse:
documents=["".join(documents)] documents=["".join(documents)]
document_length = sum(len(d) for d in documents) / len(documents)
# Rayon thread pool is global to a process, we need to launch # Rayon thread pool is global to a process, we need to launch
# separate processes in order to accurately use the correct number of threads. # separate processes in order to accurately use the correct number of threads.
# Otherwise, we're simply running tokenizers in whatever tests comes first. # Otherwise, we're simply running tokenizers in whatever tests comes first.
# tokenizers does NOT provide a method to change the number of threads during # tokenizers does NOT provide a method to change the number of threads during
# runtime. # runtime.
p = Process(target=benchmark_batch, args=(model, documents, num_threads)) p = Process(target=benchmark_batch, args=(model, documents, num_threads, document_length))
p.start() p.start()
p.join() p.join()