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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
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For reviewers, you should be able to test this with: If you get an error like then consider Click for example scriptimport random
import string
import time
import psutil
from tokenizers import Tokenizer
tokenizer = Tokenizer.from_pretrained('xlm-roberta-base')
def random_string(length: int) -> str:
return ''.join(random.choices(string.ascii_uppercase + string.digits, k=length))
for iteration in range(99999999):
start_t = time.time()
tokenizer.encode_batch([random_string(12345) for _ in range(200)])
memory_usage_in_MiB = psutil.Process().memory_info().rss / (1024 * 1024)
delta_t = time.time() - start_t
print(f"{iteration:02d}: {memory_usage_in_MiB:.2f}MB, {delta_t:.2f}s")Without clearing cacheWith clearing cacheIt seems to work now, switching between ~350 and ~580 MBs, and a constant latency, matching the lowest latency for the baseline. Well done finding the issue @ArthurZucker
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Yep, I can also do:
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Merged
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I met an error: AttributeError: 'tokenizers.models.WordPiece' object has no attribute 'clear_cache', could anyone tell me how to fix it? |
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Fixes #1539
Tried the provided script with this:
and had no "leaks"