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Move to a faster base64 implementation (#19984)

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Signed-off-by: h-avsha <avshalom.manevich@hcompany.ai>
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h-avsha 2025-06-25 06:33:51 +03:00 committed by GitHub
parent 2273ec322c
commit 3443aaf8dd
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2 changed files with 6 additions and 5 deletions
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1
requirements/common.txt
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@ -44,3 +44,4 @@ watchfiles # required for http server to monitor the updates of TLS files
python-json-logger # Used by logging as per examples/others/logging_configuration.md
scipy # Required for phi-4-multimodal-instruct
ninja # Required for xgrammar, rocm, tpu, xpu
pybase64 # fast base64 implementation

10
vllm/multimodal/image.py
View File

@ -1,10 +1,10 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import base64
from io import BytesIO
from pathlib import Path
import pybase64
import torch
from PIL import Image
@ -55,7 +55,7 @@ class ImageMediaIO(MediaIO[Image.Image]):
return convert_image_mode(image, self.image_mode)
def load_base64(self, media_type: str, data: str) -> Image.Image:
return self.load_bytes(base64.b64decode(data))
return self.load_bytes(pybase64.b64decode(data, validate=True))
def load_file(self, filepath: Path) -> Image.Image:
image = Image.open(filepath)
@ -75,7 +75,7 @@ class ImageMediaIO(MediaIO[Image.Image]):
image.save(buffer, image_format)
data = buffer.getvalue()
return base64.b64encode(data).decode('utf-8')
return pybase64.b64encode(data).decode('utf-8')
class ImageEmbeddingMediaIO(MediaIO[torch.Tensor]):
@ -88,10 +88,10 @@ class ImageEmbeddingMediaIO(MediaIO[torch.Tensor]):
return torch.load(buffer, weights_only=True)
def load_base64(self, media_type: str, data: str) -> torch.Tensor:
return self.load_bytes(base64.b64decode(data))
return self.load_bytes(pybase64.b64decode(data, validate=True))
def load_file(self, filepath: Path) -> torch.Tensor:
return torch.load(filepath, weights_only=True)
def encode_base64(self, media: torch.Tensor) -> str:
return base64.b64encode(media.numpy()).decode('utf-8')
return pybase64.b64encode(media.numpy()).decode('utf-8')