[Multimodal][Perf] Use `pybase64` instead of `base64` (#7724)

python/pyproject.toml

@@ -38,6 +38,7 @@ runtime_common = [
     "psutil",
     "pydantic",
     "pynvml",
+    "pybase64",
     "python-multipart",
     "pyzmq>=25.1.2",
     "soundfile==0.13.1",

python/sglang/bench_serving.py

@@ -814,9 +814,9 @@ def sample_mmmu_requests(
         List of tuples (prompt, prompt_token_len, output_token_len).
     """
     try:
-        import base64
         import io
 
+        import pybase64
         from datasets import load_dataset
     except ImportError:
         raise ImportError("Please install datasets: pip install datasets")
@@ -867,7 +867,7 @@ def sample_mmmu_requests(
                     # Encode image to base64
                     buffered = io.BytesIO()
                     image.save(buffered, format="JPEG")
-                    img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")
+                    img_str = pybase64.b64encode(buffered.getvalue()).decode("utf-8")
                     image_data = f"data:image/jpeg;base64,{img_str}"
                 else:
                     continue

python/sglang/srt/entrypoints/http_server_engine.py

-import base64
 import copy
 import dataclasses
 import multiprocessing
@@ -7,6 +6,7 @@ import threading
 import time
 from typing import Any, Dict, List, Optional, Tuple, Union
 
+import pybase64
 import requests
 import torch
 import torch.distributed as dist

python/sglang/srt/multimodal/mm_utils.py

@@ -28,12 +28,12 @@ LLaVA-Onevision : https://arxiv.org/pdf/2408.03326
 
 """
 import ast
-import base64
 import math
 import re
 from io import BytesIO
 
 import numpy as np
+import pybase64
 from PIL import Image
 
 from sglang.srt.utils import flatten_nested_list
@@ -252,7 +252,7 @@ def process_anyres_image(image, processor, grid_pinpoints):
 
 
 def load_image_from_base64(image):
-    return Image.open(BytesIO(base64.b64decode(image)))
+    return Image.open(BytesIO(pybase64.b64decode(image, validate=True)))
 
 
 def expand2square(pil_img, background_color):

python/sglang/srt/utils.py

@@ -15,7 +15,6 @@
 
 from __future__ import annotations
 
-import base64
 import builtins
 import ctypes
 import dataclasses
@@ -68,6 +67,7 @@ from typing import (
 
 import numpy as np
 import psutil
+import pybase64
 import requests
 import torch
 import torch.distributed
@@ -616,7 +616,7 @@ def decode_video_base64(video_base64):
     from PIL import Image
 
     # Decode the base64 string
-    video_bytes = base64.b64decode(video_base64)
+    video_bytes = pybase64.b64decode(video_base64, validate=True)
 
     # Placeholder for the start indices of each PNG image
     img_starts = []
@@ -702,7 +702,9 @@ def load_audio(audio_file: str, sr: int = 16000, mono: bool = True) -> np.ndarra
         audio, original_sr = sf.read(BytesIO(audio_file))
     elif audio_file.startswith("data:"):
         audio_file = audio_file.split(",")[1]
-        audio, original_sr = sf.read(BytesIO(base64.b64decode(audio_file)))
+        audio, original_sr = sf.read(
+            BytesIO(pybase64.b64decode(audio_file, validate=True))
+        )
     elif audio_file.startswith("http://") or audio_file.startswith("https://"):
         timeout = int(os.getenv("REQUEST_TIMEOUT", "5"))
         response = requests.get(audio_file, stream=True, timeout=timeout)
@@ -771,12 +773,12 @@ def load_image(
         image = Image.open(image_file)
     elif image_file.startswith("data:"):
         image_file = image_file.split(",")[1]
-        image = Image.open(BytesIO(base64.b64decode(image_file)))
+        image = Image.open(BytesIO(pybase64.b64decode(image_file, validate=True)))
     elif image_file.startswith("video:"):
         image_file = image_file.replace("video:", "")
         image, image_size = decode_video_base64(image_file)
     elif isinstance(image_file, str):
-        image = Image.open(BytesIO(base64.b64decode(image_file)))
+        image = Image.open(BytesIO(pybase64.b64decode(image_file, validate=True)))
     else:
         raise ValueError(f"Invalid image: {image}")
 
@@ -1866,7 +1868,7 @@ class MultiprocessingSerializer:
 
         if output_str:
             # Convert bytes to base64-encoded string
-            output = base64.b64encode(output).decode("utf-8")
+            output = pybase64.b64encode(output).decode("utf-8")
 
         return output
 
@@ -1883,7 +1885,7 @@ class MultiprocessingSerializer:
         """
         if isinstance(data, str):
             # Decode base64 string to bytes
-            data = base64.b64decode(data)
+            data = pybase64.b64decode(data, validate=True)
 
         return ForkingPickler.loads(data)
 

python/sglang/utils.py

 """Common utilities"""
 
-import base64
 import importlib
 import json
 import logging
@@ -20,6 +19,7 @@ from json import dumps
 from typing import Any, Callable, List, Optional, Tuple, Type, Union
 
 import numpy as np
+import pybase64
 import requests
 from IPython.display import HTML, display
 from pydantic import BaseModel
@@ -148,15 +148,15 @@ def encode_image_base64(image_path: Union[str, bytes]):
     if isinstance(image_path, str):
         with open(image_path, "rb") as image_file:
             data = image_file.read()
-            return base64.b64encode(data).decode("utf-8")
+            return pybase64.b64encode(data).decode("utf-8")
     elif isinstance(image_path, bytes):
-        return base64.b64encode(image_path).decode("utf-8")
+        return pybase64.b64encode(image_path).decode("utf-8")
     else:
         # image_path is PIL.WebPImagePlugin.WebPImageFile
         image = image_path
         buffered = BytesIO()
         image.save(buffered, format="PNG")
-        return base64.b64encode(buffered.getvalue()).decode("utf-8")
+        return pybase64.b64encode(buffered.getvalue()).decode("utf-8")
 
 
 def encode_frame(frame):
@@ -223,7 +223,7 @@ def encode_video_base64(video_path: str, num_frames: int = 16):
     video_bytes = b"".join(encoded_frames)
 
     # Encode the concatenated bytes to base64
-    video_base64 = "video:" + base64.b64encode(video_bytes).decode("utf-8")
+    video_base64 = "video:" + pybase64.b64encode(video_bytes).decode("utf-8")
 
     return video_base64
 

test/srt/test_vision_openai_server_common.py

 import base64
-import copy
 import io
 import json
 import os