[CI/Build] vLLM cache directory for images (vllm-project#6444)

.buildkite/test-pipeline.yaml

@@ -12,7 +12,6 @@ steps:
   fast_check_only: true
   commands:
   - pytest -v -s async_engine # Async Engine
-  - bash ../.buildkite/download-images.sh # Inputs 
   - pytest -v -s test_inputs.py
   - pytest -v -s multimodal
   - pytest -v -s test_utils.py # Utils
@@ -82,7 +81,6 @@ steps:
   working_dir: "/vllm-workspace/tests"
   num_gpus: 2
   commands:
-  - bash ../.buildkite/download-images.sh
   - VLLM_TEST_SAME_HOST=1 torchrun --nproc-per-node=4 distributed/test_same_node.py
   - TEST_DIST_MODEL=facebook/opt-125m DISTRIBUTED_EXECUTOR_BACKEND=ray pytest -v -s distributed/test_basic_distributed_correctness.py
   - TEST_DIST_MODEL=meta-llama/Llama-2-7b-hf DISTRIBUTED_EXECUTOR_BACKEND=ray pytest -v -s distributed/test_basic_distributed_correctness.py
@@ -155,7 +153,6 @@ steps:
 - label: Inputs Test
   #mirror_hardwares: [amd]
   commands:
-    - bash ../.buildkite/download-images.sh
     - pytest -v -s test_inputs.py
     - pytest -v -s multimodal
 
@@ -175,7 +172,6 @@ steps:
 - label: Vision Language Models Test
   mirror_hardwares: [amd]
   commands:
-    - bash ../.buildkite/download-images.sh
     - pytest -v -s models -m vlm
 
 - label: Prefix Caching Test

examples/llava_example.py

@@ -1,20 +1,13 @@
-import os
-import subprocess
-
-from PIL import Image
-
 from vllm import LLM
-
-# The assets are located at `s3://air-example-data-2/vllm_opensource_llava/`.
-# You can use `.buildkite/download-images.sh` to download them
+from vllm.assets.image import ImageAsset
 
 
 def run_llava():
     llm = LLM(model="llava-hf/llava-1.5-7b-hf")
 
     prompt = "USER: <image>\nWhat is the content of this image?\nASSISTANT:"
 
-    image = Image.open("images/stop_sign.jpg")
+    image = ImageAsset("stop_sign").pil_image
 
     outputs = llm.generate({
         "prompt": prompt,
@@ -28,25 +21,5 @@ def run_llava():
         print(generated_text)
 
 
-def main():
-    run_llava()
-
-
 if __name__ == "__main__":
-    # Download from s3
-    s3_bucket_path = "s3://air-example-data-2/vllm_opensource_llava/"
-    local_directory = "images"
-
-    # Make sure the local directory exists or create it
-    os.makedirs(local_directory, exist_ok=True)
-
-    # Use AWS CLI to sync the directory, assume anonymous access
-    subprocess.check_call([
-        "aws",
-        "s3",
-        "sync",
-        s3_bucket_path,
-        local_directory,
-        "--no-sign-request",
-    ])
-    main()
+    run_llava()

examples/paligemma_example.py

@@ -1,20 +1,13 @@
-import os
-import subprocess
-
-from PIL import Image
-
 from vllm import LLM
-
-# The assets are located at `s3://air-example-data-2/vllm_opensource_llava/`.
-# You can use `.buildkite/download-images.sh` to download them
+from vllm.assets.image import ImageAsset
 
 
 def run_paligemma():
     llm = LLM(model="google/paligemma-3b-mix-224")
 
     prompt = "caption es"
 
-    image = Image.open("images/stop_sign.jpg")
+    image = ImageAsset("stop_sign").pil_image
 
     outputs = llm.generate({
         "prompt": prompt,
@@ -28,25 +21,5 @@ def run_paligemma():
         print(generated_text)
 
 
-def main():
-    run_paligemma()
-
-
 if __name__ == "__main__":
-    # Download from s3
-    s3_bucket_path = "s3://air-example-data-2/vllm_opensource_llava/"
-    local_directory = "images"
-
-    # Make sure the local directory exists or create it
-    os.makedirs(local_directory, exist_ok=True)
-
-    # Use AWS CLI to sync the directory, assume anonymous access
-    subprocess.check_call([
-        "aws",
-        "s3",
-        "sync",
-        s3_bucket_path,
-        local_directory,
-        "--no-sign-request",
-    ])
-    main()
+    run_paligemma()

examples/phi3v_example.py

@@ -1,12 +1,5 @@
-import os
-import subprocess
-
-from PIL import Image
-
 from vllm import LLM, SamplingParams
-
-# The assets are located at `s3://air-example-data-2/vllm_opensource_llava/`.
-# You can use `.buildkite/download-images.sh` to download them
+from vllm.assets.image import ImageAsset
 
 
 def run_phi3v():
@@ -24,7 +17,7 @@ def run_phi3v():
         max_num_seqs=5,
     )
 
-    image = Image.open("images/cherry_blossom.jpg")
+    image = ImageAsset("cherry_blossom").pil_image
 
     # single-image prompt
     prompt = "<|user|>\n<|image_1|>\nWhat is the season?<|end|>\n<|assistant|>\n"  # noqa: E501
@@ -44,19 +37,4 @@ def run_phi3v():
 
 
 if __name__ == "__main__":
-    s3_bucket_path = "s3://air-example-data-2/vllm_opensource_llava/"
-    local_directory = "images"
-
-    # Make sure the local directory exists or create it
-    os.makedirs(local_directory, exist_ok=True)
-
-    # Use AWS CLI to sync the directory, assume anonymous access
-    subprocess.check_call([
-        "aws",
-        "s3",
-        "sync",
-        s3_bucket_path,
-        local_directory,
-        "--no-sign-request",
-    ])
     run_phi3v()

tests/conftest.py

@@ -3,11 +3,7 @@
 import os
 import sys
 from collections import UserList
-from dataclasses import dataclass
-from functools import cached_property
-from pathlib import Path
-from typing import (Any, Dict, List, Literal, Optional, Tuple, TypedDict,
-                    TypeVar)
+from typing import Any, Dict, List, Optional, Tuple, TypedDict, TypeVar
 
 import pytest
 import torch
@@ -18,12 +14,12 @@
                           AutoTokenizer, BatchEncoding)
 
 from vllm import LLM, SamplingParams
+from vllm.assets.image import ImageAsset
 from vllm.config import TokenizerPoolConfig
 from vllm.distributed import (destroy_distributed_environment,
                               destroy_model_parallel)
 from vllm.inputs import TextPrompt
 from vllm.logger import init_logger
-from vllm.multimodal.utils import fetch_image
 from vllm.sequence import SampleLogprobs
 from vllm.utils import cuda_device_count_stateless, is_cpu
 
@@ -33,30 +29,13 @@
 _TEST_PROMPTS = [os.path.join(_TEST_DIR, "prompts", "example.txt")]
 _LONG_PROMPTS = [os.path.join(_TEST_DIR, "prompts", "summary.txt")]
 
-_IMAGE_DIR = Path(_TEST_DIR) / "images"
-"""You can use `.buildkite/download-images.sh` to download the assets."""
-
 
 def _read_prompts(filename: str) -> List[str]:
     with open(filename, "r") as f:
         prompts = f.readlines()
         return prompts
 
 
-@dataclass(frozen=True)
-class ImageAsset:
-    name: Literal["stop_sign", "cherry_blossom", "boardwalk"]
-
-    @cached_property
-    def pil_image(self) -> Image.Image:
-        if self.name == "boardwalk":
-            return fetch_image(
-                "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
-            )
-
-        return Image.open(_IMAGE_DIR / f"{self.name}.jpg")
-
-
 class _ImageAssetPrompts(TypedDict):
     stop_sign: str
     cherry_blossom: str

vllm/assets/base.py

@@ -0,0 +1,11 @@
+from pathlib import Path
+
+import vllm.envs as envs
+
+
+def get_cache_dir():
+    """Get the path to the cache for storing downloaded assets."""
+    path = Path(envs.VLLM_ASSETS_CACHE)
+    path.mkdir(parents=True, exist_ok=True)
+
+    return path

vllm/assets/image.py

@@ -0,0 +1,47 @@
+import shutil
+from dataclasses import dataclass
+from functools import cached_property, lru_cache
+from typing import Literal
+
+import requests
+from PIL import Image
+
+from vllm.multimodal.utils import fetch_image
+
+from .base import get_cache_dir
+
+
+@lru_cache
+def get_air_example_data_2_asset(filename: str) -> Image.Image:
+    """
+    Download and open an image from
+    ``s3://air-example-data-2/vllm_opensource_llava/``.
+    """
+    image_directory = get_cache_dir() / "air-example-data-2"
+    image_directory.mkdir(parents=True, exist_ok=True)
+
+    image_path = image_directory / filename
+    if not image_path.exists():
+        base_url = "https://air-example-data-2.s3.us-west-2.amazonaws.com/vllm_opensource_llava"
+
+        with requests.get(f"{base_url}/{filename}", stream=True) as response:
+            response.raise_for_status()
+
+            with image_path.open("wb") as f:
+                shutil.copyfileobj(response.raw, f)
+
+    return Image.open(image_path)
+
+
+@dataclass(frozen=True)
+class ImageAsset:
+    name: Literal["stop_sign", "cherry_blossom", "boardwalk"]
+
+    @cached_property
+    def pil_image(self) -> Image.Image:
+        if self.name == "boardwalk":
+            return fetch_image(
+                "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
+            )
+
+        return get_air_example_data_2_asset(f"{self.name}.jpg")

vllm/distributed/device_communicators/custom_all_reduce_utils.py

@@ -189,10 +189,10 @@ def gpu_p2p_access_check(src: int, tgt: int) -> bool:
     cuda_visible_devices = envs.CUDA_VISIBLE_DEVICES
     if cuda_visible_devices is None:
         cuda_visible_devices = ",".join(str(i) for i in range(num_dev))
-    VLLM_CONFIG_ROOT = envs.VLLM_CONFIG_ROOT
-    path = os.path.expanduser(
-        f"{VLLM_CONFIG_ROOT}/vllm/gpu_p2p_access_cache_for_{cuda_visible_devices}.json"
-    )
+
+    path = os.path.join(
+        envs.VLLM_CACHE_ROOT,
+        f"gpu_p2p_access_cache_for_{cuda_visible_devices}.json")
     os.makedirs(os.path.dirname(path), exist_ok=True)
     from vllm.distributed.parallel_state import get_world_group
     if ((not is_distributed or get_world_group().local_rank == 0)