Validating Runai Model Streamer Integration with S3 Object Storage (#29320)

Signed-off-by: Noa Neria <noa@run.ai>

tests/model_executor/model_loader/runai_streamer_loader/conftest.py

@@ -0,0 +1,39 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+from vllm.utils.network_utils import get_distributed_init_method, get_ip, get_open_port
+from vllm.v1.executor import UniProcExecutor
+from vllm.v1.worker.worker_base import WorkerWrapperBase
+
+
+# This is a dummy executor for patching in test_runai_model_streamer_s3.py.
+# We cannot use vllm_runner fixture here, because it spawns worker process.
+# The worker process reimports the patched entities, and the patch is not applied.
+class RunaiDummyExecutor(UniProcExecutor):
+    def _init_executor(self) -> None:
+        distributed_init_method = get_distributed_init_method(get_ip(), get_open_port())
+
+        local_rank = 0
+        rank = 0
+        is_driver_worker = True
+
+        device_info = self.vllm_config.device_config.device.__str__().split(":")
+        if len(device_info) > 1:
+            local_rank = int(device_info[1])
+
+        worker_rpc_kwargs = dict(
+            vllm_config=self.vllm_config,
+            local_rank=local_rank,
+            rank=rank,
+            distributed_init_method=distributed_init_method,
+            is_driver_worker=is_driver_worker,
+        )
+
+        wrapper_kwargs = {
+            "vllm_config": self.vllm_config,
+        }
+
+        self.driver_worker = WorkerWrapperBase(**wrapper_kwargs)
+
+        self.collective_rpc("init_worker", args=([worker_rpc_kwargs],))
+        self.collective_rpc("init_device")

tests/model_executor/model_loader/runai_streamer_loader/test_runai_model_streamer_s3.py

@@ -0,0 +1,52 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+from pathlib import Path
+
+from huggingface_hub import snapshot_download
+from runai_model_streamer.safetensors_streamer.streamer_mock import StreamerPatcher
+
+from vllm.engine.arg_utils import EngineArgs
+
+from .conftest import RunaiDummyExecutor
+
+load_format = "runai_streamer"
+test_model = "openai-community/gpt2"
+
+
+def test_runai_model_loader_download_files_s3_mocked_with_patch(
+    vllm_runner,
+    tmp_path: Path,
+    monkeypatch,
+):
+    patcher = StreamerPatcher(str(tmp_path))
+
+    test_mock_s3_model = "s3://my-mock-bucket/gpt2/"
+
+    # Download model from HF
+    mock_model_dir = f"{tmp_path}/gpt2"
+    snapshot_download(repo_id=test_model, local_dir=mock_model_dir)
+
+    monkeypatch.setattr(
+        "vllm.transformers_utils.runai_utils.runai_list_safetensors",
+        patcher.shim_list_safetensors,
+    )
+    monkeypatch.setattr(
+        "vllm.transformers_utils.runai_utils.runai_pull_files",
+        patcher.shim_pull_files,
+    )
+    monkeypatch.setattr(
+        "vllm.model_executor.model_loader.weight_utils.SafetensorsStreamer",
+        patcher.create_mock_streamer,
+    )
+
+    engine_args = EngineArgs(
+        model=test_mock_s3_model,
+        load_format=load_format,
+        tensor_parallel_size=1,
+    )
+
+    vllm_config = engine_args.create_engine_config()
+
+    executor = RunaiDummyExecutor(vllm_config)
+    executor.driver_worker.load_model()