[Test] Isolate CPU collective workers from the host GPU platform

Signed-off-by: tzhouam <tzhouam@connect.ust.hk>

tests/helpers/distributed.py

@@ -0,0 +1,62 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+"""Process and platform setup for isolated collective test workers."""
+
+from collections.abc import Callable
+from multiprocessing.context import BaseContext
+
+import torch
+
+
+def collective_context(device_kind: str) -> BaseContext:
+    """Reuse imports in a clean CPU forkserver; CUDA workers use spawn."""
+    if device_kind == "cpu" and "forkserver" in torch.multiprocessing.get_all_start_methods():
+        torch.multiprocessing.set_forkserver_preload(["tests.helpers.cpu_collective_server"])
+        return torch.multiprocessing.get_context("forkserver")
+    return torch.multiprocessing.get_context("spawn")
+
+
+def start_collective_workers(
+    worker: Callable[..., None], *, args: tuple[object, ...], nprocs: int, device_kind: str
+) -> None:
+    context = collective_context(device_kind)
+    if context.get_start_method() == "spawn":
+        torch.multiprocessing.spawn(worker, args=args, nprocs=nprocs)
+    else:
+        torch.multiprocessing.start_processes(worker, args=args, nprocs=nprocs, start_method=context.get_start_method())
+
+
+def configure_cpu_collective_worker() -> None:
+    """Select CPU platforms inside a spawned worker that only uses Gloo.
+
+    Upstream coordinators resolve local ranks through the selected
+    platform's visible devices. CPU ranks can outnumber visible GPUs, so they
+    must use the CPU platform even when the test host has CUDA installed.
+    The worker still creates real process groups and runs real collectives.
+    """
+    import vllm.platforms
+    from vllm.platforms.cpu import CpuPlatform
+
+    from vllm_omni.diffusion.distributed import comm, group_coordinator, parallel_state
+    from vllm_omni.platforms.interface import UnspecifiedOmniPlatform
+
+    class CpuCollectivePlatform(UnspecifiedOmniPlatform):
+        dist_backend = "gloo"
+
+        @classmethod
+        def get_device_count(cls) -> int:
+            # CPU tensors share one logical device regardless of process rank.
+            return 1
+
+        @classmethod
+        def set_device(cls, device: torch.device) -> None:
+            assert device.type == "cpu"
+
+        @classmethod
+        def synchronize(cls) -> None:
+            pass
+
+    vllm.platforms.current_platform = CpuPlatform()
+    platform = CpuCollectivePlatform()
+    for module in (comm, group_coordinator, parallel_state):
+        module.current_omni_platform = platform