vllm-omni/tests/diffusion/offloader/test_layerwise_backend.py

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project

"""Unit tests for LayerwiseOffloadHook."""

import gc
import os
import socket
from contextlib import contextmanager

import pytest
import torch
import torch.distributed as dist
from torch import nn
from torch.distributed.tensor import DeviceMesh, DTensor, Replicate

import vllm_omni.diffusion.offloader.layerwise_backend as layerwise_backend_module
from vllm_omni.diffusion.offloader.layerwise_backend import LayerwiseOffloadHook
from vllm_omni.platforms import current_omni_platform

pytestmark = [pytest.mark.diffusion, pytest.mark.cpu, pytest.mark.core_model]


class DummyStream:
    def wait_stream(self, _stream) -> None:
        return None

    def wait_event(self, _event) -> None:
        return None


class DummyEvent:
    def record(self, _stream) -> None:
        return None


@contextmanager
def dummy_stream(_stream):
    yield None


def _find_free_port() -> int:
    with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
        s.bind(("127.0.0.1", 0))
        return int(s.getsockname()[1])


def _set_dist_env(*, rank: int, world_size: int, master_port: int) -> None:
    os.environ["RANK"] = str(rank)
    os.environ["LOCAL_RANK"] = str(rank)
    os.environ["WORLD_SIZE"] = str(world_size)
    os.environ["MASTER_ADDR"] = "127.0.0.1"
    os.environ["MASTER_PORT"] = str(master_port)


def _cleanup_distributed() -> None:
    if dist.is_initialized():
        dist.destroy_process_group()

    for key in ["MASTER_ADDR", "MASTER_PORT", "RANK", "WORLD_SIZE", "LOCAL_RANK"]:
        os.environ.pop(key, None)

    gc.collect()
    if current_omni_platform.is_available():
        current_omni_platform.empty_cache()
        current_omni_platform.synchronize()


@pytest.fixture(scope="module")
def dist_group():
    master_port = _find_free_port()
    _set_dist_env(rank=0, world_size=1, master_port=master_port)

    dist.init_process_group("gloo", rank=0, world_size=1)
    try:
        yield
    finally:
        _cleanup_distributed()


@pytest.fixture
def patched_offload_runtime(mocker):
    mocker.patch.object(layerwise_backend_module.current_omni_platform, "Stream", DummyStream)
    mocker.patch.object(layerwise_backend_module.current_omni_platform, "Event", DummyEvent)
    mocker.patch.object(layerwise_backend_module.current_omni_platform, "current_stream", lambda: DummyStream())
    mocker.patch.object(layerwise_backend_module.current_omni_platform, "stream", dummy_stream)


class TinyBlock(nn.Module):
    def __init__(self, values: torch.Tensor):
        super().__init__()
        mesh = DeviceMesh("cpu", [0])
        dtensor = DTensor.from_local(values, mesh, [Replicate()])
        self.weight = nn.Parameter(dtensor)


def _make_values(start: float) -> torch.Tensor:
    return torch.arange(start, start + 4, dtype=torch.float32)


class TestLayerwiseOffloadHook:
    def test_dtensor_wrapper_is_preserved_across_prefetch_and_offload(self, dist_group, patched_offload_runtime):
        current_block = TinyBlock(_make_values(1.0))
        next_block = TinyBlock(_make_values(10.0))

        hook = LayerwiseOffloadHook(
            next_block=next_block,
            device=torch.device("cpu"),
            stream=DummyStream(),
            pin_memory=False,
        )

        hook.initialize_hook(current_block)

        assert isinstance(next_block.weight, DTensor)
        assert next_block.weight.to_local().is_meta
        assert next_block.weight.to_local().shape == torch.Size([4])
        assert hook.dtype_metadata[next_block.weight.dtype][0]["shape"] == torch.Size([4])

        hook.prefetch_layer(non_blocking=False)
        assert isinstance(next_block.weight, DTensor)
        assert torch.equal(next_block.weight.to_local(), _make_values(10.0))
        assert next_block.weight.to_local().shape == torch.Size([4])

        hook.offload_layer()
        assert isinstance(current_block.weight, DTensor)
        assert current_block.weight.to_local().is_meta
        assert current_block.weight.to_local().shape == torch.Size([4])
        assert not hook.is_materialized