6e00aed4d5
It comes from 0.9.1dev
[0.9.1][Feature]Moe alltoallv communication optimization for unquantized
RL training sence & alltoallv support dpo (#1547)
- vLLM version: v0.10.0
- vLLM main:
97608dc276
---------
Signed-off-by: weijinqian_v1 <weijinqian@huawei.com>
Signed-off-by: whx-sjtu <2952154980@qq.com>
Signed-off-by: curryliu <120010041@link.cuhk.edu.cn>
Signed-off-by: wangli <wangli858794774@gmail.com>
Signed-off-by: ChenTaoyu-SJTU <ctynb@qq.com>
Signed-off-by: taoxudonghaha <justsheldon@163.com>
Signed-off-by: shen-shanshan <467638484@qq.com>
Signed-off-by: Shanshan Shen <87969357+shen-shanshan@users.noreply.github.com>
Signed-off-by: leo-pony <nengjunma@outlook.com>
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Signed-off-by: MengqingCao <cmq0113@163.com>
Co-authored-by: weijinqian_v1 <weijinqian@huawei.com>
Co-authored-by: whx <56632993+whx-sjtu@users.noreply.github.com>
Co-authored-by: curryliu <99582471+Irving11-BKN@users.noreply.github.com>
Co-authored-by: Li Wang <wangli858794774@gmail.com>
Co-authored-by: TaoYu Chen <ctynb@qq.com>
Co-authored-by: taoxudonghaha <justsheldon@163.com>
Co-authored-by: Shanshan Shen <467638484@qq.com>
Co-authored-by: leo-pony <nengjunma@outlook.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
Co-authored-by: Mengqing Cao <cmq0113@163.com>
66 lines
2.5 KiB
Python
66 lines
2.5 KiB
Python
#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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# Copyright 2023 The vLLM team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# This file is a part of the vllm-ascend project.
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import pytest
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from pytest_mock import MockerFixture
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from tests.ut.base import PytestBase
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from vllm_ascend.ops.moe_dispatcher.token_dispatcher import (
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MoEAlltoAllSeqOverLapDispatcher, MoEDispatcherConfig)
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from vllm_ascend.utils import adapt_patch # noqa E402
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class TestMoEAlltoAllSeqOverLapDispatcher(PytestBase):
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@pytest.fixture
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def config(self):
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config = MoEDispatcherConfig()
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config.set_num_local_experts(2)
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config.set_num_moe_experts(4)
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config.set_moe_pad_expert_input_to_capacity(False)
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config.set_moe_expert_capacity_factor(None)
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config.set_moe_router_topk(2)
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config.set_moe_grouped_gemm(False)
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config.set_group_topk(0)
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config.set_num_groups(1)
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config.set_is_fused(False)
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return config.build()
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def mock_ep_group(self, mocker):
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mock_group = mocker.MagicMock()
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mock_group.rank_in_group = 0
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mock_group.world_size = 2
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mock_group.device_group = "mock_group"
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return mock_group
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@pytest.fixture
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def dispatcher(self, config, mocker: MockerFixture):
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mocker.patch(
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"vllm_ascend.ops.moe_dispatcher.token_dispatcher.get_ep_group",
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return_value=self.mock_ep_group(mocker))
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mocker.patch("torch.npu.current_device", return_value="cpu")
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mocker.patch("torch.npu.Stream", return_value=mocker.MagicMock)
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return MoEAlltoAllSeqOverLapDispatcher(config)
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def test_initialization(self, dispatcher, config):
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assert dispatcher.num_local_experts == config.num_local_experts
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assert dispatcher.num_experts == config.num_moe_experts
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assert dispatcher.local_expert_indices == [0, 1]
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assert dispatcher.ep_rank == 0
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assert dispatcher.ep_size == 2
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assert dispatcher.overlap_stream is not None
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