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83 lines
2.5 KiB
83 lines
2.5 KiB
import pytest
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import torch.distributed as dist
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import torch.nn as nn
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import colossalai
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from colossalai.moe.experts import MLPExperts
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from colossalai.moe.manager import MOE_MANAGER
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from colossalai.moe.utils import sync_moe_model_param
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from colossalai.testing import assert_equal_in_group, rerun_if_address_is_in_use, spawn
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from colossalai.utils import get_current_device
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HIDDEN_SIZE = 4
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INTERMEDIATE_SIZE = 8
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def run_moe_init(expert_parallel):
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MOE_MANAGER.__init__()
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MOE_MANAGER.setup(parallel=expert_parallel)
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expert_args = dict(
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hidden_size=HIDDEN_SIZE,
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intermediate_size=INTERMEDIATE_SIZE,
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expert_parallel=expert_parallel,
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)
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exp0 = MLPExperts(1, **expert_args)
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exp1 = MLPExperts(2, **expert_args)
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exp2 = MLPExperts(4, **expert_args)
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if expert_parallel == "EP":
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assert exp0.num_local_experts == 1
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assert exp1.num_local_experts == 1
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assert exp2.num_local_experts == 2
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else:
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assert exp0.num_local_experts == 1
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assert exp1.num_local_experts == 2
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assert exp2.num_local_experts == 4
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parallel_info_dict = MOE_MANAGER.parallel_info_dict
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rank = dist.get_rank()
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# group creation assert
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assert len(parallel_info_dict) == 2
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assert dist.get_rank(parallel_info_dict[2].ep_group) == rank % 2
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assert dist.get_rank(parallel_info_dict[1].ep_group) == 0
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assert dist.get_rank(parallel_info_dict[2].dp_group) == rank // 2
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assert dist.get_rank(parallel_info_dict[1].dp_group) == rank
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model = nn.ModuleList([exp0, exp1, exp2])
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model = model.to(get_current_device())
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sync_moe_model_param(model)
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# MOE experts layout success when ep_size = 1
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assert_equal_in_group(exp0.wi.data, parallel_info_dict[1].dp_group)
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assert_equal_in_group(exp0.wo.data, parallel_info_dict[1].dp_group)
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# MOE experts layout success when ep_size = 2
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assert_equal_in_group(exp1.wi.data, parallel_info_dict[2].dp_group)
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assert_equal_in_group(exp1.wo.data, parallel_info_dict[2].dp_group)
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def _run_test(rank, world_size, port, expert_parallel):
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colossalai.launch(
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config=dict(),
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rank=rank,
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world_size=world_size,
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host="localhost",
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port=port,
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backend="nccl",
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)
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run_moe_init(expert_parallel)
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@pytest.mark.dist
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@pytest.mark.parametrize("expert_parallel", ["EP", "TP"])
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@rerun_if_address_is_in_use()
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def test_moe_initialization(expert_parallel):
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spawn(_run_test, 2, expert_parallel=expert_parallel)
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if __name__ == "__main__":
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test_moe_initialization("EP")
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test_moe_initialization("TP")
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