mirror of https://github.com/hpcaitech/ColossalAI
78 lines
3.1 KiB
Python
78 lines
3.1 KiB
Python
import pytest
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import colossalai
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import torch
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import torch.multiprocessing as mp
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from colossalai.testing import rerun_if_address_is_in_use
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from colossalai.utils.cuda import get_current_device
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from colossalai.utils import free_port
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from colossalai.utils.model.colo_init_context import ColoInitContext
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from colossalai.gemini import ChunkManager
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from functools import partial
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from tests.components_to_test.registry import non_distributed_component_funcs
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from colossalai.nn.parallel import ZeroDDP, ColoDDP
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from colossalai.gemini.gemini_mgr import GeminiManager
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from typing import Callable
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from collections import OrderedDict
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from colossalai.tensor import ProcessGroup, ColoParameter
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def check_state_dict_equal(state_dict: OrderedDict, other_state_dict: OrderedDict):
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for (k1, t1), (k2, t2) in zip(state_dict.items(), other_state_dict.items()):
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assert k1 == k2
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assert torch.allclose(t1, t2, atol=1e-3, rtol=1e-3)
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def init_ddp(module: torch.nn.Module) -> ColoDDP:
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pg = ProcessGroup()
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return ColoDDP(module, process_group=pg)
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def init_ddpv2(module: torch.nn.Module, use_chunk: bool = False, use_zero: bool = False) -> ZeroDDP:
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chunk_size = ChunkManager.search_chunk_size(module, 64, 4) if use_chunk else None
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chunk_manager = ChunkManager(chunk_size, enable_distributed_storage=use_zero)
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gemini_manager = GeminiManager('cuda', chunk_manager)
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pg = ProcessGroup()
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return ZeroDDP(module, gemini_manager, process_group=pg)
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def run_state_dict(ddp_init_func: Callable[[torch.nn.Module], ColoDDP]):
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get_components_func = non_distributed_component_funcs.get_callable('nested_model')
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model_builder, train_dataloader, test_dataloader, optimizer_class, criterion = get_components_func()
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torch_model = model_builder().cuda()
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with ColoInitContext(device=get_current_device()):
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model = model_builder()
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model = ddp_init_func(model)
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torch_state_dict = torch_model.state_dict()
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for param in model.parameters():
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if isinstance(param, ColoParameter):
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assert param.get_process_group() is not None
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model.load_state_dict(torch_state_dict)
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for param in model.parameters():
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if isinstance(param, ColoParameter):
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assert param.get_process_group() is not None
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state_dict = model.state_dict()
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check_state_dict_equal(torch_state_dict, state_dict)
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def run_dist(rank, world_size, port):
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colossalai.launch(config={}, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
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run_state_dict(init_ddp)
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run_state_dict(partial(init_ddpv2, use_chunk=False, use_zero=False))
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run_state_dict(partial(init_ddpv2, use_chunk=False, use_zero=True))
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run_state_dict(partial(init_ddpv2, use_chunk=True, use_zero=False))
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run_state_dict(partial(init_ddpv2, use_chunk=True, use_zero=True))
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@pytest.mark.dist
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@pytest.mark.parametrize('world_size', [1, 2])
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@rerun_if_address_is_in_use()
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def test_state_dict(world_size):
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run_func = partial(run_dist, world_size=world_size, port=free_port())
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mp.spawn(run_func, nprocs=world_size)
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if __name__ == '__main__':
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test_state_dict(2)
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