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from collections import OrderedDict
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import pytest
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import torch
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import colossalai
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from colossalai.nn.parallel import ColoDDP
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from colossalai.tensor import ColoParameter, ProcessGroup
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from colossalai.testing import rerun_if_address_is_in_use, spawn
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from colossalai.utils.cuda import get_current_device
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from colossalai.zero import ColoInitContext
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from tests.components_to_test.registry import non_distributed_component_funcs
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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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if t1.device != t2.device:
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temp_t2 = t2.to(t1.device)
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else:
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temp_t2 = t2
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assert torch.equal(t1, temp_t2), "\t{}\n\t{}".format(t1, temp_t2)
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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 run_ddp_state_dict():
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get_components_func = non_distributed_component_funcs.get_callable('gpt2')
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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 = init_ddp(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_ddp_state_dict()
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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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spawn(run_dist, world_size)
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if __name__ == '__main__':
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test_state_dict(2)
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