mirror of https://github.com/hpcaitech/ColossalAI
65 lines
2.3 KiB
Python
65 lines
2.3 KiB
Python
import pytest
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import torch
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import colossalai
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from colossalai.tensor import (
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ColoParameter,
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ColoTensorSpec,
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ComputePattern,
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ComputeSpec,
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ProcessGroup,
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ReplicaSpec,
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ShardSpec,
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)
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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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from tests.test_tensor.common_utils import set_seed
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def run_colo_init_context(rank: int, world_size: int, port: int):
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colossalai.launch(config={}, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
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# make sure seed of each process is the same, so the params are consistent among processes and the params are exactly replicated.
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set_seed(42)
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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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# keep parameters replicated during init
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with ColoInitContext(device=get_current_device()):
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model1 = model_builder()
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# shard the parameters during init
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set_seed(42)
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shard_spec = ReplicaSpec()
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# If using ShardSpec, the assertations will failed.
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# But it is not a bug, the initialized values are not consist with the original one.
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# shard_spec = ShardSpec(dims=[0], num_partitions=[world_size])
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default_pg = ProcessGroup(tp_degree=world_size)
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with ColoInitContext(device=get_current_device(), default_pg=default_pg, default_dist_spec=shard_spec):
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model2 = model_builder()
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# reshard both models
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new_shard = ShardSpec(dims=[-1], num_partitions=[world_size])
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for p1, p2 in zip(model1.parameters(), model2.parameters()):
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p1: ColoParameter = p1
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p1.set_process_group(ProcessGroup(tp_degree=world_size))
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p1.set_dist_spec(new_shard)
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p2.set_dist_spec(new_shard)
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for p1, p2 in zip(model1.parameters(), model2.parameters()):
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assert (torch.allclose(p1, p2))
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@pytest.mark.dist
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@pytest.mark.parametrize('world_size', [1, 4])
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@rerun_if_address_is_in_use()
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def test_colo_init_context(world_size):
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spawn(run_colo_init_context, world_size)
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if __name__ == '__main__':
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test_colo_init_context(2)
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