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79 lines
2.6 KiB
79 lines
2.6 KiB
#!/usr/bin/env python
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# -*- encoding: utf-8 -*-
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import pprint
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from functools import partial
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import colossalai.nn as col_nn
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import pytest
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import torch
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import torch.multiprocessing as mp
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import torch.nn as nn
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from colossalai.context.parallel_mode import ParallelMode
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from colossalai.core import global_context as gpc
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from colossalai.initialize import launch
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from colossalai.logging import disable_existing_loggers
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from colossalai.utils import free_port, is_using_pp
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from colossalai.utils.checkpointing import gather_pipeline_parallel_state_dict, load_checkpoint, save_checkpoint
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from colossalai.testing import rerun_on_exception
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def build_pipeline(model):
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from colossalai.builder.pipeline import partition_uniform
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pipeline_size = gpc.get_world_size(ParallelMode.PIPELINE)
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pipeline_rank = gpc.get_local_rank(ParallelMode.PIPELINE)
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depth = len(model)
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start, end = partition_uniform(depth, pipeline_size, 1)[pipeline_rank][0]
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layers = []
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for i in range(depth):
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if start <= i < end:
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layers.append(model[i])
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else:
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layers.append(nn.Identity())
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return nn.Sequential(*tuple(layers))
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def check_equal(A, B):
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assert torch.allclose(A, B, rtol=1e-3, atol=1e-2)
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def check_checkpoint_1d(rank, world_size, port):
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config = dict(parallel=dict(pipeline=dict(size=2), tensor=dict(size=4, mode="1d")),)
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disable_existing_loggers()
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launch(config=config, rank=rank, world_size=world_size, host="localhost", port=port, backend="nccl")
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m1 = nn.Sequential(nn.Linear(4, 8), nn.Linear(8, 4))
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sd1 = m1.state_dict()
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if gpc.get_global_rank() == 0:
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print(f"Rank {gpc.get_global_rank()}:\n{pprint.pformat(sd1)}\n")
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save_checkpoint("test.pt", 0, m1)
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m2 = nn.Sequential(col_nn.Linear(4, 8), col_nn.Linear(8, 4))
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if is_using_pp():
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m2 = build_pipeline(m2)
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load_checkpoint("test.pt", m2)
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sd2 = m2.state_dict()
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if is_using_pp() and gpc.get_local_rank(ParallelMode.TENSOR) == 0:
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sd2 = gather_pipeline_parallel_state_dict(sd2)
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print(f"Rank {gpc.get_global_rank()}:\n{pprint.pformat(sd2)}\n")
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if gpc.get_global_rank() == 0:
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for k, v in sd1.items():
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assert k in sd2
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check_equal(v, sd2[k].to(torch.device("cpu")))
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@pytest.mark.dist
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@rerun_on_exception(exception_type=mp.ProcessRaisedException, pattern=".*Address already in use.*")
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def test_checkpoint_1d():
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world_size = 8
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run_func = partial(check_checkpoint_1d, 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_checkpoint_1d()
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