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81 lines
2.8 KiB
81 lines
2.8 KiB
2 years ago
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from functools import partial
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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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from colossalai.tensor.sharding_spec import ShardingSpec
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from colossalai.device.device_mesh import DeviceMesh
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from colossalai.initialize import launch
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from colossalai.utils import free_port
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from colossalai.testing import rerun_if_address_is_in_use
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from colossalai.logging import disable_existing_loggers
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from colossalai.tensor.shape_consistency import ShapeConsistencyManager, CollectiveCommPattern
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def check_apply(rank, world_size, port):
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disable_existing_loggers()
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launch(config={}, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
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physical_mesh_id = torch.arange(0, 4)
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mesh_shape = (2, 2)
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# [[0, 1,
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# [2, 3]]
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device_mesh = DeviceMesh(physical_mesh_id, mesh_shape, init_process_group=True)
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entire_shape = torch.Size((4, 2))
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shape_consistency_manager = ShapeConsistencyManager()
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dim_partition_source = {0: [0]}
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dim_partition_target = {1: [0]}
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# DistSpec:
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# shard_sequence: S0,R
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# device_mesh_shape: (2, 2)
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sharding_spec_source = ShardingSpec(device_mesh, entire_shape, dim_partition_source)
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# DistSpec:
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# shard_sequence: R,S0
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# device_mesh_shape: (2, 2)
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sharding_spec_target = ShardingSpec(device_mesh, entire_shape, dim_partition_target)
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if rank in (0, 1):
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sharded_tensor_0 = torch.zeros(2, 1)
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sharded_tensor_1 = torch.ones(2, 1)
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# tensor([[0., 1.],
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# [0., 1.]])
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tensor_to_comm = torch.cat((sharded_tensor_0, sharded_tensor_1), 1).cuda()
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if rank in (2, 3):
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sharded_tensor_0 = torch.ones(2, 1) * 2
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sharded_tensor_1 = torch.ones(2, 1) * 3
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# tensor([[2., 3.],
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# [2., 3.]])
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tensor_to_comm = torch.cat((sharded_tensor_0, sharded_tensor_1), 1).cuda()
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if rank in (0, 1):
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# tensor([[0.],
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# [0.],
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# [2.],
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# [2.]])
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tensor_to_check = torch.tensor([[0], [0], [2], [2]], dtype=tensor_to_comm.dtype).cuda()
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if rank in (2, 3):
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# tensor([[1.],
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# [1.],
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# [3.],
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# [3.]])
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tensor_to_check = torch.tensor([[1], [1], [3], [3]], dtype=tensor_to_comm.dtype).cuda()
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tensor_to_comm.sharding_spec = sharding_spec_source
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shape_consistency_manager.apply(tensor_to_comm, sharding_spec_target)
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assert tensor_to_comm.equal(tensor_to_check)
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assert str(tensor_to_comm.sharding_spec.sharding_sequence) == str(sharding_spec_target.sharding_sequence)
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@pytest.mark.dist
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@rerun_if_address_is_in_use()
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def test_apply():
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world_size = 4
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run_func = partial(check_apply, 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_apply()
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