mirror of https://github.com/hpcaitech/ColossalAI
133 lines
5.9 KiB
Python
133 lines
5.9 KiB
Python
from colossalai.tensor.shape_consistency import ShapeConsistencyManager, CollectiveCommPattern
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import torch
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from colossalai.tensor.sharding_spec import _DimSpec, ShardingSpec
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from colossalai.device.device_mesh import DeviceMesh
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physical_mesh_id = torch.arange(0, 16).reshape(2, 8)
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mesh_shape = (4, 4)
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# [[0, 1, 2, 3],
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# [4, 5, 6, 7],
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# [8, 9, 10,11],
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# [12,13,14,15]]
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device_mesh = DeviceMesh(physical_mesh_id, mesh_shape)
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entire_shape = torch.Size((64, 32, 16))
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shape_consistency_manager = ShapeConsistencyManager()
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def test_one_step_transform():
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dim_partition_dict = {0: [0], 1: [1]}
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# DistSpec:
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# shard_sequence: S0,S1,R
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# device_mesh_shape: (4, 4)
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sharding_spec = ShardingSpec(device_mesh, entire_shape, dim_partition_dict)
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# {DistSpec:
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# shard_sequence: R,S1,R
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# device_mesh_shape: (4, 4): (CommSpec:(comm_pattern:allgather, gather_dim:0, logical_process_axis:0), 0), DistSpec:
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# shard_sequence: S0,R,R
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# device_mesh_shape: (4, 4): (CommSpec:(comm_pattern:allgather, gather_dim:1, logical_process_axis:1), 0)}
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rst_dict = shape_consistency_manager.get_all_all_gather_spec(sharding_spec, 0)
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assert '[R, S1, R]' in [
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str(all_gather_sharding_spec.sharding_sequence) for all_gather_sharding_spec in rst_dict.keys()
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]
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assert '[S0, R, R]' in [
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str(all_gather_sharding_spec.sharding_sequence) for all_gather_sharding_spec in rst_dict.keys()
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]
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dim_partition_dict_all2all = {0: [0], 1: [1]}
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# DistSpec:
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# shard_sequence: S0,S1,R
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# device_mesh_shape: (4, 4)
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sharding_spec_all2all = ShardingSpec(device_mesh, entire_shape, dim_partition_dict_all2all)
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# {DistSpec:
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# shard_sequence: S01,R,R
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# device_mesh_shape: (4, 4): (CommSpec:(comm_pattern:all2all, gather_dim:1, shard_dim:0, logical_process_axis: 1), 0), DistSpec:
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# shard_sequence: R,S1,S0
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# device_mesh_shape: (4, 4): (CommSpec:(comm_pattern:all2all, gather_dim:0, shard_dim:2, logical_process_axis: 0), 0), DistSpec:
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# shard_sequence: S0,R,S1
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# device_mesh_shape: (4, 4): (CommSpec:(comm_pattern:all2all, gather_dim:1, shard_dim:2, logical_process_axis: 1), 0)}
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rst_dict_all2all = shape_consistency_manager.get_all_all_to_all_spec(sharding_spec_all2all, 0)
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assert '[S01, R, R]' in [
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str(all2all_sharding_spec.sharding_sequence) for all2all_sharding_spec in rst_dict_all2all.keys()
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]
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assert '[R, S1, S0]' in [
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str(all2all_sharding_spec.sharding_sequence) for all2all_sharding_spec in rst_dict_all2all.keys()
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]
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assert '[S0, R, S1]' in [
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str(all2all_sharding_spec.sharding_sequence) for all2all_sharding_spec in rst_dict_all2all.keys()
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]
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dim_partition_shard = {0: [0]}
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# DistSpec:
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# shard_sequence: S0,R,R
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# device_mesh_shape: (4, 4)
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sharding_spec_shard = ShardingSpec(device_mesh, entire_shape, dim_partition_shard)
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# {DistSpec:
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# shard_sequence: S01,R,R
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# device_mesh_shape: (4, 4): (CommSpec:(comm_pattern:shard, shard_dim:0, logical_process_axis:1), 0), DistSpec:
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# shard_sequence: S0,S1,R
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# device_mesh_shape: (4, 4): (CommSpec:(comm_pattern:shard, shard_dim:1, logical_process_axis:1), 0), DistSpec:
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# shard_sequence: S0,R,S1
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# device_mesh_shape: (4, 4): (CommSpec:(comm_pattern:shard, shard_dim:2, logical_process_axis:1), 0)}
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rst_dict_shard = shape_consistency_manager.get_all_shard_spec(sharding_spec_shard, 0)
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assert '[S01, R, R]' in [
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str(shard_sharding_spec.sharding_sequence) for shard_sharding_spec in rst_dict_shard.keys()
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]
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assert '[S0, S1, R]' in [
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str(shard_sharding_spec.sharding_sequence) for shard_sharding_spec in rst_dict_shard.keys()
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]
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assert '[S0, R, S1]' in [
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str(shard_sharding_spec.sharding_sequence) for shard_sharding_spec in rst_dict_shard.keys()
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]
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def test_shape_consistency():
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dim_partition_source = {1: [0, 1]}
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dim_partition_target = {0: [0, 1]}
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# DistSpec:
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# shard_sequence: R,S01,R
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# device_mesh_shape: (4, 4)
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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: S01,R,R
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# device_mesh_shape: (4, 4)
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sharding_spec_target = ShardingSpec(device_mesh, entire_shape, dim_partition_target)
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transform_path, comm_action_sequence, total_cost = shape_consistency_manager.shape_consistency(
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sharding_spec_source, sharding_spec_target)
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transform_path_str = '->'.join([str(sharding_spec.sharding_sequence) for sharding_spec in transform_path])
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assert transform_path_str == '[R, S01, R]->[R, S0, R]->[S0, R, R]->[S01, R, R]'
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# all-gather(S01) -> S0
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assert comm_action_sequence[0].comm_pattern == CollectiveCommPattern.GATHER_FWD_SPLIT_BWD
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assert comm_action_sequence[0].gather_dim == 1
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assert comm_action_sequence[0].logical_process_axis == 1
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# all-to-all(R, S0) -> [S0, R]
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assert comm_action_sequence[1].comm_pattern == CollectiveCommPattern.ALL2ALL_FWD_ALL2ALL_BWD
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assert comm_action_sequence[1].gather_dim == 1
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assert comm_action_sequence[1].shard_dim == 0
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assert comm_action_sequence[1].logical_process_axis == 0
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# shard(S0) -> [S01]
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assert comm_action_sequence[2].comm_pattern == CollectiveCommPattern.SPLIT_FWD_GATHER_BWD
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assert comm_action_sequence[2].shard_dim == 0
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assert comm_action_sequence[2].logical_process_axis == 1
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assert shape_consistency_manager.cached_spec_pairs_transform_path[('[R, S01, R]',
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'[S01, R, R]')][0] == transform_path
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assert shape_consistency_manager.cached_spec_pairs_transform_path[('[R, S01, R]',
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'[S01, R, R]')][1] == comm_action_sequence
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if __name__ == '__main__':
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test_one_step_transform()
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test_shape_consistency()
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