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