Making large AI models cheaper, faster and more accessible
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import pytest
import torch.distributed as dist
import colossalai
from colossalai.cluster import ProcessGroupMesh
from colossalai.testing import spawn
def check_process_group_mesh_with_gpc():
from colossalai.legacy.context import ParallelMode
from colossalai.legacy.core import global_context as gpc
DP_DIM, PP_DIM, TP_DIM = 0, 1, 2
pg_mesh = ProcessGroupMesh(1, 2, 2)
# check world size
assert gpc.get_world_size(ParallelMode.TENSOR) == pg_mesh.size(
TP_DIM
), f"{gpc.get_world_size(ParallelMode.TENSOR)} != {pg_mesh.size(TP_DIM)}"
assert gpc.get_world_size(ParallelMode.PIPELINE) == pg_mesh.size(PP_DIM)
assert gpc.get_world_size(ParallelMode.DATA) == pg_mesh.size(DP_DIM)
# check locak rank (coordinate)
assert gpc.get_local_rank(ParallelMode.TENSOR) == pg_mesh.coordinate(
TP_DIM
), f"{gpc.get_local_rank(ParallelMode.TENSOR)} != {pg_mesh.coordinate(TP_DIM)}"
assert gpc.get_local_rank(ParallelMode.PIPELINE) == pg_mesh.coordinate(PP_DIM)
assert gpc.get_local_rank(ParallelMode.DATA) == pg_mesh.coordinate(DP_DIM)
# check ranks in group
tp_group = pg_mesh.get_group_along_axis(TP_DIM)
assert gpc.get_ranks_in_group(ParallelMode.TENSOR) == pg_mesh.get_ranks_in_group(tp_group)
pp_group = pg_mesh.get_group_along_axis(PP_DIM)
assert gpc.get_ranks_in_group(ParallelMode.PIPELINE) == pg_mesh.get_ranks_in_group(pp_group)
dp_group = pg_mesh.get_group_along_axis(DP_DIM)
assert gpc.get_ranks_in_group(ParallelMode.DATA) == pg_mesh.get_ranks_in_group(dp_group)
# check prev rank
coord = pg_mesh.coordinate()
if not gpc.is_first_rank(ParallelMode.TENSOR):
assert coord[TP_DIM] != 0
prev_coord = coord[:TP_DIM] + (coord[TP_DIM] - 1,) + coord[TP_DIM + 1 :]
assert gpc.get_prev_global_rank(ParallelMode.TENSOR) == pg_mesh.ravel(prev_coord, pg_mesh.shape)
if not gpc.is_first_rank(ParallelMode.PIPELINE):
assert coord[PP_DIM] != 0
prev_coord = coord[:PP_DIM] + (coord[PP_DIM] - 1,) + coord[PP_DIM + 1 :]
assert gpc.get_prev_global_rank(ParallelMode.PIPELINE) == pg_mesh.ravel(prev_coord, pg_mesh.shape)
# check next rank
if not gpc.is_last_rank(ParallelMode.TENSOR):
assert coord[TP_DIM] != pg_mesh.size(TP_DIM) - 1
next_coord = coord[:TP_DIM] + (coord[TP_DIM] + 1,) + coord[TP_DIM + 1 :]
assert gpc.get_next_global_rank(ParallelMode.TENSOR) == pg_mesh.ravel(next_coord, pg_mesh.shape)
if not gpc.is_last_rank(ParallelMode.PIPELINE):
assert coord[PP_DIM] != pg_mesh.size(PP_DIM) - 1
next_coord = coord[:PP_DIM] + (coord[PP_DIM] + 1,) + coord[PP_DIM + 1 :]
assert gpc.get_next_global_rank(ParallelMode.PIPELINE) == pg_mesh.ravel(next_coord, pg_mesh.shape)
def check_process_group_mesh_with_cases():
DP_DIM, PP_DIM, TP_DIM = 0, 1, 2
DP_SIZE, PP_SIZE, TP_SIZE = 1, 2, 2
RANK_TO_COORDINATE = {
0: (0, 0, 0),
1: (0, 0, 1),
2: (0, 1, 0),
3: (0, 1, 1),
}
TP_RANKS_IN_GROUP = {
0: [0, 1],
1: [0, 1],
2: [2, 3],
3: [2, 3],
}
PP_RANKS_IN_GROUP = {
0: [0, 2],
1: [1, 3],
2: [0, 2],
3: [1, 3],
}
DP_RANKS_IN_GROUP = {
0: [0],
1: [1],
2: [2],
3: [3],
}
pg_mesh = ProcessGroupMesh(DP_SIZE, PP_SIZE, TP_SIZE)
rank = dist.get_rank()
assert rank == pg_mesh.rank
# check world size
assert pg_mesh.size(TP_DIM) == 2
assert pg_mesh.size(PP_DIM) == 2
assert pg_mesh.size(DP_DIM) == 1
# check coordinate
assert pg_mesh.coordinate(TP_DIM) == RANK_TO_COORDINATE[rank][TP_DIM]
assert pg_mesh.coordinate(PP_DIM) == RANK_TO_COORDINATE[rank][PP_DIM]
assert pg_mesh.coordinate(DP_DIM) == RANK_TO_COORDINATE[rank][DP_DIM]
# check ranks in group
tp_group = pg_mesh.get_group_along_axis(TP_DIM)
assert pg_mesh.get_ranks_in_group(tp_group) == TP_RANKS_IN_GROUP[rank]
pp_group = pg_mesh.get_group_along_axis(PP_DIM)
assert pg_mesh.get_ranks_in_group(pp_group) == PP_RANKS_IN_GROUP[rank]
dp_group = pg_mesh.get_group_along_axis(DP_DIM)
assert pg_mesh.get_ranks_in_group(dp_group) == DP_RANKS_IN_GROUP[rank]
# check prev rank
if RANK_TO_COORDINATE[rank][TP_DIM] != 0:
prev_coord = (
RANK_TO_COORDINATE[rank][:TP_DIM]
+ (RANK_TO_COORDINATE[rank][TP_DIM] - 1,)
+ RANK_TO_COORDINATE[rank][TP_DIM + 1 :]
)
prev_rank = TP_RANKS_IN_GROUP[rank][TP_RANKS_IN_GROUP[rank].index(rank) - 1]
assert pg_mesh.ravel(prev_coord, pg_mesh.shape) == prev_rank
if RANK_TO_COORDINATE[rank][PP_DIM] != 0:
prev_coord = (
RANK_TO_COORDINATE[rank][:PP_DIM]
+ (RANK_TO_COORDINATE[rank][PP_DIM] - 1,)
+ RANK_TO_COORDINATE[rank][PP_DIM + 1 :]
)
prev_rank = PP_RANKS_IN_GROUP[rank][PP_RANKS_IN_GROUP[rank].index(rank) - 1]
assert pg_mesh.ravel(prev_coord, pg_mesh.shape) == prev_rank
# check next rank
if RANK_TO_COORDINATE[rank][TP_DIM] != TP_SIZE - 1:
next_coord = (
RANK_TO_COORDINATE[rank][:TP_DIM]
+ (RANK_TO_COORDINATE[rank][TP_DIM] + 1,)
+ RANK_TO_COORDINATE[rank][TP_DIM + 1 :]
)
next_rank = TP_RANKS_IN_GROUP[rank][TP_RANKS_IN_GROUP[rank].index(rank) + 1]
assert pg_mesh.ravel(next_coord, pg_mesh.shape) == next_rank
if RANK_TO_COORDINATE[rank][PP_DIM] != PP_SIZE - 1:
next_coord = (
RANK_TO_COORDINATE[rank][:PP_DIM]
+ (RANK_TO_COORDINATE[rank][PP_DIM] + 1,)
+ RANK_TO_COORDINATE[rank][PP_DIM + 1 :]
)
next_rank = PP_RANKS_IN_GROUP[rank][PP_RANKS_IN_GROUP[rank].index(rank) + 1]
assert pg_mesh.ravel(next_coord, pg_mesh.shape) == next_rank
def run_dist(rank, world_size, port):
colossalai.launch(
config=dict(parallel=dict(data=1, pipeline=2, tensor=dict(mode="1d", size=2))),
rank=rank,
world_size=world_size,
port=port,
host="localhost",
)
# TODO(ver217): this function should be removed when gpc is removed
# check_process_group_mesh_with_gpc()
check_process_group_mesh_with_cases()
@pytest.mark.dist
def test_process_group_mesh():
spawn(run_dist, 4)
if __name__ == "__main__":
test_process_group_mesh()