mirror of https://github.com/hpcaitech/ColossalAI
aibig-modeldata-parallelismdeep-learningdistributed-computingfoundation-modelsheterogeneous-traininghpcinferencelarge-scalemodel-parallelismpipeline-parallelism
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
89 lines
3.0 KiB
89 lines
3.0 KiB
import pytest |
|
import torch |
|
import torch.distributed as dist |
|
|
|
import colossalai |
|
from colossalai.device.device_mesh import DeviceMesh |
|
from colossalai.testing import rerun_if_address_is_in_use, spawn |
|
|
|
|
|
def test_device_mesh(): |
|
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) |
|
assert device_mesh.global_rank_to_local_rank(5) == [1, 1] |
|
assert device_mesh.global_rank_to_local_rank(11) == [2, 3] |
|
assert device_mesh.get_ranks_in_process_group(axis=1, global_rank=2) == [0, 1, 2, 3] |
|
|
|
|
|
def check_1d_device_mesh(): |
|
# check for 1D device mesh |
|
process_group = dist.GroupMember.WORLD |
|
device_mesh = DeviceMesh.from_process_group(process_group) |
|
|
|
# checks |
|
assert device_mesh.shape == [4] |
|
assert len(device_mesh.get_process_group_for_all_axes().keys()) == 1, "Expected 1 axis for the process group dict" |
|
assert device_mesh.get_process_group(axis=0) == process_group, "Expected world process group" |
|
assert device_mesh.is_initialized |
|
assert device_mesh.num_devices == 4 |
|
assert device_mesh.is_initialized |
|
assert device_mesh.logical_mesh_id is None |
|
assert device_mesh._is_init_from_process_group |
|
|
|
|
|
def check_2d_device_mesh(): |
|
# create process group for 2D device mesh |
|
first_row_ranks = [0, 1] |
|
second_row_ranks = [2, 3] |
|
first_col_ranks = [0, 2] |
|
second_col_ranks = [1, 3] |
|
|
|
first_row_pg = dist.new_group(first_row_ranks, backend="nccl") |
|
second_row_pg = dist.new_group(second_row_ranks, backend="nccl") |
|
first_col_pg = dist.new_group(first_col_ranks, backend="nccl") |
|
second_col_pg = dist.new_group(second_col_ranks, backend="nccl") |
|
|
|
# check for |
|
current_rank = dist.get_rank() |
|
|
|
if current_rank in first_row_ranks: |
|
row_pg = first_row_pg |
|
else: |
|
row_pg = second_row_pg |
|
|
|
if current_rank in first_col_ranks: |
|
col_pg = first_col_pg |
|
else: |
|
col_pg = second_col_pg |
|
|
|
device_mesh = DeviceMesh.from_process_group([col_pg, row_pg]) |
|
|
|
# checks |
|
assert device_mesh.shape == [2, 2] |
|
assert len(device_mesh.get_process_group_for_all_axes().keys()) == 2, "Expected 2 axes for the process group dict" |
|
assert device_mesh.get_process_group(axis=0) == col_pg, "Expected column process group" |
|
assert device_mesh.get_process_group(axis=1) == row_pg, "Expected row process group" |
|
assert device_mesh.num_devices == 4 |
|
assert device_mesh.is_initialized |
|
assert device_mesh.logical_mesh_id is None |
|
assert device_mesh._is_init_from_process_group |
|
|
|
|
|
def check_init_from_process_group(rank, world_size, port): |
|
colossalai.launch(config={}, rank=rank, world_size=world_size, host="localhost", port=port, backend="nccl") |
|
|
|
|
|
@pytest.mark.dist |
|
@rerun_if_address_is_in_use() |
|
def test_device_mesh_from_process_group(): |
|
spawn(check_init_from_process_group, 4) |
|
|
|
|
|
if __name__ == "__main__": |
|
test_device_mesh() |
|
test_device_mesh_from_process_group()
|
|
|