Files
LLaMA-Factory/tests_v1/accelerator/test_interface.py
Yaowei Zheng a754604c11 [misc] fix accelerator (#9661)
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
2025-12-25 02:11:04 +08:00

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Python

# Copyright 2025 the LlamaFactory team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import pytest
import torch.multiprocessing as mp
from llamafactory.v1.accelerator.helper import ReduceOp
from llamafactory.v1.accelerator.interface import DistributedInterface
from llamafactory.v1.utils.env import find_available_port
from llamafactory.v1.utils.pytest import dist_env
def _all_reduce_tests(local_rank: int, world_size: int, master_port: int):
with dist_env(local_rank, world_size, master_port):
rank = DistributedInterface().get_rank()
world_size = DistributedInterface().get_world_size()
assert world_size == 2
y_sum = DistributedInterface().all_reduce(rank + 1.0, op=ReduceOp.SUM)
assert y_sum == pytest.approx(3.0)
y_mean = DistributedInterface().all_reduce(rank + 1.0, op=ReduceOp.MEAN)
assert y_mean == pytest.approx(1.5)
y_max = DistributedInterface().all_reduce(rank + 1.0, op=ReduceOp.MAX)
assert y_max == pytest.approx(2.0)
z = DistributedInterface().all_gather(rank + 1.0)
assert z == pytest.approx([1.0, 2.0])
z = DistributedInterface().broadcast(rank + 1.0)
assert z == pytest.approx(1.0)
def test_all_device():
assert DistributedInterface().get_rank() == int(os.getenv("RANK", "0"))
assert DistributedInterface().get_world_size() == int(os.getenv("WORLD_SIZE", "1"))
assert DistributedInterface().get_local_rank() == int(os.getenv("LOCAL_RANK", "0"))
assert DistributedInterface().get_local_world_size() == int(os.getenv("LOCAL_WORLD_SIZE", "1"))
@pytest.mark.runs_on(["cuda", "npu"])
@pytest.mark.require_distributed(2)
def test_multi_device():
master_port = find_available_port()
mp.spawn(_all_reduce_tests, args=(2, master_port), nprocs=2)