ColossalAI/tests/test_engine/test_engine.py

94 lines
2.9 KiB
Python

from functools import partial
import colossalai
import pytest
import torch.multiprocessing as mp
from colossalai.amp import AMP_TYPE
from colossalai.context import Config
from colossalai.core import global_context as gpc
from colossalai.utils import free_port
from tests.components_to_test.registry import non_distributed_component_funcs
CONFIG = dict(parallel=dict(pipeline=dict(size=1), tensor=dict(size=1, mode=None)),
fp16=dict(mode=None),
clip_grad_norm=1.0)
def run_train():
test_models = ['repeated_computed_layers', 'resnet18', 'repeated_computed_layers']
# FIXME: test bert
for model_name in test_models:
get_components_func = non_distributed_component_funcs.get_callable(model_name)
model_builder, train_dataloader, _, optimizer_builder, criterion = get_components_func()
model = model_builder(checkpoint=False)
engine, train_dataloader, *args = colossalai.initialize(model=model,
optimizer=optimizer_builder(model),
criterion=criterion,
train_dataloader=train_dataloader)
try:
engine.train()
for data, label in train_dataloader:
engine.zero_grad()
data = data.cuda()
label = label.cuda()
if criterion:
output = engine(data)
loss = engine.criterion(output, label)
else:
loss = engine(data, label)
engine.backward(loss)
engine.step()
break
except IndexError:
# if using apex amp, NetWithRepeatedlyComputedLayers will raise an index out of range issue
# the following check fails in apex
# if cached_x.grad_fn.next_functions[1][0].variable is not x:
continue
def run_with_no_amp():
run_train()
def run_with_torch_amp():
# hack config
CONFIG['fp16']['mode'] = AMP_TYPE.TORCH
gpc._config = Config(CONFIG)
run_train()
def run_with_apex_amp():
# hack config
CONFIG['fp16']['mode'] = AMP_TYPE.APEX
gpc._config = Config(CONFIG)
run_train()
def run_with_naive_amp():
# hack config
CONFIG['fp16']['mode'] = AMP_TYPE.NAIVE
gpc._config = Config(CONFIG)
run_train()
def run_engine(rank, world_size, port):
# init dist env
colossalai.launch(config=dict(), rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
run_with_no_amp()
run_with_torch_amp()
run_with_apex_amp()
run_with_naive_amp()
@pytest.mark.dist
def test_engine():
world_size = 4
run_func = partial(run_engine, world_size=world_size, port=free_port())
mp.spawn(run_func, nprocs=world_size)
if __name__ == '__main__':
test_engine()