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[misc] update pre-commit and run all files (#4752)

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* [misc] update pre-commit

* [misc] run pre-commit

* [misc] remove useless configuration files

* [misc] ignore cuda for clang-format
This commit is contained in:
Hongxin Liu
2023-09-19 14:20:26 +08:00
committed by GitHub
parent 3c6b831c26
commit 079bf3cb26
1268 changed files with 50037 additions and 38444 deletions
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51
tests/test_zero/test_gemini/test_zeroddp_state_dict.py
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@@ -10,21 +10,10 @@ from colossalai.zero.gemini.chunk import search_chunk_configuration
from tests.components_to_test.registry import non_distributed_component_funcs
PLACEMENT_CONFIGS = [
{
'placement_policy': 'static',
'shard_param_frac': 0.0
}, # zero2
{
'placement_policy': 'static',
'shard_param_frac': 1.0
}, # zero3
{
'placement_policy': 'static',
'shard_param_frac': 0.5
}, # zero3-half
{
'placement_policy': 'auto'
}
{"placement_policy": "static", "shard_param_frac": 0.0}, # zero2
{"placement_policy": "static", "shard_param_frac": 1.0}, # zero3
{"placement_policy": "static", "shard_param_frac": 0.5}, # zero3-half
{"placement_policy": "auto"},
]
@@ -35,9 +24,9 @@ def ignore_the_first_parameter(model: torch.nn.Module):
return
@parameterize('placement_config', PLACEMENT_CONFIGS)
@parameterize('keep_gathered', [True, False])
@parameterize('model_name', ['gpt2', 'bert'])
@parameterize("placement_config", PLACEMENT_CONFIGS)
@parameterize("keep_gathered", [True, False])
@parameterize("model_name", ["gpt2", "bert"])
def exam_state_dict(placement_config, keep_gathered, model_name: str):
set_seed(431)
get_components_func = non_distributed_component_funcs.get_callable(model_name)
@@ -51,8 +40,8 @@ def exam_state_dict(placement_config, keep_gathered, model_name: str):
world_size = torch.distributed.get_world_size()
config_dict, *_ = search_chunk_configuration(model, search_range_m=1, search_interval=100)
config_dict[world_size]['chunk_size'] = 5000
config_dict[world_size]['keep_gathered'] = keep_gathered
config_dict[world_size]["chunk_size"] = 5000
config_dict[world_size]["keep_gathered"] = keep_gathered
model = GeminiDDP(model, config_dict, **placement_config, pin_memory=True)
model.train()
@@ -65,9 +54,9 @@ def exam_state_dict(placement_config, keep_gathered, model_name: str):
assert_close(value, temp_zero_value, rtol=1e-3, atol=1e-5)
@parameterize('placement_config', PLACEMENT_CONFIGS)
@parameterize('keep_gathered', [True, False])
@parameterize('model_name', ['gpt2', 'bert'])
@parameterize("placement_config", PLACEMENT_CONFIGS)
@parameterize("keep_gathered", [True, False])
@parameterize("model_name", ["gpt2", "bert"])
def exam_load_state_dict(placement_config, keep_gathered, model_name: str):
set_seed(431)
get_components_func = non_distributed_component_funcs.get_callable(model_name)
@@ -76,12 +65,12 @@ def exam_load_state_dict(placement_config, keep_gathered, model_name: str):
model = model_builder()
set_seed(451)
torch_model = model_builder() # get a different model
torch_model = model_builder() # get a different model
world_size = torch.distributed.get_world_size()
config_dict, *_ = search_chunk_configuration(model, search_range_m=1, search_interval=100)
config_dict[world_size]['chunk_size'] = 5000
config_dict[world_size]['keep_gathered'] = keep_gathered
config_dict[world_size]["chunk_size"] = 5000
config_dict[world_size]["keep_gathered"] = keep_gathered
model = GeminiDDP(model, config_dict, **placement_config, pin_memory=True)
@@ -95,8 +84,8 @@ def exam_load_state_dict(placement_config, keep_gathered, model_name: str):
assert_close(value, temp_zero_value, rtol=1e-3, atol=1e-5)
@parameterize('placement_config', PLACEMENT_CONFIGS)
@parameterize('model_name', ['gpt2', 'bert'])
@parameterize("placement_config", PLACEMENT_CONFIGS)
@parameterize("model_name", ["gpt2", "bert"])
def exam_state_dict_shard(placement_config, model_name: str):
get_components_func = non_distributed_component_funcs.get_callable(model_name)
model_builder, train_dataloader, test_dataloader, optimizer_class, criterion = get_components_func()
@@ -122,18 +111,18 @@ def exam_state_dict_shard(placement_config, model_name: str):
def run_dist(rank, world_size, port):
config = {}
colossalai.launch(config=config, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
colossalai.launch(config=config, rank=rank, world_size=world_size, host="localhost", port=port, backend="nccl")
exam_state_dict()
exam_load_state_dict()
exam_state_dict_shard()
@pytest.mark.dist
@pytest.mark.parametrize('world_size', [1, 4])
@pytest.mark.parametrize("world_size", [1, 4])
@rerun_if_address_is_in_use()
def test_zero_ddp(world_size):
spawn(run_dist, world_size)
if __name__ == '__main__':
if __name__ == "__main__":
test_zero_ddp(1)