[test] reorganize zero/gemini tests (#3445)

tests/test_zero/test_gemini/test_zeroddp_state_dict.py

@@ -0,0 +1,113 @@
+from functools import partial
+
+import pytest
+import torch
+import torch.distributed as dist
+import torch.multiprocessing as mp
+from torch.testing import assert_close
+
+import colossalai
+from colossalai.testing import parameterize, rerun_if_address_is_in_use
+from colossalai.utils import free_port
+from colossalai.utils.cuda import get_current_device
+from colossalai.zero import ColoInitContext, ZeroDDP
+from colossalai.zero.gemini.chunk import ChunkManager, search_chunk_configuration
+from colossalai.zero.gemini.gemini_mgr import GeminiManager
+from tests.components_to_test.registry import non_distributed_component_funcs
+from tests.test_tensor.common_utils import debug_print, set_seed
+
+
+def ignore_the_first_parameter(model: torch.nn.Module):
+    for name, param in model.named_parameters():
+        print(f"parameter `{name}` is set ignored")
+        ZeroDDP.set_params_to_ignore([param])
+        return
+
+
+@parameterize('placement_policy', ['cuda', 'cpu', 'auto'])
+@parameterize('keep_gathered', [True, False])
+@parameterize('model_name', ['gpt2', 'bert'])
+def exam_state_dict(placement_policy, keep_gathered, model_name: str):
+    set_seed(431)
+    get_components_func = non_distributed_component_funcs.get_callable(model_name)
+    model_builder, train_dataloader, test_dataloader, optimizer_class, criterion = get_components_func()
+
+    with ColoInitContext(device=get_current_device()):
+        model = model_builder()
+
+    torch_model = model_builder()
+    for torch_p, p in zip(torch_model.parameters(), model.parameters()):
+        torch_p.data.copy_(p.data)
+
+    world_size = torch.distributed.get_world_size()
+    config_dict, *_ = search_chunk_configuration(model, search_range_mb=1, search_interval_byte=100)
+    config_dict[world_size]['chunk_size'] = 5000
+    config_dict[world_size]['keep_gathered'] = keep_gathered
+    chunk_manager = ChunkManager(config_dict)
+    gemini_manager = GeminiManager(placement_policy, chunk_manager)
+    model = ZeroDDP(model, gemini_manager, pin_memory=True)
+    model.train()
+
+    zero_dict = model.state_dict(only_rank_0=False)
+    torch_dict = torch_model.state_dict()
+
+    for key, value in torch_dict.items():
+        assert key in zero_dict, "{} not in ZeRO dictionary.".format(key)
+        temp_zero_value = zero_dict[key].to(device=value.device, dtype=value.dtype)
+        assert_close(value, temp_zero_value, rtol=1e-3, atol=1e-5)
+
+
+@parameterize('placement_policy', ['cuda', 'cpu', 'auto'])
+@parameterize('keep_gathered', [True, False])
+@parameterize('model_name', ['gpt2', 'bert'])
+def exam_load_state_dict(placement_policy, keep_gathered, model_name: str):
+    set_seed(431)
+    get_components_func = non_distributed_component_funcs.get_callable(model_name)
+    model_builder, train_dataloader, test_dataloader, optimizer_class, criterion = get_components_func()
+
+    with ColoInitContext(device=get_current_device()):
+        model = model_builder()
+
+    set_seed(451)
+    torch_model = model_builder()    # get a different model
+
+    world_size = torch.distributed.get_world_size()
+    config_dict, *_ = search_chunk_configuration(model, search_range_mb=1, search_interval_byte=100)
+    config_dict[world_size]['chunk_size'] = 5000
+    config_dict[world_size]['keep_gathered'] = keep_gathered
+
+    if placement_policy != 'cuda':
+        init_device = torch.device('cpu')
+    else:
+        init_device = None
+    chunk_manager = ChunkManager(config_dict, init_device=init_device)
+    gemini_manager = GeminiManager(placement_policy, chunk_manager)
+    model = ZeroDDP(model, gemini_manager, pin_memory=True)
+
+    torch_dict = torch_model.state_dict()
+    model.load_state_dict(torch_dict, strict=False)
+    zero_dict = model.state_dict(only_rank_0=False)
+
+    for key, value in torch_dict.items():
+        assert key in zero_dict, "{} not in ZeRO dictionary.".format(key)
+        temp_zero_value = zero_dict[key].to(device=value.device, dtype=value.dtype)
+        assert_close(value, temp_zero_value, rtol=1e-3, atol=1e-5)
+
+
+def run_dist(rank, world_size, port):
+    config = {}
+    colossalai.launch(config=config, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
+    exam_state_dict()
+    exam_load_state_dict()
+
+
+@pytest.mark.dist
+@pytest.mark.parametrize('world_size', [1, 4])
+@rerun_if_address_is_in_use()
+def test_zero_ddp(world_size):
+    run_func = partial(run_dist, world_size=world_size, port=free_port())
+    mp.spawn(run_func, nprocs=world_size)
+
+
+if __name__ == '__main__':
+    test_zero_ddp(1)