diff --git a/tests/test_tensor/test_gpt2.py b/tests/test_tensor/test_gpt2.py index 3c6a3a43f..ad1ee5d58 100644 --- a/tests/test_tensor/test_gpt2.py +++ b/tests/test_tensor/test_gpt2.py @@ -12,7 +12,7 @@ from colossalai.testing import rerun_if_address_is_in_use from colossalai.utils.cuda import get_current_device from colossalai.utils import free_port from colossalai.utils.model.colo_init_context import ColoInitContext -from colossalai.tensor import ShardSpec, ComputePattern, ComputeSpec, DistSpecManager, ProcessGroup +from colossalai.tensor import ShardSpec, ComputePattern, ComputeSpec, DistSpecManager, ProcessGroup, ColoTensor, ColoTensorSpec from colossalai.nn.parallel.data_parallel import ColoDDP from colossalai.core import global_context as gpc from colossalai.context.parallel_mode import ParallelMode @@ -21,18 +21,20 @@ from tests.components_to_test.registry import non_distributed_component_funcs def init_1d_row_spec(model, pg: ProcessGroup): tensor_spec = (ShardSpec([0], [pg.tp_world_size()]), ComputeSpec(ComputePattern.TP1D)) - with DistSpecManager.no_grad(): - for n, p in model.named_parameters(): - if 'weight' in n and 'ln' not in n: - p.set_tensor_spec(*tensor_spec) + + for n, p in model.named_parameters(): + p.set_process_group(pg) + if 'weight' in n and 'ln' not in n: + p.set_tensor_spec(*tensor_spec) def init_1d_col_spec(model, pg: ProcessGroup): spec = (ShardSpec([-1], [pg.tp_world_size()]), ComputeSpec(ComputePattern.TP1D)) - with DistSpecManager.no_grad(): - for n, p in model.named_parameters(): - if 'ln' not in n and ('weight' in n or 'bias' in n): - p.set_tensor_spec(*spec) + + for n, p in model.named_parameters(): + p.set_process_group(pg) + if 'ln' not in n and ('weight' in n or 'bias' in n): + p.set_tensor_spec(*spec) def check_param_equal(model, torch_model, pg: ProcessGroup): @@ -48,6 +50,7 @@ def check_grad_equal(model, torch_model, pg: ProcessGroup): def run_gpt(init_spec_func, use_ddp): + set_seed(13234) world_size = torch.distributed.get_world_size() pg = ProcessGroup(dp_degree=(2 if (use_ddp and world_size >= 2) else 1)) get_components_func = non_distributed_component_funcs.get_callable('gpt2') @@ -67,14 +70,16 @@ def run_gpt(init_spec_func, use_ddp): model = ColoDDP(model, process_group=pg) for torch_p, p in zip(torch_model.parameters(), model.parameters()): torch_p.data.copy_(p) + init_spec_func(model, pg) check_param_equal(model, torch_model, pg) model.train() torch_model.train() - set_seed(pg.tp_local_rank()) + torch.distributed.barrier() for i, (input_ids, attn_mask) in enumerate(train_dataloader): - logits = model(input_ids, attn_mask) + colo_input = ColoTensor.from_torch_tensor(input_ids, ColoTensorSpec(pg)) + logits = model(colo_input, attn_mask) torch_logits = torch_model(input_ids, attn_mask) assert tensor_equal(torch_logits, logits), f"{torch_logits - logits}" loss = criterion(logits, input_ids) @@ -95,14 +100,13 @@ def run_dist(rank, world_size, port, use_ddp): tp_world_size = world_size // 2 if use_ddp else world_size config = dict(parallel=dict(tensor=dict(mode="1d", size=tp_world_size),)) colossalai.launch(config=config, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl') - # run_gpt(init_1d_row_spec, use_ddp) + run_gpt(init_1d_row_spec, use_ddp) run_gpt(init_1d_col_spec, use_ddp) @pytest.mark.dist -@pytest.mark.skip("under development") @pytest.mark.parametrize('world_size', [1, 4]) -@pytest.mark.parametrize('use_ddp', [False, True]) +@pytest.mark.parametrize('use_ddp', [False]) @rerun_if_address_is_in_use() def test_gpt(world_size, use_ddp): run_func = partial(run_dist, world_size=world_size, port=free_port(), use_ddp=use_ddp) @@ -110,4 +114,4 @@ def test_gpt(world_size, use_ddp): if __name__ == '__main__': - test_gpt(4, True) + test_gpt(4, False)