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63 lines
2.3 KiB
63 lines
2.3 KiB
import pytest
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import colossalai
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from colossalai.amp import AMP_TYPE
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from colossalai.core import global_context as gpc
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from colossalai.testing import parameterize, rerun_if_address_is_in_use, spawn
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from tests.components_to_test.registry import non_distributed_component_funcs
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CONFIG = dict(parallel=dict(pipeline=dict(size=1), tensor=dict(size=1, mode=None)),
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fp16=dict(mode=None),
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clip_grad_norm=1.0)
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@parameterize('model_name', ['repeated_computed_layers', 'resnet18', 'repeated_computed_layers'])
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@parameterize('amp_mode', [AMP_TYPE.APEX, AMP_TYPE.TORCH, AMP_TYPE.NAIVE, None])
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def run_train(model_name, amp_mode):
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# FIXME: test bert
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get_components_func = non_distributed_component_funcs.get_callable(model_name)
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gpc.config.fp16['mode'] = amp_mode
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model_builder, train_dataloader, _, optimizer_class, criterion = get_components_func()
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model = model_builder(checkpoint=False)
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engine, train_dataloader, *args = colossalai.initialize(model=model,
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optimizer=optimizer_class(model.parameters(), lr=1e-3),
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criterion=criterion,
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train_dataloader=train_dataloader)
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try:
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engine.train()
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for data, label in train_dataloader:
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engine.zero_grad()
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data = data.cuda()
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label = label.cuda()
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if criterion:
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output = engine(data)
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loss = engine.criterion(output, label)
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else:
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loss = engine(data, label)
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engine.backward(loss)
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engine.step()
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break
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except IndexError:
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# if using apex amp, NetWithRepeatedlyComputedLayers will raise an index out of range issue
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# the following check fails in apex
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# if cached_x.grad_fn.next_functions[1][0].variable is not x:
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pass
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def run_engine(rank, world_size, port):
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# init dist env
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colossalai.launch(config=CONFIG, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
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run_train()
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@pytest.mark.dist
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@rerun_if_address_is_in_use()
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def test_engine():
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spawn(run_engine, 2)
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if __name__ == '__main__':
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test_engine()
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