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[zero] update zero context init with the updated test utils (#327)
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@@ -9,22 +9,27 @@ import torch
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import torch.multiprocessing as mp
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from colossalai.zero.shard_utils.tensor_shard_strategy import TensorShardStrategy
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from colossalai.zero.init_ctx import ZeroInitContext
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from common import CONFIG, Net
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from common import CONFIG
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from colossalai.utils import free_port
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from tests.components_to_test.registry import non_distributed_component_funcs
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def run_dist(rank, world_size, port):
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colossalai.launch(config=CONFIG, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
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with ZeroInitContext(convert_fp16=True, convert_cuda=True, shard_strategy=TensorShardStrategy(), shard_param=True):
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# Note Net(checkpoint=True).cuda() moving to cuda is useless
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model = Net(checkpoint=True)
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for get_components_func in non_distributed_component_funcs:
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model_builder, _, _, _, _ = get_components_func()
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with ZeroInitContext(convert_fp16=True,
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convert_cuda=True,
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shard_strategy=TensorShardStrategy(),
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shard_param=True):
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model = model_builder(checkpoint=True)
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for param in model.parameters():
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assert hasattr(param, 'ca_attr')
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assert param.ca_attr.data.dtype == torch.half
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assert param.ca_attr._data_sharded_tensor.is_sharded
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assert param.ca_attr.data.device.type == 'cuda'
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for param in model.parameters():
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assert hasattr(param, 'ca_attr')
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assert param.ca_attr.data.dtype == torch.half
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assert param.ca_attr._data_sharded_tensor.is_sharded
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assert param.ca_attr.data.device.type == 'cuda'
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@pytest.mark.dist
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@@ -46,6 +46,8 @@ def _run_shard_param_v2(rank, world_size, port):
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sparam = ShardedParamV2(param=param, process_group=None)
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allclose(sparam.data, param_ref.data)
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sparam.remove_torch_payload()
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assert (param.data.numel() == 1)
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