mirror of https://github.com/hpcaitech/ColossalAI
61 lines
2.2 KiB
Python
61 lines
2.2 KiB
Python
#!/usr/bin/env python
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# -*- encoding: utf-8 -*-
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from copy import deepcopy
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from functools import partial
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import colossalai
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import pytest
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import torch
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import torch.multiprocessing as mp
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from colossalai.testing import parameterize
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from colossalai.utils import free_port
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from colossalai.zero.init_ctx import ZeroInitContext
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from colossalai.zero.shard_utils import (BucketTensorShardStrategy, TensorShardStrategy)
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from colossalai.zero.sharded_model import ShardedModelV2
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from colossalai.zero.sharded_model.utils import col_model_deepcopy
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from tests.components_to_test.registry import non_distributed_component_funcs
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from common import CONFIG
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@parameterize("shard_strategy_class", [TensorShardStrategy, BucketTensorShardStrategy])
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def run_zero_state_dict(shard_strategy_class):
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test_models = ['repeated_computed_layers', 'resnet18']
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shard_strategy = shard_strategy_class()
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for model_name in test_models:
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get_components_func = non_distributed_component_funcs.get_callable(model_name)
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model_builder, train_dataloader, test_dataloader, optimizer, criterion = get_components_func()
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with ZeroInitContext(convert_fp16=True,
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target_device=torch.cuda.current_device(),
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shard_strategy=shard_strategy,
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shard_param=True,
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rm_torch_payload_on_the_fly=False):
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zero_model = model_builder(checkpoint=True)
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zero_model = ShardedModelV2(zero_model, shard_strategy)
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model = model_builder(checkpoint=True).half()
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col_model_deepcopy(zero_model, model)
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model = model.cuda()
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zero_state_dict = zero_model.state_dict()
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for key, val in model.state_dict().items():
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assert torch.equal(val, zero_state_dict[key])
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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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run_zero_state_dict()
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@pytest.mark.dist
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@pytest.mark.parametrize("world_size", [1, 2])
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def test_zero_state_dict(world_size):
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run_func = partial(run_dist, world_size=world_size, port=free_port())
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mp.spawn(run_func, nprocs=world_size)
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if __name__ == '__main__':
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test_zero_state_dict(2, TensorShardStrategy)
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