ColossalAI/tests/test_zero_data_parallel/test_state_dict.py

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#!/usr/bin/env python
# -*- encoding: utf-8 -*-
from copy import deepcopy
from functools import partial
import colossalai
import pytest
import torch
import torch.multiprocessing as mp
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from colossalai.testing import parameterize, rerun_on_exception
from colossalai.utils import free_port
from colossalai.zero.init_ctx import ZeroInitContext
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from colossalai.zero.shard_utils import (BucketTensorShardStrategy, TensorShardStrategy)
from colossalai.zero.sharded_model import ShardedModelV2
from colossalai.zero.sharded_model.utils import col_model_deepcopy
from tests.components_to_test.registry import non_distributed_component_funcs
from common import CONFIG
@parameterize("shard_strategy_class", [TensorShardStrategy, BucketTensorShardStrategy])
def run_zero_state_dict(shard_strategy_class):
test_models = ['repeated_computed_layers', 'resnet18']
shard_strategy = shard_strategy_class()
for model_name in test_models:
get_components_func = non_distributed_component_funcs.get_callable(model_name)
model_builder, train_dataloader, test_dataloader, optimizer, criterion = get_components_func()
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with ZeroInitContext(target_device=torch.cuda.current_device(),
shard_strategy=shard_strategy,
shard_param=True,
rm_torch_payload_on_the_fly=False):
zero_model = model_builder(checkpoint=True)
zero_model = ShardedModelV2(zero_model, shard_strategy)
model = model_builder(checkpoint=True).half()
col_model_deepcopy(zero_model, model)
model = model.cuda()
zero_state_dict = zero_model.state_dict()
for key, val in model.state_dict().items():
assert torch.equal(val, zero_state_dict[key])
def run_dist(rank, world_size, port):
colossalai.launch(config=CONFIG, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
run_zero_state_dict()
@pytest.mark.dist
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@pytest.mark.parametrize("world_size", [1, 2])
@rerun_on_exception(exception_type=mp.ProcessRaisedException, pattern=".*Address already in use.*")
def test_zero_state_dict(world_size):
run_func = partial(run_dist, world_size=world_size, port=free_port())
mp.spawn(run_func, nprocs=world_size)
if __name__ == '__main__':
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test_zero_state_dict(2, TensorShardStrategy)