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df67ac4c86
as these unit tests would fail if run on a single GPU (i.e**. skip_if_lt_x_gpu(2)) seems to view world size as 2 even on platforms with 1 GPU.** Pull Request resolved: https://github.com/pytorch/pytorch/pull/145195 Approved by: https://github.com/Skylion007, https://github.com/atalman
96 lines
3.2 KiB
Python
96 lines
3.2 KiB
Python
# Owner(s): ["oncall: distributed"]
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import sys
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import torch
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from torch import distributed as dist
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from torch.distributed.checkpoint import FileSystemReader, FileSystemWriter, load, save
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from torch.distributed.fsdp import FullyShardedDataParallel as FSDP, StateDictType
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from torch.distributed.fsdp.fully_sharded_data_parallel import FullyShardedDataParallel
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from torch.distributed.fsdp.wrap import enable_wrap, wrap
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from torch.testing._internal.common_device_type import instantiate_device_type_tests
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from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
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from torch.testing._internal.common_fsdp import FSDPTest, SkipModel
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from torch.testing._internal.common_utils import (
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parametrize,
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run_tests,
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TEST_WITH_DEV_DBG_ASAN,
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)
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from torch.testing._internal.distributed.checkpoint_utils import with_temp_dir
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if not dist.is_available():
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print("Distributed not available, skipping tests", file=sys.stderr)
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sys.exit(0)
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if TEST_WITH_DEV_DBG_ASAN:
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print(
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"Skip dev-asan as torch + multiprocessing spawn have known issues",
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file=sys.stderr,
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)
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sys.exit(0)
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_DISTRIBUTED_STATE_DICT_IMPLS = {
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StateDictType.LOCAL_STATE_DICT,
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StateDictType.SHARDED_STATE_DICT,
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}
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class TestDistributedCheckpoint(FSDPTest):
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@property
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def world_size(self):
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if torch.cuda.is_available():
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gpu_cnt = torch.cuda.device_count()
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if gpu_cnt < 2:
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return gpu_cnt
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return 2
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@skip_if_lt_x_gpu(2)
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@with_temp_dir
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@parametrize("state_dict_type", _DISTRIBUTED_STATE_DICT_IMPLS)
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def test_distributed_checkpoint(self, state_dict_type) -> None:
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with enable_wrap(wrapper_cls=FSDP):
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torch.manual_seed(100)
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model = wrap(SkipModel(double_nest=True))
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torch.manual_seed(200)
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new_model = wrap(SkipModel(double_nest=True))
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with FullyShardedDataParallel.summon_full_params(
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model
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), FullyShardedDataParallel.summon_full_params(new_model):
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params = list(model.parameters())
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new_params = list(new_model.parameters())
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self.assertNotEqual(params, new_params)
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writer = FileSystemWriter(self.temp_dir)
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reader = FileSystemReader(self.temp_dir)
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with FSDP.state_dict_type(model, state_dict_type), FSDP.state_dict_type(
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new_model, state_dict_type
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):
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state_dict = model.state_dict()
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save(state_dict, writer)
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with FSDP.state_dict_type(model, state_dict_type), FSDP.state_dict_type(
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new_model, state_dict_type
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):
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state_dict = new_model.state_dict()
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load(state_dict, reader)
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new_model.load_state_dict(state_dict)
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with FullyShardedDataParallel.summon_full_params(
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model
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), FullyShardedDataParallel.summon_full_params(new_model):
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params = list(model.parameters())
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new_params = list(new_model.parameters())
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self.assertEqual(params, new_params)
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# TODO: add resharding test case.
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devices = ("cuda", "hpu")
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instantiate_device_type_tests(TestDistributedCheckpoint, globals(), only_for=devices)
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if __name__ == "__main__":
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run_tests()
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