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bac10cdd6f
…ogger Fixes #129951 . Would you take a moment to review it? @LucasLLC Pull Request resolved: https://github.com/pytorch/pytorch/pull/130423 Approved by: https://github.com/Skylion007
134 lines
4.6 KiB
Python
134 lines
4.6 KiB
Python
# Owner(s): ["oncall: distributed"]
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import sys
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import torch
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from torch.distributed._shard.sharded_tensor import (
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Shard,
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ShardedTensor,
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ShardedTensorMetadata,
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ShardMetadata,
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)
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from torch.distributed._shard.sharded_tensor.metadata import TensorProperties
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from torch.distributed.c10d_logger import _c10d_logger
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from torch.distributed.checkpoint.logger import _dcp_logger
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from torch.distributed.checkpoint.metadata import MetadataIndex
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from torch.distributed.checkpoint.utils import find_state_dict_object
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from torch.testing._internal.common_utils import (
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run_tests,
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TEST_WITH_DEV_DBG_ASAN,
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TestCase,
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)
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from torch.testing._internal.distributed.distributed_utils import with_fake_comms
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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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def create_sharded_tensor(rank, world_size, shards_per_rank):
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shards_metadata = []
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local_shards = []
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for idx in range(0, world_size * shards_per_rank):
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shard_rank = idx // shards_per_rank
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shard_md = ShardMetadata(
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shard_offsets=[idx * 8], shard_sizes=[8], placement=f"rank:{shard_rank}/cpu"
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)
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shards_metadata.append(shard_md)
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if shard_rank == rank:
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shard = Shard.from_tensor_and_offsets(
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torch.rand(*shard_md.shard_sizes),
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shard_offsets=shard_md.shard_offsets,
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rank=rank,
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)
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local_shards.append(shard)
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sharded_tensor_md = ShardedTensorMetadata(
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shards_metadata=shards_metadata,
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size=torch.Size([8 * len(shards_metadata)]),
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tensor_properties=TensorProperties.create_from_tensor(torch.zeros(1)),
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)
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return ShardedTensor._init_from_local_shards_and_global_metadata(
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local_shards=local_shards, sharded_tensor_metadata=sharded_tensor_md
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)
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class TestMedatadaIndex(TestCase):
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def test_init_convert_offset(self):
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a = MetadataIndex("foo", [1, 2])
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b = MetadataIndex("foo", torch.Size([1, 2]))
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self.assertEqual(a, b)
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def test_index_hint_ignored_on_equals(self):
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a = MetadataIndex("foo")
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b = MetadataIndex("foo", index=99)
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self.assertEqual(a, b)
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def test_index_hint_ignored_on_hash(self):
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a = MetadataIndex("foo")
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b = MetadataIndex("foo", index=99)
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self.assertEqual(hash(a), hash(b))
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def test_flat_data(self):
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state_dict = {
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"a": torch.rand(10),
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"b": [1, 2, 3],
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}
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a = find_state_dict_object(state_dict, MetadataIndex("a"))
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self.assertEqual(a, state_dict["a"])
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a = find_state_dict_object(state_dict, MetadataIndex("a", [0]))
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self.assertEqual(a, state_dict["a"])
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a = find_state_dict_object(state_dict, MetadataIndex("a", index=99))
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self.assertEqual(a, state_dict["a"])
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b = find_state_dict_object(state_dict, MetadataIndex("b"))
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self.assertEqual(b, state_dict["b"])
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b = find_state_dict_object(state_dict, MetadataIndex("b", index=1))
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self.assertEqual(b, state_dict["b"])
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with self.assertRaisesRegex(ValueError, "FQN"):
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find_state_dict_object(state_dict, MetadataIndex("c"))
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with self.assertRaisesRegex(ValueError, "ShardedTensor"):
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find_state_dict_object(state_dict, MetadataIndex("b", [1]))
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@with_fake_comms(rank=0, world_size=2)
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def test_sharded_tensor_lookup(self):
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st = create_sharded_tensor(rank=0, world_size=2, shards_per_rank=3)
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state_dict = {"st": st}
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obj = find_state_dict_object(state_dict, MetadataIndex("st", [8]))
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self.assertEqual(obj, st.local_shards()[1].tensor)
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# good hint
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obj = find_state_dict_object(state_dict, MetadataIndex("st", [8], index=1))
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self.assertEqual(obj, st.local_shards()[1].tensor)
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# bad hint
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obj = find_state_dict_object(state_dict, MetadataIndex("st", [8], index=2))
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self.assertEqual(obj, st.local_shards()[1].tensor)
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# broken hint
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obj = find_state_dict_object(state_dict, MetadataIndex("st", [8], index=99))
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self.assertEqual(obj, st.local_shards()[1].tensor)
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with self.assertRaisesRegex(ValueError, "no offset was provided"):
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find_state_dict_object(state_dict, MetadataIndex("st"))
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with self.assertRaisesRegex(ValueError, "Could not find shard"):
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find_state_dict_object(state_dict, MetadataIndex("st", [1]))
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def test_dcp_logger(self):
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self.assertTrue(_c10d_logger is not _dcp_logger)
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self.assertEqual(1, len(_c10d_logger.handlers))
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if __name__ == "__main__":
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run_tests()
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