code: def _infer_enum_sharding_spec_case(self):
      shards_metadata = [
          ShardMetadata(
              shard_offsets=[0, 0],
              shard_sizes=[5, 5],
              placement="cuda:0",
          ),
          ShardMetadata(
              shard_offsets=[5, 0],
              shard_sizes=[10, 5],
              placement="cuda:1",
          ),
      ]
      spec = _infer_sharding_spec_from_shards_metadata(shards_metadata)
      self.assertTrue(isinstance(spec, EnumerableShardingSpec))
      self.assertEqual(spec.shards, shards_metadata)
  
      shards_metadata = [
          ShardMetadata(
              shard_offsets=[0],
              shard_sizes=[16],
              placement="cuda:0",
          ),
          ShardMetadata(
              shard_offsets=[16],
              shard_sizes=[9],
              placement="cuda:1",
          ),
      ]
      spec = _infer_sharding_spec_from_shards_metadata(shards_metadata)
      self.assertTrue(isinstance(spec, EnumerableShardingSpec))
      self.assertEqual(spec.shards, shards_metadata)
  
      shards_metadata = [
          ShardMetadata(
              shard_offsets=[0, 0],
              shard_sizes=[5, 5],
              placement="rank:0/cuda:0",
          ),
          ShardMetadata(
              shard_offsets=[5, 0],
              shard_sizes=[5, 5],
              placement="rank:1/cuda:1",
          ),
          ShardMetadata(
              shard_offsets=[0, 5],
              shard_sizes=[5, 5],
              placement="rank:2/cuda:2",
          ),
          ShardMetadata(
              shard_offsets=[5, 5],
              shard_sizes=[5, 5],
              placement="rank:3/cuda:3",
          ),
      ]
      spec = _infer_sharding_spec_from_shards_metadata(shards_metadata)
      self.assertTrue(isinstance(spec, EnumerableShardingSpec))
      self.assertEqual(spec.shards, shards_metadata)
  
imports: from typing import List, Union
  from dataclasses import dataclass
  import copy
  import torch
  from torch.testing._internal.common_utils import TestCase
  from torch.testing._internal.common_distributed import requires_nccl, skip_if_lt_x_gpu
  from torch.distributed._shard import sharded_tensor, _shard_tensor
  from torch.distributed._shard.sharding_spec import ShardingSpec, ChunkShardingSpec, DevicePlacementSpec, EnumerableShardingSpec, ShardMetadata, _infer_sharding_spec_from_shards_metadata
  from torch.distributed._shard.sharded_tensor import TensorProperties, ShardedTensor, ShardedTensorMetadata
  from torch.distributed._shard.sharding_spec._internals import check_tensor, get_split_size, get_chunked_dim_size, get_chunk_sharding_params, validate_non_overlapping_shards_metadata
  from torch.testing._internal.common_cuda import TEST_MULTIGPU
  from torch.testing._internal.common_utils import run_tests, skip_but_pass_in_sandcastle_if
  from torch.testing._internal.distributed._shard.sharded_tensor._test_st_common import _chunk_sharding_specs_list_for_test
  from torch.testing._internal.distributed._shard.sharded_tensor import ShardedTensorTestBase, with_comms
label_desc: Use image node_id 7 for calling the TestShardingSpec obj's underlying member method code with example usage: obj._infer_enum_sharding_spec_case() without return types