code: def generate_enumerable_sharding_specs_for_test():
      return [
          EnumerableShardingSpec(
              [
                  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",
                  ),
              ]
          )
      ]
  
file_path: pytorch/torch/testing/_internal/distributed/_shard/sharded_tensor/_test_ops_common.py
imports: import builtins
  import torch
  from torch.distributed._shard.sharding_spec import ChunkShardingSpec, EnumerableShardingSpec, ShardMetadata
  from torch.distributed._shard.sharding_spec._internals import get_chunked_dim_size, get_split_size
label_desc: Use image node_id 2 for calling a global function with example usage: generate_enumerable_sharding_specs_for_test() and returns: list