code: def get_shrunk_dlrm_num_embeddings(
      reduction_degree: int,
  ) -> List[int]:
      return [
          num_emb
          if num_emb < 10000000
          else int(num_emb / reduction_degree)
          for num_emb in DLRM_NUM_EMBEDDINGS_PER_FEATURE
      ]
  
file_path: torchrec/benchmarks/ebc_benchmarks.py
imports: import argparse
  import sys
  from typing import List, Tuple
  import torch
  from fbgemm_gpu.split_table_batched_embeddings_ops_training import EmbeddingLocation
  from torchrec.github.benchmarks import ebc_benchmarks_utils
  from torchrec.modules.embedding_configs import EmbeddingBagConfig
  from torchrec.modules.embedding_modules import EmbeddingBagCollection
  from torchrec.modules.fused_embedding_modules import FusedEmbeddingBagCollection
label_desc: Use image node_id 1 for calling a global function with example usage: get_shrunk_dlrm_num_embeddings(reduction_degree) and returns: unknown