code: def _get_expected_cache_prefetch_time(
      ddr_mem_bw: float,
      expected_cache_fetches: float,
      emb_dim: int,
      table_data_type_size: float,
  ) -> float:
      # TODO: validate cost model with empirical test
      prefetch_bytes = (
          expected_cache_fetches * emb_dim * table_data_type_size
      )
      return prefetch_bytes / ddr_mem_bw
  
imports: import logging
  import math
  from typing import cast, Dict, List, Optional, Tuple, Type
  import torch
  import torchrec.optim
  from torch import nn
  from torchrec.distributed.embedding_types import EmbeddingComputeKernel
  from torchrec.distributed.planner.constants import BATCHED_COPY_PERF_FACTOR, BIGINT_DTYPE, DP_ELEMENTWISE_KERNELS_PERF_FACTOR, FULL_BLOCK_EMB_DIM, HALF_BLOCK_PENALTY, kernel_bw_lookup, QUARTER_BLOCK_PENALTY, UVM_CACHING_RATIO, WEIGHTED_KERNEL_MULTIPLIER
  from torchrec.distributed.planner.types import ParameterConstraints, Perf, PlannerError, ShardEstimator, ShardingOption, Storage, Topology
  from torchrec.distributed.planner.utils import prod, sharder_name
  from torchrec.distributed.types import CacheStatistics, CommOp, ModuleSharder, ShardingType
  from torchrec.modules.embedding_modules import EmbeddingBagCollectionInterface
label_desc: Use image node_id 2 for calling a global function with example usage: _get_expected_cache_prefetch_time(ddr_mem_bw, expected_cache_fetches, emb_dim, table_data_type_size) and returns: unknown