docstr: Determine the necessary dependencies to produce `keys`.
  
  For a simple shuffle, output partitions always depend on
  all input partitions. This method does not require graph
  materialization.
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code: def _cull_dependencies(
      self, keys: Iterable[str], parts_out: Iterable[str] | None = None
  ):
      """Determine the necessary dependencies to produce `keys`.
  
      For a simple shuffle, output partitions always depend on
      all input partitions. This method does not require graph
      materialization.
      """
      deps = {}
      parts_out = parts_out or self._keys_to_parts(keys)
      keys = {
          (self.name_input_left, i) for i in range(self.npartitions)
      }
      keys |= {
          (self.name_input_right, i) for i in range(self.npartitions)
      }
      # Protect against mutations later on with frozenset
      keys = frozenset(keys)
      for part in parts_out:
          deps[(self.name, part)] = keys
      return deps
  
imports: from __future__ import annotations
  from collections.abc import Iterable, Sequence
  from typing import TYPE_CHECKING, Any
  import dask
  from dask.base import is_dask_collection, tokenize
  from dask.highlevelgraph import HighLevelGraph
  from dask.layers import Layer
  from distributed.shuffle._arrow import check_minimal_arrow_version
  from distributed.shuffle._core import ShuffleId, barrier_key, get_worker_plugin
  from distributed.shuffle._shuffle import shuffle_barrier, shuffle_transfer
label_desc: Use image node_id 2 for calling the HashJoinP2PLayer obj's underlying member method code with example usage: obj._cull_dependencies(keys, parts_out) and returns: deps