code: def trim_to_layer(
      layer: int,
      num_sampled_nodes_per_hop: List[int],
      num_sampled_edges_per_hop: List[int],
      x: Tensor,
      edge_index: Adj,
      edge_attr: Optional[Tensor] = None,
  ) -> Tuple[Tensor, Tensor, Optional[Tensor]]:
      pass
  
file_path: pytorch_geometric/torch_geometric/utils/_trim_to_layer.py
imports: import copy
  from typing import Any, Dict, List, Optional, Tuple, Union, overload
  import torch
  from torch import Tensor
  from torch_geometric.typing import Adj, EdgeType, MaybeHeteroAdjTensor, MaybeHeteroEdgeTensor, MaybeHeteroNodeTensor, NodeType, SparseStorage, SparseTensor
label_desc: Use image node_id 2 for calling a global function with example usage: trim_to_layer(layer, num_sampled_nodes_per_hop, num_sampled_edges_per_hop, x, edge_index, edge_attr) without return types