code: def forward(self, features: KeyedJaggedTensor) -> KeyedJaggedTensor:
      cat_seq = torch.ops.fbgemm.offsets_range(
          features.offsets().long(), torch.numel(features.values())
      )
  
      return KeyedJaggedTensor(
          keys=features.keys(),
          values=features.values(),
          weights=get_weights_list(
              cat_seq, features, self.position_weights_dict
          ),
          lengths=features.lengths(),
          offsets=features.offsets(),
          stride=features.stride(),
          length_per_key=features.length_per_key(),
      )
  
imports: import abc
  from typing import Dict, Optional
  import torch
  from torch import nn
  from torchrec.sparse.jagged_tensor import JaggedTensor, KeyedJaggedTensor
label_desc: Use image node_id 3 for calling the PositionWeightedModuleCollection obj's underlying member method code with example usage: obj.forward(features) and returns: KeyedJaggedTensor