code: def create_inst(inst, seq_len):
      output = {
          "input_ids_0": torch.tensor(
              inst["input_ids_0"], dtype=torch.long
          )[:seq_len]
      }
      output["mask_0"] = (output["input_ids_0"] != 0).float()
  
      if "input_ids_1" in inst:
          output["input_ids_1"] = torch.tensor(
              inst["input_ids_1"], dtype=torch.long
          )[:seq_len]
          output["mask_1"] = (output["input_ids_1"] != 0).float()
      output["label"] = torch.tensor(inst["label"], dtype=torch.long)
      return output
  
file_path: xformers/xformers/benchmarks/LRA/code/dataset.py
imports: import logging
  import pickle
  import torch
  from torch.utils.data.dataset import Dataset
label_desc: Use image node_id 4 for calling the LRADataset obj's underlying member method code with example usage: obj.create_inst(inst, seq_len) and returns: output