code: def inputs(self, bs=1, seq_len=20):
      input_ids = torch.randint(low=0, high=1000, size=(bs, seq_len))
      position_ids = torch.randint(low=0, high=2, size=(bs, seq_len))
      attention_mask = torch.randint(
          low=0, high=2, size=(bs, seq_len), dtype=torch.bool
      )
      return [input_ids, position_ids, attention_mask]
  
imports: import os
  import torch
  import deepspeed
  import pytest
  import random
  import numpy
  import deepspeed.comm
  from unit.common import DistributedTest, DistributedFixture
  from unit.megatron_model import get_gpt2_model, get_megatron_version
label_desc: Use image node_id 2 for calling the ConfigurableMP obj's underlying member method code with example usage: obj.inputs(bs, seq_len) and returns: list