code: def inputs(self, bs=1, seq_len=1, hidden_size=128):
      hidden_states = torch.randn(bs, seq_len, hidden_size)
      attention_mask = torch.randint(
          low=0, high=2, size=(bs, seq_len), dtype=torch.bool
      )
      return (hidden_states, 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_megatron_version
  from unit.megatron_model import MockGPT2ModelPipe
  from deepspeed.utils import RepeatingLoader
  from deepspeed.accelerator import get_accelerator
  from deepspeed.runtime.utils import required_torch_version
label_desc: Use image node_id 2 for calling the ConfigurablePP obj's underlying member method code with example usage: obj.inputs(bs, seq_len, hidden_size) and returns: hidden_states,  attention_mask