code: def get_pp_offsets():
      pp_rank = parallel_state.get_pipeline_model_parallel_rank()
      pp_size = parallel_state.get_pipeline_model_parallel_world_size()
      return ((0, pp_rank, pp_size),)
  
file_path: megatron-lm/tests/unit_tests/dist_checkpointing/models/test_mlp_glu.py
imports: import pytest
  import torch
  from torch.optim import Adam
  from megatron.core import parallel_state
  from megatron.core.dist_checkpointing.dict_utils import diff, nested_values
  from megatron.core.dist_checkpointing.optimizer import get_param_id_to_sharded_param_map, optim_state_to_sharding_state
  from megatron.core.transformer.mlp import MLP
  from tests.unit_tests.dist_checkpointing import TempNamedDir
  from tests.unit_tests.test_utilities import Utils
  from megatron.core.dist_checkpointing import save, load, load_plain_tensors, ShardedTensor
  from megatron.core.tensor_parallel.random import model_parallel_cuda_manual_seed
  from megatron.core.transformer.transformer_config import TransformerConfig
  from megatron.core.models.gpt.gpt_layer_specs import get_gpt_layer_with_transformer_engine_spec
label_desc: Use image node_id 2 for calling a global function with example usage: get_pp_offsets() and returns: int,  pp_rank,  pp_size