code: def param_is_not_tensor_parallel_duplicate(
      param: torch.Tensor,
  ) -> bool:
      return (
          hasattr(param, "tensor_model_parallel")
          and param.tensor_model_parallel
      ) or (get_tensor_model_parallel_rank() == 0)
  
imports: from typing import Optional, Dict, Tuple, List
  import warnings
  import torch
  import torch.nn.functional
  import torch.nn.init
  from torch.nn.parameter import Parameter
  from apex._autocast_utils import _cast_if_autocast_enabled
  from apex.transformer.parallel_state import get_tensor_model_parallel_group
  from apex.transformer.parallel_state import get_tensor_model_parallel_rank
  from apex.transformer.parallel_state import get_tensor_model_parallel_world_size
  from apex.transformer.utils import divide
  from apex.transformer.tensor_parallel.mappings import copy_to_tensor_model_parallel_region
  from apex.transformer.tensor_parallel.mappings import gather_from_tensor_model_parallel_region
  from apex.transformer.tensor_parallel.mappings import reduce_from_tensor_model_parallel_region
  from apex.transformer.tensor_parallel.mappings import scatter_to_tensor_model_parallel_region
  from apex.transformer.tensor_parallel.mappings import reduce_scatter_to_sequence_parallel_region
  from apex.transformer.tensor_parallel.random import get_cuda_rng_tracker
  from apex.transformer.tensor_parallel.utils import VocabUtility
  from apex.transformer.log_util import get_transformer_logger
label_desc: Use image node_id 1 for calling a global function with example usage: param_is_not_tensor_parallel_duplicate(param) and returns: unknown