docstr: Check if a parameter is marked as partially derived in sequence parallelism.
  
  Args:
      param: The parameter to check.
  
  Returns:
      bool: True if the parameter is marked as partially derived, False otherwise.
docstr_tok: ["Check","if","a","parameter","is","marked","as","partially","derived","in","sequence","parallelism",".","Args",":","param",":","The","parameter","to","check",".","Returns",":","bool",":","True","if","the","parameter","is","marked","as","partially","derived",",","False","otherwise","."]
code: def is_sp_partial_derived_param(param):
      """
      Check if a parameter is marked as partially derived in sequence parallelism.
  
      Args:
          param: The parameter to check.
  
      Returns:
          bool: True if the parameter is marked as partially derived, False otherwise.
      """
      return getattr(param, "partial_derived", False)
  
imports: from contextlib import contextmanager
  from typing import List
  import torch
  import torch.distributed
  from torch import nn
  from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
  from torch.distributed import ProcessGroup, get_world_size
  from colossalai.utils.device import get_current_device, get_rng_state, set_rng_state, manual_seed
label_desc: Use image node_id 2 for calling the SeqParallelUtils obj's underlying member method code with example usage: obj.is_sp_partial_derived_param(param) and returns: getattr