class_docstr: Apply SMOTE for classification tasks.
  
  This will average a percentage p of the elements in the batch with other elements.
  The target will stay unchanged and keep the value of the most important row in the mix.
class_docstr_tok: ["Apply","SMOTE","for","classification","tasks",".","This","will","average","a","percentage","p","of","the","elements","in","the","batch","with","other","elements",".","The","target","will","stay","unchanged","and","keep","the","value","of","the","most","important","row","in","the","mix","."]
code: def _set_seed(self):
      torch.manual_seed(self.seed)
      np.random.seed(self.seed)
      return
  
file_path: tabnet/pytorch_tabnet/augmentations.py
imports: import torch
  from pytorch_tabnet.utils import define_device
  import numpy
label_desc: Use image node_id 2 for calling the ClassificationSMOTE obj's underlying member method code with example usage: obj._set_seed() without return types