class_docstr: The estimator of NAS model.
  
  Parameters
  ----------
  loss_f: callable
      Default loss function for evaluation
  
  evaluation: list of autogl.module.train.evaluation.Evaluation
      Default evaluation metric
class_docstr_tok: ["The","estimator","of","NAS","model",".","Parameters","--","--","--","--","--","loss_f",":","callable","Default","loss","function","for","evaluation","evaluation",":","list","of","autogl.module.train.evaluation.Evaluation","Default","evaluation","metric"]
code: def __init__(self, loss_f: str = "nll_loss", evaluation=[Acc()]):
      self.loss_f = loss_f
      self.evaluation = evaluation
  
file_path: AutoGL/autogl/module/nas/estimator/base.py
imports: from abc import abstractmethod
  from ..space import BaseSpace
  from typing import Tuple
  from ...train.evaluation import Evaluation, Acc
  import torch.nn.functional
  import torch
label_desc: Use image node_id 1 to create a new BaseEstimator object  with example: obj = BaseEstimator(loss_f, evaluation)