class_docstr: An estimator which trans from scratch
  
  Parameters
  ----------
  loss_f : str
      The name of loss funciton in PyTorch
  evaluation : list of Evaluation
      The evaluation metrics in module/train/evaluation
class_docstr_tok: ["An","estimator","which","trans","from","scratch","Parameters","--","--","--","--","--","loss_f",":","str","The","name","of","loss","funciton","in","PyTorch","evaluation",":","list","of","Evaluation","The","evaluation","metrics","in","module\/train\/evaluation"]
code: def __init__(self, loss_f="nll_loss", evaluation=[Acc()]):
      super().__init__(loss_f, evaluation)
      self.evaluation = evaluation
      self.estimator = OneShotEstimator(self.loss_f, self.evaluation)
  
file_path: AutoGL/autogl/module/nas/estimator/train_scratch.py
imports: from .None import register_nas_estimator
  from ..space import BaseSpace
  from .base import BaseEstimator
  from .one_shot import OneShotEstimator, OneShotEstimator_HardwareAware
  import torch
  from autogl.module.train import NodeClassificationFullTrainer, Acc
label_desc: Use image node_id 1 to create a new TrainEstimator object from inherited base classes: BaseEstimator with example: obj = TrainEstimator(loss_f, evaluation)