class_docstr: MF regularized TCN + TCN. This version is not for automated searching yet.
class_docstr_tok: ["MF","regularized","TCN","+","TCN",".","This","version","is","not","for","automated","searching","yet","."]
docstr: Incremental fitting given a pre-trained model.
  :param x: incremental data
  :param covariates_new: covariates corresponding to the incremental x
  :param dti_new: dti corresponding to the incremental x
  :return:
docstr_tok: ["Incremental","fitting","given","a","pre-trained","model",".",":","param","x",":","incremental","data",":","param","covariates_new",":","covariates","corresponding","to","the","incremental","x",":","param","dti_new",":","dti","corresponding","to","the","incremental","x",":","return",":"]
code: def fit_incremental(self, x, covariates_new=None, dti_new=None):
      """
      Incremental fitting given a pre-trained model.
      :param x: incremental data
      :param covariates_new: covariates corresponding to the incremental x
      :param dti_new: dti corresponding to the incremental x
      :return:
      """
      from bigdl.nano.utils.common import invalidInputError
  
      if x is None:
          invalidInputError(False, "Input invalid x of None")
      if self.model is None:
          invalidInputError(
              False,
              "Needs to call fit_eval or restore first before calling "
              "fit_incremental",
          )
      self._check_covariates_dti(
          covariates=covariates_new,
          dti=dti_new,
          ts_len=x.shape[1],
          method_name="fit_incremental",
      )
      self.model.inject_new(
          x, covariates_new=covariates_new, dti_new=dti_new
      )
  
imports: from abc import ABCMeta, abstractmethod
  from bigdl.chronos.model.tcmf import DeepGLO
  from bigdl.orca.automl.metrics import Evaluator
  from bigdl.orca.automl.model.abstract import BaseModel
  from bigdl.orca.data import SparkXShards, XShards
  import pickle
  import numpy
  import pandas
label_desc: Use image node_id 4 for calling the TCMF obj's underlying member method code with example usage: obj.fit_incremental(x, covariates_new, dti_new) without return types