class_docstr: Regresses one or more floating point values given a set of documents per example.
  
  :param config: A :py:class:`finetune.config.Settings` object or None (for default config).
  :param \**kwargs: key-value pairs of config items to override.
class_docstr_tok: ["Regresses","one","or","more","floating","point","values","given","a","set","of","documents","per","example",".",":","param","config",":","A",":","py",":","class",":","`","finetune.config.Settings","`","object","or","None","(","for","default","config",")",".",":","param","\\","*","*","kwargs",":","key-value","pairs","of","config","items","to","override","."]
code: def _get_input_pipeline(self):
      return MultiFieldRegressionPipeline(self.config)
  
imports: import copy
  from finetune.errors import FinetuneError
  from finetune.target_models.classifier import Classifier, ClassificationPipeline
  from finetune.target_models.regressor import Regressor, RegressionPipeline
  from finetune.base import BaseModel
label_desc: Use image node_id 1 for calling the MultiFieldRegressor obj's underlying member method code with example usage: obj._get_input_pipeline() and returns: MultiFieldRegressionPipeline