class_docstr: Builder for constructing preprocessing part of pipeline during the preparation of an initial assumption.
  If data is multimodal, builder makes preprocessing pipeline for each data source iteratively.
docstr: Returns result as Pipeline. Scaling is applied final by default.
  
  Returns:
      adapted graph as pipeline
docstr_tok: ["Returns","result","as","Pipeline",".","Scaling","is","applied","final","by","default",".","Returns",":","adapted","graph","as","pipeline"]
code: def to_pipeline(self) -> Optional[Pipeline]:
      """
      Returns result as Pipeline. Scaling is applied final by default.
  
      Returns:
          adapted graph as pipeline
      """
      return self.to_builder().build()
  
file_path: FEDOT/fedot/api/api_utils/assumptions/preprocessing_builder.py
imports: from typing import Optional, Union
  from fedot.core.data.data import InputData
  from fedot.core.data.data_preprocessing import data_has_text_features
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.pipelines.pipeline_builder import PipelineBuilder
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import TaskTypesEnum
label_desc: Use image node_id 6 for calling the PreprocessingBuilder obj's underlying member method code with example usage: obj.to_pipeline() and returns: self