code: def get_simple_pipeline(
      model: str,
      custom_params: dict = None,
      use_input_preprocessing: bool = True,
  ) -> "Pipeline":
      surrogate_node = PipelineNode(model)
      if custom_params:
          surrogate_node.parameters = custom_params
      return Pipeline(
          surrogate_node,
          use_input_preprocessing=use_input_preprocessing,
      )
  
imports: import os
  from copy import deepcopy
  from inspect import signature
  from typing import Optional
  from matplotlib import pyplot
  from sklearn import tree
  from sklearn.tree._tree import TREE_LEAF
  from fedot.core.composer.metrics import Metric
  from fedot.core.composer.metrics import R2, F1
  from fedot.core.data.data import InputData
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.tasks import TaskTypesEnum
  from fedot.explainability.explainer_template import Explainer
label_desc: Use image node_id 1 for calling a global function with example usage: get_simple_pipeline(model, custom_params, use_input_preprocessing) and returns: Pipeline