code: def data_setup() -> InputData:
      predictors, response = load_iris(return_X_y=True)
      predictors = predictors[:100]
      response = response[:100]
      data = InputData(
          features=predictors,
          target=response,
          idx=np.arange(0, 100),
          task=Task(TaskTypesEnum.classification),
          data_type=DataTypesEnum.table,
      )
      return data
  
imports: import os
  from copy import deepcopy, copy
  import numpy
  import pandas
  import pytest
  from sklearn.datasets import load_iris
  from fedot.core.data.data import InputData, get_df_from_csv
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.core.utils import fedot_project_root
  from test.unit.tasks.test_forecasting import get_ts_data_with_dt_idx
label_desc: Use image node_id 1 for calling a global function with example usage: data_setup() and returns: data