code: def make_moons_input_data(samples):
      X, y = make_moons(
          n_samples=samples, shuffle=True, noise=0.1, random_state=137
      )
  
      train_data = InputData(
          idx=list(range(len(X))),
          features=X,
          target=y,
          task=Task(TaskTypesEnum.classification),
          data_type=DataTypesEnum.table,
      )
      test_data = InputData(
          idx=list(range(len(X))),
          features=X,
          target=y,
          task=Task(TaskTypesEnum.classification),
          data_type=DataTypesEnum.table,
      )
  
      return train_data, test_data
  
file_path: FEDOT/examples/advanced/gpu_example.py
imports: from datetime import datetime
  from typing import Tuple
  from sklearn.datasets import make_moons
  from examples.simple.classification.classification_pipelines import classification_svc_complex_pipeline
  from fedot import Fedot
  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.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.core.utils import fedot_project_root
label_desc: Use image node_id 4 for calling a global function with example usage: make_moons_input_data(samples) and returns: train_data,  test_data