code: def test_the_formation_of_initial_assumption():
      """Checks that the initial assumption is formed based on the given available operations"""
  
      train_input, _, _ = get_dataset(task_type="classification")
      train_input = DataPreprocessor().obligatory_prepare_for_fit(
          train_input
      )
      available_operations = ["dt"]
  
      initial_assumptions = (
          AssumptionsBuilder.get(train_input)
          .from_operations(available_operations)
          .build()
      )
      res_init_assumption = Pipeline(PipelineNode("dt"))
      assert (
          initial_assumptions[0].root_node.descriptive_id
          == res_init_assumption.root_node.descriptive_id
      )
  
imports: import logging
  from copy import deepcopy
  import pytest
  from examples.simple.classification.classification_pipelines import classification_pipeline_with_balancing, classification_pipeline_without_balancing
  from fedot import Fedot
  from fedot.api.api_utils.assumptions.assumptions_builder import AssumptionsBuilder
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.preprocessing.preprocessing import DataPreprocessor
  from test.data.datasets import get_cholesterol_dataset
  from test.integration.api.test_main_api import get_dataset
  from test.unit.tasks.test_classification import get_binary_classification_data
label_desc: Use image node_id 5 for calling a global function with example usage: test_the_formation_of_initial_assumption() without return types