code: def test_api_composer_available_operations():
      """Checks if available_operations goes through all fitting process"""
      task = Task(
          TaskTypesEnum.ts_forecasting,
          TsForecastingParams(forecast_length=1),
      )
      train_data, _, _ = get_dataset(task_type="ts_forecasting")
      available_operations = ["lagged"]
      model = Fedot(
          problem="ts_forecasting",
          task_params=task.task_params,
          timeout=0.01,
          available_operations=available_operations,
          pop_size=500,
      )
      model.fit(train_data)
      assert (
          model.params.get("available_operations")
          == available_operations
      )
  
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 7 for calling a global function with example usage: test_api_composer_available_operations() without return types