code: def test_blend_model_basic(load_setup, load_models, method):
      """Tests basic blender functionality for all methods"""
      from sktime.forecasting.compose import EnsembleForecaster
  
      exp = load_setup
      models = load_models
      weights = [random.uniform(0, 1) for _ in range(len(models))]
      blender = exp.blend_models(
          models, method=method, weights=weights, verbose=False
      )
      assert isinstance(blender, EnsembleForecaster)
  
      # Test input models are available
      blender_forecasters = blender.forecasters_
      blender_forecasters_class = [
          f.__class__ for f in blender_forecasters
      ]
      ts_models_class = [f.__class__ for f in models]
      assert blender_forecasters_class == ts_models_class
  
file_path: pycaret/tests/test_time_series_blending.py
imports: import random
  import numpy
  import pandas
  import pytest
  from pycaret.datasets import get_data
  from pycaret.time_series import TSForecastingExperiment
label_desc: Use image node_id 1 for calling a global function with example usage: test_blend_model_basic(load_setup, load_models, method) without return types