code: def test_lgt_fixed_sm_input(
      make_weekly_data,
      level_sm_input,
      seasonality_sm_input,
      slope_sm_input,
  ):
      train_df, test_df, coef = make_weekly_data
  
      lgt = LGT(
          response_col="response",
          date_col="week",
          regressor_col=train_df.columns.tolist()[2:],
          level_sm_input=level_sm_input,
          seasonality_sm_input=seasonality_sm_input,
          slope_sm_input=slope_sm_input,
          estimator="stan-map",
          seasonality=52,
          verbose=False,
      )
  
      lgt.fit(train_df)
      predict_df = lgt.predict(test_df)
  
      regression_out = lgt.get_regression_coefs()
      num_regressors = regression_out.shape[0]
  
      expected_columns = ["week", "prediction"]
      expected_shape = (51, len(expected_columns))
      expected_regression_shape = (6, 3)
  
      assert predict_df.shape == expected_shape
      assert predict_df.columns.tolist() == expected_columns
      assert regression_out.shape == expected_regression_shape
      assert num_regressors == len(train_df.columns.tolist()[2:])
  
imports: from copy import copy
  import pytest
  import numpy
  from orbit.models import LGT
  from orbit.constants.constants import PredictionKeys
label_desc: Use image node_id 11 for calling a global function with example usage: test_lgt_fixed_sm_input(make_weekly_data, level_sm_input, seasonality_sm_input, slope_sm_input) without return types