code: def _get_config_values(
      config: AmericanOptionConfig,
  ) -> Tuple[str, int, types.IntTensor, int, int]:
      """Extracts config values."""
      [
          model,
          num_samples,
          seed,
          num_exercise_times,
          num_calibration_samples,
      ] = [
          config.model,
          config.num_samples,
          tf.convert_to_tensor(config.seed, name="seed"),
          config.num_exercise_times,
          config.num_calibration_samples,
      ]
      return (
          model,
          num_samples,
          seed,
          num_exercise_times,
          num_calibration_samples,
      )
  
imports: from typing import Any, Optional, List, Dict, Union, Tuple
  import dataclasses
  import tensorflow.compat.v2
  from tf_quant_finance import datetime
  from tf_quant_finance.experimental.pricing_platform.framework.core import curve_types
  from tf_quant_finance.experimental.pricing_platform.framework.core import instrument
  from tf_quant_finance.experimental.pricing_platform.framework.core import processed_market_data
  from tf_quant_finance.experimental.pricing_platform.framework.core import types
  from tf_quant_finance.experimental.pricing_platform.framework.equity_instruments import utils
  from tf_quant_finance.experimental.pricing_platform.framework.equity_instruments.american_option import proto_utils
  from tf_quant_finance.experimental.pricing_platform.framework.equity_instruments.american_option import utils
  from tf_quant_finance.experimental.pricing_platform.framework.market_data import utils
  from tf_quant_finance.experimental.pricing_platform.framework.rate_instruments import cashflow_streams
  from tf_quant_finance.experimental.pricing_platform.instrument_protos import american_equity_option_pb2
label_desc: Use image node_id 2 for calling a global function with example usage: _get_config_values(config) and returns: model,  num_samples,  seed,  num_exercise_times,  num_calibration_samples