code: def list_to_named_parameters(param_name, options):
      """Convert list of options for parameter to input to @parameterized.named_parameters.
  
      Arguments:
        param_name: name of parameter
        options: list of options for parameter
  
      Returns:
        named_params: input to @parameterized.named_parameters
  
      Needed to stack multiple parameters (e.g. with keras run_all_modes).
      """
  
      def snakecase_to_camelcase(value):
          # Non-comprensive check for camelcase already.
          if value[0].isupper() and "_" not in value:
              return value
  
          camelcase = ""
          for s in value.split("_"):
              camelcase += s.capitalize()
          return camelcase
  
      def name(s):
          if isinstance(s, str):
              return s
  
          return s.__name__
  
      named_params = []
      for key in options:
          named_params.append(
              {
                  "testcase_name": snakecase_to_camelcase(name(key)),
                  param_name: key,
              }
          )
      return named_params
  
file_path: model-optimization/tensorflow_model_optimization/python/core/sparsity/keras/test_utils.py
imports: import tempfile
  import numpy
  import tensorflow
  from tensorflow_model_optimization.python.core.sparsity.keras import prune
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_utils
  from tensorflow_model_optimization.python.core.sparsity.keras import pruning_wrapper
label_desc: Use image node_id 7 for calling a global function with example usage: list_to_named_parameters(param_name, options) and returns: named_params, camelcase, s, value, s