code: def parse_values(values, type_map, ignore_unknown=False):
      """Parses hyperparameter values from a string into a python map.
  
      `values` is a string containing comma-separated `name=value` pairs.
      For each pair, the value of the hyperparameter named `name` is set to
      `value`.
  
      If a hyperparameter name appears multiple times in `values`, a ValueError
      is raised (e.g. 'a=1,a=2', 'a[1]=1,a[1]=2').
  
      If a hyperparameter name in both an index assignment and scalar assignment,
      a ValueError is raised.  (e.g. 'a=[1,2,3],a[0] = 1').
  
      The hyperparameter name may contain '.' symbols, which will result in an
      attribute name that is only accessible through the getattr and setattr
      functions.  (And must be first explicit added through add_hparam.)
  
      WARNING: Use of '.' in your variable names is allowed, but is not well
      supported and not recommended.
  
      The `value` in `name=value` must follows the syntax according to the
      type of the parameter:
  
      *  Scalar integer: A Python-parsable integer point value.  E.g.: 1,
         100, -12.
      *  Scalar float: A Python-parsable floating point value.  E.g.: 1.0,
         -.54e89.
      *  Boolean: Either true or false.
      *  Scalar string: A non-empty sequence of characters, excluding comma,
         spaces, and square brackets.  E.g.: foo, bar_1.
      *  List: A comma separated list of scalar values of the parameter type
         enclosed in square brackets.  E.g.: [1,2,3], [1.0,1e-12], [high,low].
  
      When index assignment is used, the corresponding type_map key should be the
      list name.  E.g. for "arr[1]=0" the type_map must have the key "arr" (not
      "arr[1]").
  
      Args:
        values: String.  Comma separated list of `name=value` pairs where
          'value' must follow the syntax described above.
        type_map: A dictionary mapping hyperparameter names to types.  Note every
          parameter name in values must be a key in type_map.  The values must
          conform to the types indicated, where a value V is said to conform to a
          type T if either V has type T, or V is a list of elements of type T.
          Hence, for a multidimensional parameter 'x' taking float values,
          'x=[0.1,0.2]' will parse successfully if type_map['x'] = float.
        ignore_unknown: Bool. Whether values that are missing a type in type_map
          should be ignored. If set to True, a ValueError will not be raised for
          unknown hyperparameter type.
  
      Returns:
        A python map mapping each name to either:
        * A scalar value.
        * A list of scalar values.
        * A dictionary mapping index numbers to scalar values.
        (e.g. "x=5,L=[1,2],arr[1]=3" results in {'x':5,'L':[1,2],'arr':{1:3}}")
  
      Raises:
        ValueError: If there is a problem with input.
        * If `values` cannot be parsed.
        * If a list is assigned to a list index (e.g. 'a[1] = [1,2,3]').
        * If the same rvalue is assigned two different values (e.g. 'a=1,a=2',
          'a[1]=1,a[1]=2', or 'a=1,a=[1]')
      """
      results_dictionary = {}
      pos = 0
      while pos < len(values):
          m = PARAM_RE.match(values, pos)
          if not m:
              raise ValueError(
                  "Malformed hyperparameter value: %s" % values[pos:]
              )
          # Check that there is a comma between parameters and move past it.
          pos = m.end()
          # Parse the values.
          m_dict = m.groupdict()
          name = m_dict["name"]
          if name not in type_map:
              if ignore_unknown:
                  continue
              raise ValueError(
                  "Unknown hyperparameter type for %s" % name
              )
          type_ = type_map[name]
  
          # Set up correct parsing function (depending on whether type_ is a bool)
          if type_ == bool:
  
              def parse_bool(value):
                  if value in ["true", "True"]:
                      return True
                  elif value in ["false", "False"]:
                      return False
                  else:
                      try:
                          return bool(int(value))
                      except ValueError:
                          _parse_fail(name, type_, value, values)
  
              parse = parse_bool
          else:
              parse = type_
  
          # If a singe value is provided
          if m_dict["val"] is not None:
              _process_scalar_value(
                  name, parse, type_, m_dict, values, results_dictionary
              )
  
          # If the assigned value is a list:
          elif m_dict["vals"] is not None:
              _process_list_value(
                  name, parse, type_, m_dict, values, results_dictionary
              )
  
          else:  # Not assigned a list or value
              _parse_fail(name, type_, "", values)
  
      return results_dictionary
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import json
  import numbers
  import re
  from model_search.proto import hparam_pb2
  import six
label_desc: Use image node_id 9 for calling a global function with example usage: parse_values(values, type_map, ignore_unknown) and returns: results_dictionary, True, False, bool