class_docstr: Base class for all problem configs.
  Defines the interface for all problem configs.
class_docstr_tok: ["Base","class","for","all","problem","configs",".","Defines","the","interface","for","all","problem","configs","."]
code: def from_dict(cls, cfg_dict: dict):
      class_fields = {f.name: f for f in dataclasses.fields(cls)}
  
      # Prepare arguments for creating a new dataclass instance
      init_args = {}
      for field_name, field_obj in class_fields.items():
          if hasattr(field_obj.type, "from_dict"):
              attr_value = cfg_dict.get(field_name, {})
              init_args[field_name] = field_obj.type.from_dict(
                  attr_value
              )
          else:
              # Use the value from cfg_dict,
              # or the field's default value if not available in cfg_dict
              init_args[field_name] = cfg_dict.get(
                  field_name, field_obj.default
              )
  
      return cls(**init_args)
  
imports: import dataclasses
  import logging
  from dataclasses import dataclass, fields
  from typing import Any, Dict, List, Optional, Sequence, Set, Tuple
  from llm_studio.src import possible_values
  from llm_studio.src.nesting import Dependency, Nesting
  from llm_studio.src.order import Order
  from llm_studio.src.tooltips import tooltips
label_desc: Use image node_id 2 for calling the DefaultConfigProblemBase obj's underlying member method code with example usage: obj.from_dict(cls, cfg_dict) and returns: cls