code: def _populate_implicit_field(
      json_ai: JsonAI,
      field_name: str,
      implicit_value: dict,
      is_timeseries: bool,
  ) -> None:
      """
      Populate the implicit field of the JsonAI, either by filling it in entirely if missing, or by introspecting the class or function and assigning default values to the args in it's signature that are in the implicit default but haven't been populated by the user
  
      :params: json_ai: ``JsonAI`` object that describes the ML pipeline that may not have every detail fully specified.
      :params: field_name: Name of the field the implicit field in ``JsonAI``
      :params: implicit_value: The dictionary containing implicit values for the module and arg in the field
      :params: is_timeseries: Whether or not this is a timeseries problem
  
      :returns: nothing, this method mutates the respective field of the ``JsonAI`` object it receives
      """  # noqa
      # These imports might be slow, in which case the only <easy> solution is to line this code
      field = json_ai.__getattribute__(field_name)
      if field is None:
          # This if is to only populated timeseries-specific implicit fields for implicit problems
          if is_timeseries or field_name not in (
              "timeseries_analyzer",
              "timeseries_transformer",
          ):
              field = implicit_value
  
      # If the user specified one or more subfields in a field that's a list
      # Populate them with implicit arguments form the implicit values from that subfield
      elif isinstance(field, list) and isinstance(implicit_value, list):
          for i in range(len(field)):
              sub_field_implicit = [
                  x
                  for x in implicit_value
                  if x["module"] == field[i]["module"]
              ]
              if len(sub_field_implicit) == 1:
                  field[i] = _merge_implicit_values(
                      field[i], sub_field_implicit[0]
                  )
          for sub_field_implicit in implicit_value:
              if (
                  len(
                      [
                          x
                          for x in field
                          if x["module"] == sub_field_implicit["module"]
                      ]
                  )
                  == 0
              ):
                  field.append(sub_field_implicit)
      # If the user specified the field, add implicit arguments which we didn't specify
      else:
          field = _merge_implicit_values(field, implicit_value)
      json_ai.__setattr__(field_name, field)
  
file_path: lightwood/lightwood/api/json_ai.py
imports: import inspect
  from type_infer.dtype import dtype
  from type_infer.base import TypeInformation
  from dataprep_ml import StatisticalAnalysis
  from lightwood.helpers.templating import _consolidate_analysis_blocks, _add_cls_kwarg
  from lightwood.helpers.constants import IMPORTS, IMPORT_EXTERNAL_DIRS
  from lightwood.api.types import JsonAI, ProblemDefinition
  import lightwood.ensemble
  import lightwood.encoder
label_desc: Use image node_id 4 for calling a global function with example usage: _populate_implicit_field(json_ai, field_name, implicit_value, is_timeseries) without return types