code: def get_loss_conds(feature_type: str):
      """Returns a JSON schema of conditionals to validate against loss types for specific feature types."""
      conds = []
      for loss in get_loss_classes(feature_type):
          loss_cls = get_loss_cls(feature_type, loss)
          other_props = (
              schema_utils.unload_jsonschema_from_marshmallow_class(
                  loss_cls
              )["properties"]
          )
          schema_utils.remove_duplicate_fields(other_props)
          loss_cond = schema_utils.create_cond(
              {"type": loss},
              other_props,
          )
          conds.append(loss_cond)
      return conds
  
imports: from dataclasses import Field
  from typing import Type
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.schema import utils
  from ludwig.schema.features.loss import get_loss_classes, get_loss_cls
label_desc: Use image node_id 1 for calling a global function with example usage: get_loss_conds(feature_type) and returns: conds