code: def get_trainer_jsonschema(model_type: str):
      trainer_cls = trainer_schema_registry[model_type]
      props = schema_utils.unload_jsonschema_from_marshmallow_class(
          trainer_cls
      )["properties"]
  
      return {
          "type": "object",
          "properties": props,
          "title": "trainer_options",
          "additionalProperties": False,
          "description": "Schema for trainer determined by Model Type",
      }
  
imports: from abc import ABC
  from typing import Optional, Type, Union
  import torch
  from packaging.version import parse
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.constants import AUTO, EFFECTIVE_BATCH_SIZE, LOSS, MAX_BATCH_SIZE, MAX_POSSIBLE_BATCH_SIZE, MODEL_ECD, MODEL_GBM, MODEL_LLM, TRAINING
  from ludwig.error import ConfigValidationError
  from ludwig.schema import utils
  from ludwig.schema.lr_scheduler import LRSchedulerConfig, LRSchedulerDataclassField
  from ludwig.schema.metadata import TRAINER_METADATA
  from ludwig.schema.optimizers import BaseOptimizerConfig, GradientClippingConfig, GradientClippingDataclassField, OptimizerDataclassField
  from ludwig.schema.profiler import ProfilerConfig, ProfilerDataclassField
  from ludwig.schema.utils import ludwig_dataclass
  from ludwig.utils.registry import Registry
label_desc: Use image node_id 5 for calling a global function with example usage: get_trainer_jsonschema(model_type) and returns: dict