code: def get_llm_trainer_cls(trainer_type: str):
      """Returns the adapter config class registered with the given name."""
      return _llm_trainer_schema_registry[trainer_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 3 for calling a global function with example usage: get_llm_trainer_cls(trainer_type) and returns: _llm_trainer_schema_registry