code: def __init__(
      self,
      max_models=None,
      config=None,
      reserved=750000000,
      ram_max_frac=0.8,
  ):
      self.loaded_models = list()
      self.max_models = max_models
      self.gpu_memory_limit = None
      self.model_cache = dict()
      self.max_above_resting = None
      self.previous_in_use = 0
      self.max_model_size = None
      self.config = config or {}
      self.reserved = reserved
      self.ram_max_frac = ram_max_frac
      self.etl_cache = EtlCache()
  
imports: from collections import OrderedDict
  import gc
  import logging
  import functools
  import psutil
  from finetune.target_models.sequence_labeling import SequenceLabeler
  import tensorflow
  from finetune.base import BaseModel
  from finetune.custom_ops import BytesInUse, BytesLimit, MaxBytesInUse
  from finetune.errors import FinetuneSchedulerError
label_desc: Use image node_id 1 to create a new Scheduler object  with example: obj = Scheduler(max_models, config, reserved, ram_max_frac)