code: def __init__(
      self,
      provider: NodeProvider,
      node_types: Dict[NodeType, NodeTypeConfigDict],
      max_workers: int,
      head_node_type: NodeType,
      upscaling_speed: float,
  ) -> None:
      self.provider = provider
      self.node_types = copy.deepcopy(node_types)
      self.node_resource_updated = set()
      self.max_workers = max_workers
      self.head_node_type = head_node_type
      self.upscaling_speed = upscaling_speed
  
      utilization_scorer_str = os.environ.get(
          AUTOSCALER_UTILIZATION_SCORER_KEY,
          "ray.autoscaler._private.resource_demand_scheduler"
          "._default_utilization_scorer",
      )
      self.utilization_scorer: UtilizationScorer = (
          load_function_or_class(utilization_scorer_str)
      )
  
imports: import collections
  import copy
  import logging
  import os
  from abc import abstractmethod
  from functools import partial
  from typing import Callable, Dict, List, Optional, Tuple
  import ray
  from ray._private.gcs_utils import PlacementGroupTableData
  from ray.autoscaler._private.constants import AUTOSCALER_CONSERVE_GPU_NODES, AUTOSCALER_UTILIZATION_SCORER_KEY
  from ray.autoscaler._private.loader import load_function_or_class
  from ray.autoscaler._private.node_provider_availability_tracker import NodeAvailabilitySummary
  from ray.autoscaler._private.util import NodeID, NodeIP, NodeType, NodeTypeConfigDict, ResourceDict, is_placement_group_resource
  from ray.autoscaler.node_provider import NodeProvider
  from ray.autoscaler.tags import NODE_KIND_HEAD, NODE_KIND_UNMANAGED, NODE_KIND_WORKER, TAG_RAY_NODE_KIND, TAG_RAY_USER_NODE_TYPE
  from ray.core.generated.common_pb2 import PlacementStrategy
label_desc: Use image node_id 1 to create a new ResourceDemandScheduler object  with example: obj = ResourceDemandScheduler(provider, node_types, max_workers, head_node_type, upscaling_speed)