code: def _has_gpu_quota(
      quotas: Dict[str, int], resources: Resources
  ) -> bool:
      if not resources.gpus:
          return True
      gpu = resources.gpus[0]
      quota_name = f"NVIDIA_{gpu.name}_GPUS"
      if gpu.name == "A100" and gpu.memory_mib == 80 * 1024:
          quota_name = "NVIDIA_A100_80GB_GPUS"
      if resources.spot:
          quota_name = "PREEMPTIBLE_" + quota_name
      return len(resources.gpus) <= quotas.get(quota_name, 0)
  
imports: from collections import defaultdict
  from typing import Callable, Dict, List, Optional, Tuple
  import google.api_core.exceptions
  import google.cloud.compute_v1
  import dstack._internal.core.backends.gcp.auth
  import dstack._internal.core.backends.gcp.resources
  from dstack._internal.core.backends.base.compute import Compute, get_gateway_user_data, get_instance_name, get_user_data
  from dstack._internal.core.backends.base.offers import get_catalog_offers
  from dstack._internal.core.backends.gcp.config import GCPConfig
  from dstack._internal.core.errors import NoCapacityError, ResourceNotFoundError
  from dstack._internal.core.models.backends.base import BackendType
  from dstack._internal.core.models.instances import InstanceAvailability, InstanceOffer, InstanceOfferWithAvailability, InstanceType, LaunchedGatewayInfo, LaunchedInstanceInfo, Resources
  from dstack._internal.core.models.runs import Job, Requirements, Run
label_desc: Use image node_id 2 for calling a global function with example usage: _has_gpu_quota(quotas, resources) and returns: unknown, True