code: def get_accelerators(
      project_id: str, zone: str, gpus: List[Gpu]
  ) -> List[compute_v1.AcceleratorConfig]:
      if len(gpus) == 0 or gpus[0].name in {"A100", "L4"}:
          # A100 and L4 are bundled with the instance
          return []
      accelerator_config = compute_v1.AcceleratorConfig()
      accelerator_config.accelerator_count = len(gpus)
      for acc in supported_accelerators:
          if (
              gpus[0].name == acc["gpu_name"]
              and gpus[0].memory_mib == acc["memory_mb"]
          ):
              accelerator_name = acc["accelerator_name"]
              break
      else:
          raise ValueError(
              f"Unsupported GPU: {gpus[0].name} {gpus[0].memory_mib} MiB"
          )
      accelerator_config.accelerator_type = f"projects/{project_id}/zones/{zone}/acceleratorTypes/{accelerator_name}"
      return [accelerator_config]
  
file_path: dstack/src/dstack/_internal/core/backends/gcp/resources.py
imports: from typing import Dict, List, Optional
  import google.api_core.exceptions
  import google.cloud.compute_v1
  from google.api_core.extended_operation import ExtendedOperation
  import dstack.version
  from dstack._internal.core.models.instances import Gpu
  from dstack._internal.utils.logging import get_logger
label_desc: Use image node_id 6 for calling a global function with example usage: get_accelerators(project_id, zone, gpus) and returns: list, list