text: from multiprocessing import Condition
  from queue import SimpleQueue
  from typing import Any, Dict
  
  from numba import cuda
  
  from blazer.logs import logging
  
  from ..mpi.primitives import comm, host, rank, size
  from .utils import main
  
  ranks_exit_request: SimpleQueue = SimpleQueue()
  
  
  def handle_request(host_queues, requests, gpu_request):
      if type(gpu_request) is dict:
          destination = gpu_request["rank"]
          host = gpu_request["host"]
      else:
          parts = gpu_request.split(":")
          if gpu_request == "pass":
              return
          if len(parts) != 3:
              logging.warn("Invalid message %s", gpu_request)
              return
  
          host = parts[1]
          destination = parts[2]
  
      logging.debug("[%s][%s] Got gpu request: %s", host, rank, gpu_request)
      logging.debug("[%s][%s] Got gpu request[host_queues]: %s", host, rank, host_queues)
      gpu_queue = host_queues[host]
  
      if destination:
          logging.debug(
              "Master sending GPU allocation to rank[%s] queue size %s",
              int(destination),
              gpu_queue.qsize(),
          )
          try:
              gpu = gpu_queue.get(block=False)
              if gpu:
                  logging.debug("Master Got GPU from QUEUE %s", gpu)
                  comm.send(gpu, dest=int(destination), tag=1)
          except Exception as ex:
              logging.debug(
                  "Master storing GPU request for rank[%s] queue size %s",
                  int(destination),
                  gpu_queue.qsize(),
              )
              requests.put(gpu_request)
  
  
  class gpu:
      using_gpu: Dict[str, Any] = {}
  
      gpu_queue: SimpleQueue = SimpleQueue()
      requests: SimpleQueue = SimpleQueue()
  
      host_queues: dict = {}
      lock = Condition()
      total_released = 0
      has_cuda = False
  
      def __init__(self, *args, **kwargs):
          logging.debug("[%s][%s] GPU Context init %s", host, rank, kwargs)
  
          self.kwargs = kwargs
  
          # Master node reads list of gpus for each node in fabric
          # Then it places those GPU definitions on individual queues for each
          # host
  
          def load_gpus():
              from blazer.hpc.mpi import parallel
              from blazer.hpc.mpi import partial as p
              from blazer.hpc.mpi import rank, size
  
              def get_gpus():
                  import platform
  
                  from blazer.hpc.mpi import rank
  
                  logging.debug("GETTING GPU for rank[%s]", rank)
                  try:
                      gpus = main()
                      for gpu in gpus:
                          gpu["host"] = platform.node()
                          gpu["rank"] = rank
                      return gpus
                  except:
                      return []
  
              gpu_calls = [p(get_gpus) for i in range(1, size)]
              gpus = parallel(gpu_calls)
              if not gpus:
                  gpus = []
              gpulist = [gpu for gpu in gpus if len(gpu) > 0]
  
              logging.debug("GOT GPUs for rank[%s] %s", rank, gpulist)
              return gpulist
  
          self.GPUS = []
  
          try:
              from pydash import flatten
  
              if rank == 0:
                  self.GPUS = load_gpus()
                  self.GPUS = flatten(self.GPUS)
                  self.gpuranks = len(self.GPUS)
                  for gpu in self.GPUS:
                      if gpu["host"] not in self.host_queues:
                          self.host_queues[gpu["host"]] = SimpleQueue()
                      self.host_queues[gpu["host"]].put(gpu)
  
                  # comm.Barrier()
  
              else:
                  import platform
  
                  # print("WAITING FOR MASTER TO GATHER GPU DATA")
                  # comm.Barrier()
                  logging.info("[%s][%s] GPU context init. Checking my GPUS", host, rank)
                  try:
                      gpus = main()
                      for gpu in gpus:
                          gpu["host"] = platform.node()
                          gpu["rank"] = rank
                      self.GPUS = flatten(gpus)
                  except Exception as ex:
                      logging.error(ex)
                      self.GPUS = []
  
                  logging.info("GOT GPUs for [%s][%s] %s", host, rank, self.GPUS)
  
          except Exception as ex:
              import traceback
  
              print(traceback.format_exc())
              logging.warn("No GPUS found")
          finally:
              return None
  
      def __enter__(self, *args, **kwargs) -> Any:
          logging.debug("[%s][%s] GPU Context enter", host, rank)
  
          while True:
  
              if rank == 0:
                  logging.debug(
                      "[%s][%s] Master waiting on gpu request from rank", host, rank
                  )
                  logging.debug("Master requests %s", self.requests.qsize())
                  logging.debug(
                      "size is %s and ranks_exit_request.qsize()+1 is %s",
                      size,
                      ranks_exit_request.qsize() + 1,
                  )
  
                  logging.debug(
                      "total_released %s size %s", self.total_released, size - 1
                  )
                  logging.debug(
                      "gpuranks is %s and ranks_exit_request.qsize()+1 is %s",
                      self.gpuranks,
                      ranks_exit_request.qsize() + 1,
                  )
                  # If the # of rank exist requests + 1 (master) equals the total number of ranks
                  # Then master node can exit. All ranks have reported in
                  if self.gpuranks == ranks_exit_request.qsize() + 1:
                      logging.debug(
                          "MASTER FINISHED: total_released = %s", self.total_released
                      )
                      break
  
                  # Wait for GPU requests on tag 1. Block until we get a message
                  logging.debug("MASTER recv")
                  gpu_request = comm.recv(tag=1)
                  logging.debug("MASTER got gpu_request")
  
                  logging.debug(
                      "[%s][%s] Master got request from rank %s", host, rank, gpu_request
                  )
  
                  if type(gpu_request) is dict and "release" in gpu_request:
                      del gpu_request["release"]
  
                      try:
                          logging.debug("[%s][%s] Master acquiring lock", host, rank)
                          self.lock.acquire()
                          self.total_released += 1
                          ranks_exit_request.put("exit")
                      finally:
                          logging.debug("[%s][%s] Master releasing lock", host, rank)
                          self.lock.release()
  
                      logging.debug("[%s][%s] Release GPU %s", host, rank, gpu_request)
                      try:
                          request = self.requests.get(block=False)
                          logging.debug("Got REQUEST %s", request)
                      except Exception as ex:
                          request = None
  
                      # Put this GPU back on the queue for that host
                      self.host_queues[gpu_request["host"]].put(gpu_request)
  
                      # Are there any pending GPU requests on the requests queue?
                      if request:
                          handle_request(self.host_queues, self.requests, request)
                  else:
                      if gpu_request == "break":
                          logging.debug("[%s][%s] MASTER IS BREAKING", host, rank)
                          break
  
                      # Handle the message
                      handle_request(self.host_queues, self.requests, gpu_request)
              else:
                  if len(self.GPUS) == 0:
                      logging.debug(
                          "[%s][%s] I don't have any GPUS so just exiting", host, rank
                      )
                      break
  
                  logging.debug("[%s][%s] Sending gpu request", host, rank)
  
                  # Request a GPU from master node.
                  comm.send(f"gpu:{host}:{rank}", dest=0, tag=1)
  
                  # Block until we get one: NOTE: What if server finishes and this receive is never fulfilled?
                  logging.debug("[%s][%s] RECV Waiting for gpu", host, rank)
                  self.using_gpu = gpu = comm.recv(source=0, tag=1)
  
                  logging.debug("[%s][%s] RECV Received GPU[%s]", host, rank, gpu)
                  cuda.select_device(gpu["id"])
                  self.has_cuda = True
                  # Resume context in app code
                  return gpu
  
          logging.debug("[%s][%s] Exiting GPU context: ", host, rank)
  
      def __exit__(self, exc_type, exc_value, exc_traceback) -> Any:
          # notify master of releasing this gpu
  
          logging.debug("[%s][%s] GPU Context exit", host, rank)
  
          if self.has_cuda:
              cuda.close()
  
              # Worker context is exiting, therefore, send our GPU definition back to the head
              # node and exit the context
              if rank != 0:
                  self.using_gpu["release"] = True
                  self.using_gpu["rank"] = rank
                  logging.debug(
                      "[%s][%s] GPU Context exit: sending gpu back to master GPU %s",
                      host,
                      rank,
                      self.using_gpu,
                  )
                  comm.send(self.using_gpu, dest=0, tag=1)
                  logging.debug(
                      "[%s][%s] GPU Context exit: released GPU %s",
                      host,
                      rank,
                      self.using_gpu,
                  )
                  # ranks_exit_request.put("exit")
              else:
                  # Master node exiting GPU context. Receive any stuck messages?
                  logging.debug("[%s][%s] MASTER GPU Context exit", host, rank)
          else:
              comm.send("pass", dest=0, tag=1)
  