class_docstr: Context manager to synchronize output from different sensors. Synchronous
  mode is enabled as long as we are inside this context
  
      with CARLASyncContext(world, sensors) as sync_mode:
          while True:
              data = sync_mode.tick(timeout=1.0)
  
  This code is based on https://github.com/carla-simulator/carla/blob/master/PythonAPI/examples/synchronous_mode.py
class_docstr_tok: ["Context","manager","to","synchronize","output","from","different","sensors",".","Synchronous","mode","is","enabled","as","long","as","we","are","inside","this","context","with","CARLASyncContext","(","world",",","sensors",")","as","sync_mode",":","while","True",":","data","=","sync_mode.tick","(","timeout=1.0",")","This","code","is","based","on","https",":","\/\/github.com\/carla-simulator\/carla\/blob\/master\/PythonAPI\/examples\/synchronous_mode.py"]
docstr: Retrieves data for sensors (i.e. camera and other) it blocks waiting until timeout is expired.
docstr_tok: ["Retrieves","data","for","sensors","(","i.e",".","camera","and","other",")","it","blocks","waiting","until","timeout","is","expired","."]
code: def _get_sensor_data(self, sensor_queue: queue.Queue, timeout: float):
      """Retrieves data for sensors (i.e. camera and other) it blocks waiting until timeout is expired."""
      while True:
          data = sensor_queue.get(timeout=timeout)
  
          if data.frame == self.frame:
              return data
  
file_path: tensorforce/tensorforce/environments/carla/synchronous_mode.py
imports: import carla
  import queue
label_desc: Use image node_id 7 for calling the CARLASyncContext obj's underlying member method code with example usage: obj._get_sensor_data(sensor_queue, timeout) and returns: data