{
  "context": "This criteria evaluates how well the engineer uses PyCUDA's context management and synchronization capabilities to implement a GPU context manager. It focuses on proper device initialization, context lifecycle management, synchronization operations, and device property queries.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Device initialization",
      "description": "Uses pycuda.driver.Device to initialize and select the GPU device by device_id in the __init__ method",
      "max_score": 15
    },
    {
      "name": "Context creation",
      "description": "Uses pycuda.driver.Context or pycuda.autoinit to create/initialize a CUDA context in the __enter__ method",
      "max_score": 20
    },
    {
      "name": "Context cleanup",
      "description": "Properly cleans up the context in the __exit__ method using Context.pop() or Context.detach() to release GPU resources",
      "max_score": 20
    },
    {
      "name": "Context synchronization",
      "description": "Uses pycuda.driver.Context.synchronize() or pycuda.driver.Context.get_current().synchronize() in the synchronize method to ensure GPU operations complete",
      "max_score": 25
    },
    {
      "name": "Device properties",
      "description": "Uses Device.name() and Device.total_memory() methods to retrieve device information in the get_device_info method",
      "max_score": 20
    }
  ]
}