content: import os
  import platform
  import tempfile
  
  import torch
  from torch_tensorrt._Device import Device
  from torch_tensorrt._enums import EngineCapability, dtype
  
  ENABLED_PRECISIONS = {dtype.f32}
  DEVICE = None
  DISABLE_TF32 = False
  ASSUME_DYNAMIC_SHAPE_SUPPORT = False
  DLA_LOCAL_DRAM_SIZE = 1073741824
  DLA_GLOBAL_DRAM_SIZE = 536870912
  DLA_SRAM_SIZE = 1048576
  ENGINE_CAPABILITY = EngineCapability.STANDARD
  WORKSPACE_SIZE = 0
  MIN_BLOCK_SIZE = 5
  PASS_THROUGH_BUILD_FAILURES = False
  MAX_AUX_STREAMS = None
  NUM_AVG_TIMING_ITERS = 1
  VERSION_COMPATIBLE = False
  OPTIMIZATION_LEVEL = None
  SPARSE_WEIGHTS = False
  TRUNCATE_DOUBLE = False
  USE_PYTHON_RUNTIME = False
  USE_FAST_PARTITIONER = True
  ENABLE_EXPERIMENTAL_DECOMPOSITIONS = False
  REQUIRE_FULL_COMPILATION = False
  DRYRUN = False
  HARDWARE_COMPATIBLE = False
  SUPPORTED_KERNEL_PRECISIONS = {
      dtype.f32,
      dtype.f16,
      dtype.bf16,
      dtype.i8,
      dtype.f8,
      dtype.f4,
  }
  TIMING_CACHE_PATH = os.path.join(
      tempfile.gettempdir(), "torch_tensorrt_engine_cache", "timing_cache.bin"
  )
  LAZY_ENGINE_INIT = False
  CACHE_BUILT_ENGINES = False
  REUSE_CACHED_ENGINES = False
  ENGINE_CACHE_DIR = os.path.join(tempfile.gettempdir(), "torch_tensorrt_engine_cache")
  ENGINE_CACHE_SIZE = 5368709120  # 5GB
  CUSTOM_ENGINE_CACHE = None
  USE_EXPLICIT_TYPING = True
  USE_FP32_ACC = False
  REFIT_IDENTICAL_ENGINE_WEIGHTS = False
  STRIP_ENGINE_WEIGHTS = False
  IMMUTABLE_WEIGHTS = True
  ENABLE_WEIGHT_STREAMING = False
  ENABLE_CROSS_COMPILE_FOR_WINDOWS = False
  TILING_OPTIMIZATION_LEVEL = "none"
  L2_LIMIT_FOR_TILING = -1
  USE_DISTRIBUTED_MODE_TRACE = False
  OFFLOAD_MODULE_TO_CPU = False
  ENABLE_AUTOCAST = False
  AUTOCAST_LOW_PRECISION_TYPE = None
  AUTOCAST_EXCLUDED_NODES = set[str]()
  AUTOCAST_EXCLUDED_OPS = set[torch.fx.node.Target]()
  AUTOCAST_MAX_OUTPUT_THRESHOLD = 512
  AUTOCAST_MAX_DEPTH_OF_REDUCTION = None
  AUTOCAST_CALIBRATION_DATALOADER = None
  ENABLE_RESOURCE_PARTITIONING = False
  CPU_MEMORY_BUDGET = None
  
  if platform.system() == "Linux":
      import pwd
  
      current_user = pwd.getpwuid(os.getuid())[0]
  else:
      import getpass
  
      current_user = getpass.getuser()
  
  DEBUG_LOGGING_DIR = os.path.join(
      tempfile.gettempdir(), f"torch_tensorrt_{current_user}/debug_logs"
  )
  
  
  def default_device() -> Device:
      return Device(gpu_id=torch.cuda.current_device())
  