content: """
  .. _resnet_cross_runtime_compilation_for_windows_example:
  
  cross runtime compilation limitations:
  The cross compile and saved model can only be loaded in Windows, it can no longer be loaded in Linux
  The cross compile and saved model can only be loaded in the same Compute Capability as the Linux which it was cross compiled
  (for example, if the model was cross compiled in Linux with GeForceRTX 4080 which has Compute Capability of 8.9,
  It cannot be loaded in Windows with GeForceRTX 3080 which has Compute Capability of 8.6)
  
  Cross runtime compilation for windows example
  ======================================================
  
  Compile and save the Resnet Model using Torch-TensorRT in Linux:
  
  python examples/dynamo/cross_runtime_compilation_for_windows.py --path trt_resnet.ep
  
  Load the Resnet Model saved in Windows:
  
  python examples/dynamo/cross_runtime_compilation_for_windows.py --path trt_resnet.ep --load True
  
  """
  
  # %%
  # Imports and Model Definition
  # ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  
  import argparse
  import platform
  
  import torch
  import torch_tensorrt as torchtrt
  import torchvision.models as models
  
  PARSER = argparse.ArgumentParser(
      description="Cross runtime comilation for windows example: Resnet Model"
  )
  PARSER.add_argument(
      "--load", default=False, type=bool, required=False, help="Load the model in Windows"
  )
  PARSER.add_argument(
      "--path",
      type=str,
      required=True,
      help="Path to the saved model file",
  )
  
  args = PARSER.parse_args()
  torch.manual_seed(0)
  model = models.resnet18().cuda().eval()
  input = torch.rand((1, 3, 224, 224)).to("cuda")
  inputs = [input]
  
  # %%
  # According to the argument, it is either cross compile and save resnet model for windows in Linux
  # or load the saved resnet model in Windows
  # ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  if args.load:
      # load the saved model in Windows
      if platform.system() != "Windows" or platform.machine() != "AMD64":
          raise ValueError(
              "cross runtime compiled model for windows can only be loaded in Windows system"
          )
      loaded_model = torchtrt.load_cross_compiled_exported_program(args.path).module()
      print(f"model has been successfully loaded from ${args.path}")
      # inference
      with torch.no_grad():
          trt_output = loaded_model(input)
      print(f"inference result: {trt_output}")
  else:
      if platform.system() != "Linux" or platform.architecture()[0] != "64bit":
          raise ValueError(
              "cross runtime compiled model for windows can only be compiled in Linux system"
          )
      compile_spec = {
          "min_block_size": 1,
      }
      torchtrt.cross_compile_for_windows(
          model, file_path=args.path, inputs=inputs, **compile_spec
      )
      print(
          f"model has been successfully cross compiled and saved in Linux to {args.path}"
      )
  