Fix 'torch.device' object has no attribute 'gpu_id' issue in trt export (#8019)

Part of #8017


### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [ ] New tests added to cover the changes.
- [ ] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [ ] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [ ] In-line docstrings updated.
- [ ] Documentation updated, tested `make html` command in the `docs/`
folder.

---------

Signed-off-by: YunLiu <[email protected]>

Author: KumoLiu

monai/networks/utils.py

@@ -822,7 +822,7 @@ def _onnx_trt_compile(
     output_names = [] if not output_names else output_names
 
     # set up the TensorRT builder
-    torch_tensorrt.set_device(device)
+    torch.cuda.set_device(device)
     logger = trt.Logger(trt.Logger.WARNING)
     builder = trt.Builder(logger)
     network = builder.create_network(1 << int(trt.NetworkDefinitionCreationFlag.EXPLICIT_BATCH))
@@ -931,7 +931,7 @@ def convert_to_trt(
         warnings.warn(f"The dynamic batch range sequence should have 3 elements, but got {dynamic_batchsize} elements.")
 
     device = device if device else 0
-    target_device = torch.device(f"cuda:{device}") if device else torch.device("cuda:0")
+    target_device = torch.device(f"cuda:{device}")
     convert_precision = torch.float32 if precision == "fp32" else torch.half
     inputs = [torch.rand(ensure_tuple(input_shape)).to(target_device)]
 
@@ -986,7 +986,7 @@ def scale_batch_size(input_shape: Sequence[int], scale_num: int):
                     ir_model,
                     inputs=input_placeholder,
                     enabled_precisions=convert_precision,
-                    device=target_device,
+                    device=torch_tensorrt.Device(f"cuda:{device}"),
                     ir="torchscript",
                     **kwargs,
                 )

monai/utils/module.py

@@ -214,7 +214,6 @@ def load_submodules(
                     loader = mod_spec.loader
                     loader.exec_module(mod)
                     submodules.append(mod)
-
             except OptionalImportError:
                 pass  # could not import the optional deps., they are ignored
             except ImportError as e: