feat: Add support for device compilation setting

[gs-olive]

Description

• Enables support for device compilation settings in Dynamo paths
• Developed in a way such that extensions for multiple gpus can be made in a straightforward fashion
  • Default device type/format can be customized
• Defaults to current present device, with context-aware switching, enable the following workflow for torch compile:

    with torch.cuda.device(1):
        model = models.resnet18(pretrained=True).eval().cuda()
        input = torch.randn((1, 3, 224, 224)).cuda()

        compile_spec = {
            "inputs": [
                torchtrt.Input(
                    input.shape, dtype=torch.float, format=torch.contiguous_format
                )
            ],
            "enabled_precisions": {torch.float},
            "debug": True,
            "ir": "torch_compile",
        }

        trt_mod = torchtrt.compile(model, **compile_spec)

Fixes #2172

Type of change

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)

Checklist:

• [ x ] My code follows the style guidelines of this project (You can use the linters)
• [ x ] I have performed a self-review of my own code
• [ x ] I have commented my code, particularly in hard-to-understand areas and hacks
• [ x ] I have made corresponding changes to the documentation
• [ x ] I have added tests to verify my fix or my feature
• [ x ] New and existing unit tests pass locally with my changes
• [ x ] I have added the relevant labels to my PR in so that relevant reviewers are notified

[gs-olive]

Device is now populated with a default factory once the CompilationSettings object gets instantiated.

[gs-olive]

Device can now be None, which will take the Torch default device.

[gs-olive]

If the device is None, we use the default Torch context device

[narendasan]

LGTM

[peri044]

LGTM