partially address --root CLI argument handling

- fix places where `get_config()` is being called at import time rather
  than at run time.

- add regression test for import time get_config() calling.

invokeai/backend/util/devices.py

@@ -12,11 +12,11 @@ from invokeai.app.services.config.config_default import get_config
 CPU_DEVICE = torch.device("cpu")
 CUDA_DEVICE = torch.device("cuda")
 MPS_DEVICE = torch.device("mps")
-config = get_config()
 
 
 def choose_torch_device() -> torch.device:
     """Convenience routine for guessing which GPU device to run model on"""
+    config = get_config()
     if config.device == "auto":
         if torch.cuda.is_available():
             return torch.device("cuda")
@@ -34,7 +34,7 @@ def choose_precision(
     device: torch.device, app_config: Optional[InvokeAIAppConfig] = None
 ) -> Literal["float32", "float16", "bfloat16"]:
     """Return an appropriate precision for the given torch device."""
-    app_config = app_config or config
+    app_config = app_config or get_config()
     if device.type == "cuda":
         device_name = torch.cuda.get_device_name(device)
         if not ("GeForce GTX 1660" in device_name or "GeForce GTX 1650" in device_name):

invokeai/backend/util/logging.py

@@ -339,7 +339,8 @@ class InvokeAILogger(object):  # noqa D102
     loggers: Dict[str, logging.Logger] = {}
 
     @classmethod
-    def get_logger(cls, name: str = "InvokeAI", config: InvokeAIAppConfig = get_config()) -> logging.Logger:  # noqa D102
+    def get_logger(cls, name: str = "InvokeAI", config: Optional[InvokeAIAppConfig] = None) -> logging.Logger:  # noqa D102
+        config = config or get_config()
         if name in cls.loggers:
             return cls.loggers[name]