consolidated a few checks

GANDLF/utils/parameter_processing.py

@@ -21,22 +21,22 @@ def populate_header_in_parameters(parameters, headers):
         parameters["model"]["num_classes"] = len(headers["predictionHeaders"])
 
     # initialize model type for processing: if not defined, default to torch
-    if not ("type" in parameters["model"]):
-        parameters["model"]["type"] = "torch"
+    parameters["model"]["type"] = parameters["model"].get("type", "torch")
 
     if parameters["model"]["type"] == "openvino" and parameters["model"][
         "architecture"
     ] in ["brain_age", "sdnet"]:
         print(
-            "Only PyTorch for inference is supported for the current model architecture: {0}.".format(
+            "Only PyTorch for inference is supported for the current network topology: {0}.".format(
                 parameters["model"]["architecture"]
             )
         )
         parameters["model"]["type"] = "torch"
 
     # initialize number of channels for processing
-    if not ("num_channels" in parameters["model"]):
-        parameters["model"]["num_channels"] = len(headers["channelHeaders"])
+    parameters["model"]["num_channels"] = parameters["model"].get(
+        "num_channels", len(headers["channelHeaders"])
+    )
 
     parameters["problem_type"] = find_problem_type(
         parameters, get_modelbase_final_layer(parameters["model"]["final_layer"])