Added a check on the aux file such that if it is not a real file, it is set to None and doesn't get used. This protects against an incorrect default argument.

Author: Corey Adams

bin/exec.py

@@ -358,6 +358,7 @@ def add_core_configuration(self, parser):
 
         return parser
 
+
     def add_io_arguments(self, parser):
 
         # data_directory = "/lus/theta-fs0/projects/datascience/cadams/datasets/SBND/H5/cosmic_tagging/"
@@ -370,6 +371,12 @@ def add_io_arguments(self, parser):
             default = data_directory + "cosmic_tagging_train.h5",
             help    = "IO Input File")
 
+        parser.add_argument('--aux-file',
+            type    = str,
+            default = data_directory + "cosmic_tagging_test.h5",
+            help    = "IO Aux Input File, or output file in inference mode")
+
+
         parser.add_argument('--start-index',
             type    = int,
             default = 0,
@@ -380,14 +387,6 @@ def add_io_arguments(self, parser):
             default = 2,
             help    = "Number of images in the minibatch size")
 
-        # IO PARAMETERS FOR AUX INPUT:
-        parser.add_argument('--aux-file',
-            type    = str,
-            # default = None,
-            default = data_directory + "cosmic_tagging_test.h5",
-            help    = "IO Aux Input File, or output file in inference mode")
-
-
         parser.add_argument('--aux-iteration',
             type    = int,
             default = 10,

src/utils/core/trainercore.py

@@ -58,14 +58,23 @@ def _initialize_io(self, color=None):
 
         if self.args.mode == "build_net": return
 
+        # Check that the training file exists:
+        if not os.path.isfile(self.args.file):
+            raise Exception(f"Can not continue with file {self.args.file} - does not exist.")
+        if not os.path.isfile(self.args.aux_file):
+            if self.args.mode == "train":
+                self.print("WARNING: Aux file does not exist.  Setting to None for training")
+                self.args.aux_file = None
+            else:
+                raise Exception("Writing of output currently not supported but will be soon.")
+
         self._train_data_size = self.larcv_fetcher.prepare_cosmic_sample(
             "train", self.args.file, self.args.minibatch_size, color)
 
         if self.args.aux_file is not None:
             # Check if the file exists:
-            if os.path.isfile(self.args.aux_file):
-                self._aux_data_size = self.larcv_fetcher.prepare_cosmic_sample(
-                    "aux", self.args.aux_file, self.args.minibatch_size, color)
+            self._aux_data_size = self.larcv_fetcher.prepare_cosmic_sample(
+                "aux", self.args.aux_file, self.args.minibatch_size, color)
 
     def build_lr_schedule(self, learning_rate_schedule = None):
         # Define the learning rate sequence: