add some snark about the kludge I had to fix, and the kludge I used to fix it

codes/train.py

@@ -110,6 +110,8 @@ class Trainer:
                 self.dataset_debugger = get_dataset_debugger(dataset_opt)
                 if self.dataset_debugger is not None and resume_state is not None:
                     self.dataset_debugger.load_state(opt_get(resume_state, ['dataset_debugger_state'], {}))
+                # it will indefinitely try to train if your batch size is larger than your dataset
+                # could just whine when generating the YAML rather than assert here
                 if len(self.train_set) <= dataset_opt['batch_size']:
                     raise Exception("dataset size is less than batch size, consider reducing your batch size, or increasing your dataset.")
                 train_size = int(math.ceil(len(self.train_set) / dataset_opt['batch_size']))

codes/trainer/inject.py

@@ -34,6 +34,7 @@ def format_injector_name(name):
 # Works by loading all python modules in the injectors/ directory and sniffing out subclasses of Injector.
 # field will be properly populated.
 def find_registered_injectors(base_path="trainer/injectors"):
+    # this has the same modification networks.py has, so be sure to mirror it
     path = os.path.normpath(os.path.join(os.path.dirname(os.path.realpath(__file__)), f'../{base_path}'))
     module_iter = pkgutil.walk_packages([path])
     results = {}

codes/trainer/networks.py

@@ -30,6 +30,12 @@ def register_model(func):
     func._dlas_registered_model = True
     return func
 
+# this had some weird kludge that I don't understand needing to have a reference frame around the current working directory
+# it works better when you set it relative to this file instead
+# however, this has very different behavior when importing DLAS from outside the repo, rather than spawning a shell instance to a script within it
+# I can't be assed to deal with that headache at the moment, I just want something to work right now without needing to touch a shell
+
+# inject.py has a similar loader scheme, be sure to mirror it if you touch this too
 def find_registered_model_fns(base_path='models'):
     found_fns = {}
     path = os.path.normpath(os.path.join(os.path.dirname(os.path.realpath(__file__)), f'../{base_path}'))