continual without enforcement

decoder_demos/ndt2_sample.py

@@ -37,11 +37,17 @@ def main():
     parser.add_argument(
         '--batch-size', type=int, default=1
     )
+    parser.add_argument(
+        '--continual', action='store_true', default=False
+    )
+
     args = parser.parse_args()
 
     evaluator = FalconEvaluator(
         eval_remote=args.evaluation == "remote",
-        split=args.split)
+        split=args.split,
+        continual=args.continual
+    )
 
     task = getattr(FalconTask, args.split)
     config = FalconConfig(task=task)

falcon_challenge/evaluator.py

@@ -277,9 +277,10 @@ def simple_collater(batch, task):
 
 class FalconEvaluator:
 
-    def __init__(self, eval_remote=False, split='h1'):
+    def __init__(self, eval_remote=False, split='h1', continual=False):
         self.eval_remote = eval_remote
         assert split in ['h1', 'h2', 'm1', 'm2'], "Split must be h1, h2, m1, or m2."
+        self.continual = continual
         self.dataset: FalconTask = getattr(FalconTask, split)
         self.cfg = FalconConfig(self.dataset)
 
@@ -374,7 +375,8 @@ def predict_files(self, decoder: BCIDecoder, eval_files: List):
                     if trial_delta_obs[0]:
                         trial_preds.append(decoder.on_done(trial_delta_obs))
                 else:
-                    decoder.on_done(trial_delta_obs)
+                    if not self.continual:
+                        decoder.on_done(trial_delta_obs)
                     step_prediction = decoder.predict(neural_observations)
                     assert step_prediction.shape[1] == self.cfg.out_dim, f"Prediction shape mismatch: {step_prediction.shape[1]} vs {self.cfg.out_dim}."
                     trial_preds.append(step_prediction)

setup.py

@@ -2,7 +2,7 @@
 
 setup(
     name='falcon_challenge',
-    version='0.3.3',
+    version='0.3.4',
 
     url='https://github.com/snel-repo/stability-benchmark',
     author='Joel Ye',