Update configuration to speed it up.

pes_to_spec/bnn.py

@@ -200,10 +200,10 @@ class BNNModel(RegressorMixin, BaseEstimator):
         self.model = BNN(X.shape[1], y.shape[1])
 
         # prepare data loader
-        B = 100
+        B = 50
         loader = DataLoader(ds,
                             batch_size=B,
-                            num_workers=32,
+                            num_workers=20,
                             shuffle=True,
                             #pin_memory=True,
                             drop_last=True,
@@ -222,7 +222,7 @@ class BNNModel(RegressorMixin, BaseEstimator):
 
         # train
         self.model.train()
-        epochs = 1000
+        epochs = 500
         for epoch in range(epochs):
             meter = {k: AverageMeter(k, ':6.3f')
                     for k in ('loss', '-log(lkl)', '-log(prior)', '-log(hyper)', 'sigma', 'w.prec.')}

pes_to_spec/test/offline_analysis.py

@@ -144,7 +144,7 @@ def main():
     parser.add_argument('-o', '--offset', type=int, metavar='INT', default=0, help='Train ID offset')
     parser.add_argument('-c', '--xgm_cut', type=float, metavar='INTENSITY', default=500, help='XGM intensity threshold in uJ.')
     parser.add_argument('-e', '--bnn', action="store_true", default=False, help='Use BNN?')
-    parser.add_argument('-w', '--weight', action="store_true", default=True, help='Whether to reweight data as a function of the pulse energy to make it invariant to that.')
+    parser.add_argument('-w', '--weight', action="store_true", default=False, help='Whether to reweight data as a function of the pulse energy to make it invariant to that.')
 
     args = parser.parse_args()