testing twoclassbatch

src/model/classifiers.py

@@ -18,11 +18,11 @@ class AuthorshipAttributionClassifier(nn.Module):
         self.device = device
 
     def fit(self, X, y, batch_size, epochs, lr=0.001, val_prop=0.1, log='../log/tmp.csv'):
-        batcher = Batch(batch_size=batch_size, n_epochs=epochs)
+        #batcher = Batch(batch_size=batch_size, n_epochs=epochs)
+        batcher = TwoClassBatch(batch_size=batch_size, n_epochs=epochs, steps_per_epoch=X.shape[0]//batch_size)
         batcher_val = Batch(batch_size=batch_size, n_epochs=epochs, shuffle=False)
         criterion = torch.nn.CrossEntropyLoss().to(self.device)
         optim = torch.optim.Adam(self.parameters(), lr=lr)
-        #optim = torch.optim.Adadelta(self.parameters(), lr=lr)
 
         X, Xval, y, yval = train_test_split(X, y, test_size=val_prop, stratify=y)