refactored

src/tests/test_norbs.py

@@ -37,17 +37,19 @@ if __name__ == "__main__":
 	model.load()
 
 	# Load train data
-	batch = read_armadillo(os.path.join(prj_root, f"{prj_name}.training.dat"))
+	train_batch = read_armadillo(os.path.join(prj_root, f"{prj_name}.training.dat"))
+
+	# Load test data
+	test_batch = read_armadillo(os.path.join(prj_root, f"{prj_name}.test.dat"))
 
 	# Train
-	model.train(batch, TrainingParams(learning_rate=0.00001, momentum=0.9, do_rao_blackwell=True, num_epochs=100, num_gibbs_samples=3))
+	model.train(train_batch, TrainingParams(learning_rate=0.00001, momentum=0.9, do_rao_blackwell=True, num_epochs=100, num_gibbs_samples=3))
 
 	# save state
 	model.save()
 
-	num_patterns = len(batch)
-	fig, axes = plt.subplots(1, num_patterns, figsize=(12, 3))
-	for index, inp in enumerate(batch):
+	fig, axes = plt.subplots(1, len(test_batch), figsize=(12, 3))
+	for index, inp in enumerate(test_batch):
 		out_normalized = model.backward(model.forward(inp))
 		img = 2*(out_normalized + 0.5)
 		img = np.reshape(img, (96, 96))