- fixed max index

- call status once inside epoch loop

src/rbm/layer.py

@@ -76,8 +76,6 @@ class Layer:
 
 				training_seen += 1
 
-		status.on_change({"progress": {"value": round(training_seen*d_progress), "unit": "%"}, "err_rms": {"value": err_rms, "unit": ""}})
-
 	def v_to_ph(self, v: np.ndarray) -> np.ndarray:
 		state = self.state.v_to_h(v)
 		if self.params.do_gaussian_visible:

src/rbm/rbm.py

@@ -25,7 +25,7 @@ class MyStatus(Status):
 		shape = self.stack.from_index(0).shape[0:2] + (1,)
 
 		# User input
-		max_index = self.batch.shape[0]
+		max_index = self.batch.shape[0] - 1
 		key = cv.waitKeyEx(1)
 		if key == ord('q'):
 			do_continue = False
@@ -74,20 +74,20 @@ def main(prj_name: str = "test"):
 	stack.state_load()
 
 	# Load train data
-	training_data_path = os.path.join(prj_root, f"{prj_name}.training.dat")
+	training_data = read_armadillo(os.path.join(prj_root, f"{prj_name}.training.dat"))
-	batch = read_armadillo(training_data_path)
+	test_data = read_armadillo(os.path.join(prj_root, f"{prj_name}.test.dat"))
 
 	# Prepare status listener
-	my_status = MyStatus(stack, batch)
+	my_status = MyStatus(stack, test_data)
 
 	# Train
-	stack.train(batch, status=my_status)
+	stack.train(training_data, status=my_status)
 
 	# Save state
 	stack.state_save()
 
 if __name__ == "__main__":
-	main("norb_small_16h")
+	main("norb_small_16h_v2")
 	cv.destroyAllWindows()
 
 	print("Test: [passed]")