src/machine_learning/neural_network/learning_neural_network.py

@@ -30,7 +30,6 @@ if __name__ == '__main__':
 		
 		for epoch in range(n_iter):
 			for image, label in zip(train_images, train_labels):
-				print(image.shape)
 				optimizer.zero_grad()
 				
 				output = model(image)
@@ -44,7 +43,7 @@ if __name__ == '__main__':
 	train(model, 100)
 	
 	# def accuracy(expected, predicted):
-	# 	return len([1 for e, p in zip(expected, predicted) if e == p]) / len(expected)
+	# 	return len([_ for e, p in zip(expected, predicted) if e == p]) / len(expected)
 	#
 	#
 	# predicted = [model(image).argmax() for image in train_images]