- removed Optimizer

- refactored training
- use static seed for random (for better comparison)
- simplified StackDeep.train

src/rbm/matrix.py

@@ -13,7 +13,8 @@ else:
 	def convert(src: Mat):
 		return src
 
-np.random.seed(int(time.monotonic()))
+np.random.seed(12345)
+
 def uniform(shape: tuple, mu: float = 0.5, std: float = 1.0) -> Mat:
 	return std * (np.random.rand(shape[0], shape[1]) + mu - 0.5)