Create trainer.py

trainer.py

@@ -0,0 +1,16 @@
+import numpy as np
+
+
+class SelfTrainer:
+    def __init__(self, system):
+        self.system = system
+
+    def objective(self):
+        return -np.linalg.norm(self.system.Xi)
+
+    def train_step(self):
+        Psi = np.random.randn(self.system.n)
+        self.system.step(Psi)
+
+        if self.objective() > -1:
+            self.system.Xi *= 0.98