built class for training all networks, including working fixpoint check and some experiments on that

code/experiment.py

@@ -2,6 +2,7 @@ import sys
 import os
 import time
 import dill
+from tqdm import tqdm
 
 
 class Experiment:
@@ -69,15 +70,23 @@ class FixpointExperiment(Experiment):
                 self.counters['fix_zero'] += 1
             else:
                 self.counters['fix_other'] += 1
-                self.interesting_fixpoints.append(net)
-                self.log(net.repr_weights())
-                net.self_attack()
-                self.log(net.repr_weights())
+                self.interesting_fixpoints.append(net.get_weights())
         elif net.is_fixpoint(2):
             self.counters['fix_sec'] += 1
         else:
             self.counters['other'] += 1
             
+class MixedFixpointExperiment(FixpointExperiment):
+
+    def run_net(self, net, trains_per_application=100, step_limit=100):
+        i = 0
+        while i < step_limit and not net.is_diverged() and not net.is_fixpoint():
+            net.self_attack()
+            for _ in tqdm(range(trains_per_application)):
+                loss = net.compiled().train()
+            i += 1
+        self.count(net)
+    
             
 class SoupExperiment(Experiment):
     pass