FIX assert in EM algorithm to handle case where loss converges

tufts-ml-courses · Apr 1, 2020 · 6817272 · 6817272
1 parent 222e9ee
commit 6817272
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Showing 2 changed files with 4 additions and 5 deletions.
diff --git a/cp3/src/GMM_PenalizedMLEstimator_EM.py b/cp3/src/GMM_PenalizedMLEstimator_EM.py
@@ -300,7 +300,7 @@ def fit(self, x_ND, x_valid_ND=None, verbose=True):
                 # Verify the loss goes down after the M step
                 loss_m = self.calc_EM_loss(r_NK, x_ND)
                 self.history['train_loss_em'].append(loss_m)
-                ## TODO this should pass: assert loss_m + 1e-9 <= loss_e
+                ## TODO this should pass: assert loss_m <= loss_e + 1e-9 (UPDATED 2020-04-01)
 
             if verbose:
                 print("iter %4d / %4d after %9.1f sec | train loss % 9.6f %s" % (

diff --git a/cp3/src/GMM_PenalizedMLEstimator_LBFGS.py b/cp3/src/GMM_PenalizedMLEstimator_LBFGS.py
@@ -526,8 +526,6 @@ def callback_update_history(cur_param_vec):
         optimal_param_vec = result.x
         self.log_pi_K, self.mu_KD, self.stddev_KD = self.to_common_parameters_from_flat_array(optimal_param_vec)
 
-
-
     def write_history_to_csv(self, csv_path):
         ''' Write history of training to comma separated value (CSV) file
 
@@ -545,6 +543,7 @@ def write_history_to_csv(self, csv_path):
         None.
         '''
         df = pd.DataFrame()
-        for key in self.history:
-            df[key] = self.history[key]
+        cur_list = self.history[key]
+        if df.shape[0] == 0 or df.shape[0] == len(cur_list):
+            df[key] = cur_list
         df.to_csv(csv_path, index=False)