From ad450b0a5bb63ee9731e88d4a8e7423b16f1abd8 Mon Sep 17 00:00:00 2001
From: tvayer <titouan.vayer@gmail.com>
Date: Tue, 4 Jun 2019 10:32:30 +0200
Subject: changes forgotten coments

---
 ot/gromov.py | 26 +++-----------------------
 1 file changed, 3 insertions(+), 23 deletions(-)

(limited to 'ot/gromov.py')

diff --git a/ot/gromov.py b/ot/gromov.py
index 53349b7..ca96b31 100644
--- a/ot/gromov.py
+++ b/ot/gromov.py
@@ -17,7 +17,7 @@ import numpy as np
 
 
 from .bregman import sinkhorn
-from .utils import dist
+from .utils import dist, UndefinedParameter
 from .optim import cg
 
 
@@ -1011,9 +1011,6 @@ def fgw_barycenters(N, Ys, Cs, ps, lambdas, alpha, fixed_structure=False, fixed_
         International Conference on Machine Learning (ICML). 2019.
     """
 
-    class UndefinedParameter(Exception):
-        pass
-
     S = len(Cs)
     d = Ys[0].shape[1]  # dimension on the node features
     if p is None:
@@ -1049,10 +1046,7 @@ def fgw_barycenters(N, Ys, Cs, ps, lambdas, alpha, fixed_structure=False, fixed_
 
     T = [np.outer(p, q) for q in ps]
 
-    # X is N,d
-    # Ys is ns,d
-    Ms = [np.asarray(dist(X, Ys[s]), dtype=np.float64) for s in range(len(Ys))]
-    # Ms is N,ns
+    Ms = [np.asarray(dist(X, Ys[s]), dtype=np.float64) for s in range(len(Ys))]  # Ms is N,ns
 
     cpt = 0
     err_feature = 1
@@ -1072,27 +1066,13 @@ def fgw_barycenters(N, Ys, Cs, ps, lambdas, alpha, fixed_structure=False, fixed_
             Ys_temp = [y.T for y in Ys]
             X = update_feature_matrix(lambdas, Ys_temp, T, p).T
 
-        # X must be N,d
-        # Ys must be ns,d
         Ms = [np.asarray(dist(X, Ys[s]), dtype=np.float64) for s in range(len(Ys))]
 
         if not fixed_structure:
             if loss_fun == 'square_loss':
-                # T must be ns,N
-                # Cs must be ns,ns
-                # p must be N,1
                 T_temp = [t.T for t in T]
                 C = update_sructure_matrix(p, lambdas, T_temp, Cs)
 
-        # Ys must be d,ns
-        # Ts must be N,ns
-        # p must be N,1
-        # Ms is N,ns
-        # C is N,N
-        # Cs is ns,ns
-        # p is N,1
-        # ps is ns,1
-
         T = [fused_gromov_wasserstein((1 - alpha) * Ms[s], C, Cs[s], p, ps[s], loss_fun, alpha, numItermax=max_iter, stopThr=1e-5, verbose=verbose) for s in range(S)]
 
         # T is N,ns
@@ -1115,7 +1095,7 @@ def fgw_barycenters(N, Ys, Cs, ps, lambdas, alpha, fixed_structure=False, fixed_
     if log:
         log_['T'] = T  # from target to Ys
         log_['p'] = p
-        log_['Ms'] = Ms  # Ms are N,ns
+        log_['Ms'] = Ms
 
     if log:
         return X, C, log_
-- 
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