solving conflicts :/

1 files changed, 5 insertions, 38 deletions

diff --git a/ot/gromov.py b/ot/gromov.py
index 197e3ea..9dbf463 100644
--- a/ot/gromov.py
+++ b/ot/gromov.py
@@ -208,11 +208,7 @@ def update_kl_loss(p, lambdas, T, Cs):
     return(np.exp(np.divide(tmpsum, ppt)))

 

 

-<<<<<<< HEAD
 def gromov_wasserstein(C1, C2, p, q, loss_fun, epsilon, max_iter=1000, stopThr=1e-9, verbose=False, log=False):

-=======
-def gromov_wasserstein(C1, C2, p, q, loss_fun, epsilon, numItermax=1000, stopThr=1e-9, verbose=False, log=False):

->>>>>>> 986f46ddde3ce2f550cb56f66620df377326423d
     """

     Returns the gromov-wasserstein coupling between the two measured similarity matrices

 

@@ -252,11 +248,11 @@ def gromov_wasserstein(C1, C2, p, q, loss_fun, epsilon, numItermax=1000, stopThr
     loss_fun :  loss function used for the solver either 'square_loss' or 'kl_loss'

     epsilon : float

         Regularization term >0

-<<<<<<< HEAD
+<<<<<<< HEAD

     max_iter : int, optional

-=======
+=======

     numItermax : int, optional

->>>>>>> 986f46ddde3ce2f550cb56f66620df377326423d
+>>>>>>> 986f46ddde3ce2f550cb56f66620df377326423d

         Max number of iterations

     stopThr : float, optional

         Stop threshold on error (>0)

@@ -282,11 +278,7 @@ def gromov_wasserstein(C1, C2, p, q, loss_fun, epsilon, numItermax=1000, stopThr
     cpt = 0

     err = 1

 

-<<<<<<< HEAD
     while (err > stopThr and cpt < max_iter):

-=======
-    while (err > stopThr and cpt < numItermax):

->>>>>>> 986f46ddde3ce2f550cb56f66620df377326423d
 

         Tprev = T

 

@@ -319,11 +311,7 @@ def gromov_wasserstein(C1, C2, p, q, loss_fun, epsilon, numItermax=1000, stopThr
         return T

 

 

-<<<<<<< HEAD
 def gromov_wasserstein2(C1, C2, p, q, loss_fun, epsilon, max_iter=1000, stopThr=1e-9, verbose=False, log=False):

-=======
-def gromov_wasserstein2(C1, C2, p, q, loss_fun, epsilon, numItermax=1000, stopThr=1e-9, verbose=False, log=False):

->>>>>>> 986f46ddde3ce2f550cb56f66620df377326423d
     """

     Returns the gromov-wasserstein discrepancy between the two measured similarity matrices

 

@@ -358,7 +346,7 @@ def gromov_wasserstein2(C1, C2, p, q, loss_fun, epsilon, numItermax=1000, stopTh
     loss_fun :  loss function used for the solver either 'square_loss' or 'kl_loss'

     epsilon : float

         Regularization term >0

-    numItermax : int, optional

+    max_iter : int, optional

         Max number of iterations

     stopThr : float, optional

         Stop threshold on error (>0)

@@ -378,17 +366,10 @@ def gromov_wasserstein2(C1, C2, p, q, loss_fun, epsilon, numItermax=1000, stopTh
 

     if log:

         gw, logv = gromov_wasserstein(

-<<<<<<< HEAD
             C1, C2, p, q, loss_fun, epsilon, max_iter, stopThr, verbose, log)

     else:

         gw = gromov_wasserstein(C1, C2, p, q, loss_fun,

                                 epsilon, max_iter, stopThr, verbose, log)

-=======
-            C1, C2, p, q, loss_fun, epsilon, numItermax, stopThr, verbose, log)

-    else:

-        gw = gromov_wasserstein(C1, C2, p, q, loss_fun,

-                                epsilon, numItermax, stopThr, verbose, log)

->>>>>>> 986f46ddde3ce2f550cb56f66620df377326423d
 

     if loss_fun == 'square_loss':

         gw_dist = np.sum(gw * tensor_square_loss(C1, C2, gw))

@@ -402,11 +383,7 @@ def gromov_wasserstein2(C1, C2, p, q, loss_fun, epsilon, numItermax=1000, stopTh
         return gw_dist

 

 

-<<<<<<< HEAD
 def gromov_barycenters(N, Cs, ps, p, lambdas, loss_fun, epsilon, max_iter=1000, stopThr=1e-9, verbose=False, log=False):

-=======
-def gromov_barycenters(N, Cs, ps, p, lambdas, loss_fun, epsilon, numItermax=1000, stopThr=1e-9, verbose=False, log=False):

->>>>>>> 986f46ddde3ce2f550cb56f66620df377326423d
     """

     Returns the gromov-wasserstein barycenters of S measured similarity matrices

 

@@ -439,7 +416,7 @@ def gromov_barycenters(N, Cs, ps, p, lambdas, loss_fun, epsilon, numItermax=1000
              with the S Ts couplings calculated at each iteration

     epsilon : float

         Regularization term >0

-    numItermax : int, optional

+    max_iter : int, optional

         Max number of iterations

     stopThr : float, optional

         Stop threshol on error (>0)

@@ -469,21 +446,11 @@ def gromov_barycenters(N, Cs, ps, p, lambdas, loss_fun, epsilon, numItermax=1000
 

     error = []

 

-<<<<<<< HEAD
     while(err > stopThr and cpt < max_iter):

-=======
-    while(err > stopThr and cpt < numItermax):

->>>>>>> 986f46ddde3ce2f550cb56f66620df377326423d
-

         Cprev = C

 

         T = [gromov_wasserstein(Cs[s], C, ps[s], p, loss_fun, epsilon,

-<<<<<<< HEAD
                                 max_iter, 1e-5, verbose, log) for s in range(S)]

-=======
-                                numItermax, 1e-5, verbose, log) for s in range(S)]

->>>>>>> 986f46ddde3ce2f550cb56f66620df377326423d
-

         if loss_fun == 'square_loss':

             C = update_square_loss(p, lambdas, T, Cs)