import unif and dist in bregman file

Author: Kilian Fatras

ot/bregman.py

@@ -10,6 +10,7 @@
 # License: MIT License
 
 import numpy as np
+from .utils import unif, dist
 
 
 def sinkhorn(a, b, M, reg, method='sinkhorn', numItermax=1000,
@@ -1375,11 +1376,11 @@ def empirical_sinkhorn(X_s, X_t, reg, a=None, b=None, metric='sqeuclidean', numI
     '''
 
     if a is None:
-        a = ot.unif(np.shape(X_s)[0])
+        a = unif(np.shape(X_s)[0])
     if b is None:
-        b = ot.unif(np.shape(X_t)[0])
+        b = unif(np.shape(X_t)[0])
 
-    M = ot.dist(X_s, X_t, metric=metric)
+    M = dist(X_s, X_t, metric=metric)
 
     if log:
         pi, log = sinkhorn(a, b, M, reg, numItermax=numIterMax, stopThr=stopThr, verbose=verbose, log=True, **kwargs)
@@ -1465,11 +1466,11 @@ def empirical_sinkhorn2(X_s, X_t, reg, a=None, b=None, metric='sqeuclidean', num
     '''
 
     if a is None:
-        a = ot.unif(np.shape(X_s)[0])
+        a = unif(np.shape(X_s)[0])
     if b is None:
-        b = ot.unif(np.shape(X_t)[0])
+        b = unif(np.shape(X_t)[0])
 
-    M = ot.dist(X_s, X_t, metric=metric)
+    M = dist(X_s, X_t, metric=metric)
 
     if log:
         sinkhorn_loss, log = sinkhorn2(a, b, M, reg, numItermax=numIterMax, stopThr=stopThr, verbose=verbose, log=log, **kwargs)