[MRG] make alpha parameter in FGW diferentiable (#463)

* make alpha diferentiable

* update release file

* debug tensorflow to_numpy

1 files changed, 5 insertions, 1 deletions

diff --git a/ot/backend.py b/ot/backend.py
index 74f8366..0dd6fb8 100644
--- a/ot/backend.py
+++ b/ot/backend.py
@@ -1694,10 +1694,12 @@ class TorchBackend(Backend):
         self.ValFunction = ValFunction
 
     def _to_numpy(self, a):
+        if isinstance(a, float) or isinstance(a, int) or isinstance(a, np.ndarray):
+            return np.array(a)
         return a.cpu().detach().numpy()
 
     def _from_numpy(self, a, type_as=None):
-        if isinstance(a, float):
+        if isinstance(a, float) or isinstance(a, int):
             a = np.array(a)
         if type_as is None:
             return torch.from_numpy(a)
@@ -2501,6 +2503,8 @@ class TensorflowBackend(Backend):
             )
 
     def _to_numpy(self, a):
+        if isinstance(a, float) or isinstance(a, int) or isinstance(a, np.ndarray):
+            return np.array(a)
         return a.numpy()
 
     def _from_numpy(self, a, type_as=None):