Use new interval() of categorical

Why:

Categorical used to return the categories even when there was a one-hot
encoding of it. Since PR Epistimio/orion#447,
the one-hot transformer now returns the proper interval in (0, 1) in
vector of the size equal to number of dimensions.

src/orion/algo/skopt/bayes.py

@@ -24,21 +24,17 @@ def orion_space_to_skopt_space(orion_space):
     """Convert Oríon's definition of problem's domain to a skopt compatible."""
     dimensions = []
     for key, dimension in orion_space.items():
-        #  low = dimension._args[0]
-        #  high = low + dimension._args[1]
         low, high = dimension.interval()
-        # NOTE: A hack, because orion priors have non-inclusive higher bound
-        #       while scikit-optimizer have inclusive ones.
-        # pylint: disable = assignment-from-no-return
-        high = numpy.nextafter(high, high - 1)
         shape = dimension.shape
         assert not shape or len(shape) == 1
         if not shape:
             shape = (1,)
+            low = (low,)
+            high = (high,)
         # Unpack dimension
         for i in range(shape[0]):
             dimensions.append(
-                Real(name=key + "_" + str(i), prior="uniform", low=low, high=high)
+                Real(name=key + "_" + str(i), prior="uniform", low=low[i], high=high[i])
             )
 
     return Space(dimensions)