[Numpy] Fix np.clip in scalar case

python/mxnet/numpy/multiarray.py

@@ -6200,6 +6200,11 @@ def clip(a, a_min, a_max, out=None):
     >>> np.clip(a, 3, 6, out=a)
     array([3., 3., 3., 3., 4., 5., 6., 6., 6., 6.], dtype=float32)
     """
+    from numbers import Number
+    if isinstance(a, Number):
+        # In case input is a scalar, the computation would fall back to native numpy.
+        # The value returned would be a python scalar.
+        return _np.clip(a, a_min, a_max, out=None)
     return _mx_nd_np.clip(a, a_min, a_max, out=out)
 
 

tests/python/unittest/test_numpy_op.py

@@ -3487,6 +3487,16 @@ def __init__(self, a_min=None, a_max=None):
 
         def hybrid_forward(self, F, x):
             return x.clip(self._a_min, self._a_max)
+
+    # Test scalar case
+    for _, a_min, a_max, throw_exception in workloads:
+        a = _np.random.uniform() # A scalar
+        if throw_exception:
+            # No need to test the exception case here.
+            continue
+        mx_ret = np.clip(a, a_min, a_max)
+        np_ret = _np.clip(a, a_min, a_max)
+        assert_almost_equal(mx_ret, np_ret, atol=1e-4, rtol=1e-3, use_broadcast=False)
 
     for shape, a_min, a_max, throw_exception in workloads:
         for dtype in dtypes: