diff --git a/brainunit/math/_compat_numpy_array_creation.py b/brainunit/math/_compat_numpy_array_creation.py
index 912a87d..1e31f4d 100644
--- a/brainunit/math/_compat_numpy_array_creation.py
+++ b/brainunit/math/_compat_numpy_array_creation.py
@@ -59,7 +59,7 @@ def full(
     Union[jax.Array, Quantity]: Quantity if `unit` is provided, else an array.
   '''
   if isinstance(fill_value, Quantity):
-    return jnp.full(shape, fill_value.magnitude, dtype=dtype) * fill_value.unit
+    return Quantity(jnp.full(shape, fill_value.value, dtype=dtype), dim=fill_value.dim)
   return jnp.full(shape, fill_value, dtype=dtype)
 
 
@@ -498,7 +498,7 @@ def asarray(
       # Convert the values to a jnp.ndarray and create a Quantity object
       return Quantity(jnp.asarray(values, dtype=dtype, order=order), dim=unit)
     else:
-      values = jax.tree.unflatten(tree, [x.value for x in a])
+      values = jax.tree.unflatten(tree, leaves)
       val = jnp.asarray(values, dtype=dtype, order=order)
       if unit is not None:
         assert isinstance(unit, Unit)
@@ -681,7 +681,8 @@ def logspace(start: Union[Quantity, bst.typing.ArrayLike],
 @set_module_as('brainunit.math')
 def fill_diagonal(a: Union[Quantity, bst.typing.ArrayLike],
                   val: Union[Quantity, bst.typing.ArrayLike],
-                  wrap: Optional[bool] = False) -> Union[Quantity, jax.Array]:
+                  wrap: Optional[bool] = False,
+                  inplace: Optional[bool] = False) -> Union[Quantity, jax.Array]:
   '''
   Fill the main diagonal of the given array of `a` with `val`.
 
@@ -697,14 +698,14 @@ def fill_diagonal(a: Union[Quantity, bst.typing.ArrayLike],
   if isinstance(val, Quantity):
     if isinstance(a, Quantity):
       fail_for_dimension_mismatch(a, val, error_message="Array and value have to have the same units.")
-      return Quantity(jnp.fill_diagonal(a.value, val.value, wrap), dim=a.dim)
+      return Quantity(jnp.fill_diagonal(a.value, val.value, wrap, inplace=inplace), dim=a.dim)
     else:
-      return Quantity(jnp.fill_diagonal(a, val.value, wrap), dim=val.dim)
+      return Quantity(jnp.fill_diagonal(a, val.value, wrap, inplace=inplace), dim=val.dim)
   else:
     if isinstance(a, Quantity):
-      return jnp.fill_diagonal(a.value, val, wrap)
+      return jnp.fill_diagonal(a.value, val, wrap, inplace=inplace)
     else:
-      return jnp.fill_diagonal(a, val, wrap)
+      return jnp.fill_diagonal(a, val, wrap, inplace=inplace)
 
 
 @set_module_as('brainunit.math')
diff --git a/brainunit/math/_compat_numpy_test.py b/brainunit/math/_compat_numpy_test.py
index 2f8de29..615d720 100644
--- a/brainunit/math/_compat_numpy_test.py
+++ b/brainunit/math/_compat_numpy_test.py
@@ -45,7 +45,7 @@ def test_full(self):
     self.assertEqual(result.shape, (3,))
     self.assertTrue(jnp.all(result == 4))
 
-    q = bu.math.full(3, 4, unit=second)
+    q = bu.math.full(3, 4 * second)
     self.assertEqual(q.shape, (3,))
     assert_quantity(q, result, second)
 
@@ -192,11 +192,11 @@ def test_logspace(self):
 
   def test_fill_diagonal(self):
     array = jnp.zeros((3, 3))
-    result = bu.math.fill_diagonal(array, 5, inplace=False)
+    result = bu.math.fill_diagonal(array, 5)
     self.assertTrue(jnp.all(result == jnp.array([[5, 0, 0], [0, 5, 0], [0, 0, 5]])))
 
     q = jnp.zeros((3, 3)) * bu.second
-    result_q = bu.math.fill_diagonal(q, 5 * bu.second, inplace=False)
+    result_q = bu.math.fill_diagonal(q, 5 * bu.second)
     assert_quantity(result_q, jnp.array([[5, 0, 0], [0, 5, 0], [0, 0, 5]]), bu.second)
 
   def test_array_split(self):