diff --git i/lib/matplotlib/colors.py w/lib/matplotlib/colors.py
index 2f8c89265..598956d76 100644
--- i/lib/matplotlib/colors.py
+++ w/lib/matplotlib/colors.py
@@ -1213,8 +1213,14 @@ class SymLogNorm(Normalize):
         Normalize.__init__(self, vmin, vmax, clip)
         self.linthresh = float(linthresh)
         self._linscale_adj = (linscale / (1.0 - np.e ** -1))
-        if vmin is not None and vmax is not None:
-            self._transform_vmin_vmax()
+
+    @property
+    def _lower(self):
+        return self._transform(np.array(self.vmin, float))
+
+    @property
+    def _upper(self):
+        return self._transform(np.array(self.vmax, float))
 
     def __call__(self, value, clip=None):
         if clip is None:
@@ -1263,12 +1269,6 @@ class SymLogNorm(Normalize):
         a[~masked] /= self._linscale_adj
         return a
 
-    def _transform_vmin_vmax(self):
-        """Calculates vmin and vmax in the transformed system."""
-        vmin, vmax = self.vmin, self.vmax
-        arr = np.array([vmax, vmin]).astype(float)
-        self._upper, self._lower = self._transform(arr)
-
     def inverse(self, value):
         if not self.scaled():
             raise ValueError("Not invertible until scaled")
@@ -1276,16 +1276,6 @@ class SymLogNorm(Normalize):
         val = val * (self._upper - self._lower) + self._lower
         return self._inv_transform(val)
 
-    def autoscale(self, A):
-        # docstring inherited.
-        super().autoscale(A)
-        self._transform_vmin_vmax()
-
-    def autoscale_None(self, A):
-        # docstring inherited.
-        super().autoscale_None(A)
-        self._transform_vmin_vmax()
-
 
 class PowerNorm(Normalize):
     """