Addresses Daniel's comments

Author: PTNobel

cvxpy/atoms/affine/hstack.py

@@ -116,6 +116,7 @@ def _verify_hess_vec_args(self):
 
     def _hess_vec(self, vec):
         result = {}
+        keys_require_summing = []
 
         flat_offset = 0
         for arg in self.args:
@@ -131,12 +132,13 @@ def _hess_vec(self, vec):
                         np.concatenate([old_cols, new_cols]),
                         np.concatenate([old_vals, new_vals]),
                     )
+                    keys_require_summing.append(k)
                 else:
                     result[k] = v
 
             flat_offset += arg.size
 
-        for k in result:
+        for k in set(keys_require_summing):
             rows, cols, vals = result[k]
             var1, var2 = k
             hess = coo_matrix((vals, (rows, cols)), shape=(var1.size, var2.size))

cvxpy/atoms/affine/vstack.py

@@ -113,6 +113,7 @@ def _verify_hess_vec_args(self):
     def _hess_vec(self, vec):
         M = self.shape[0]
         result = {}
+        keys_require_summing = []
 
         row_offset = 0
         for arg in self.args:
@@ -132,12 +133,13 @@ def _hess_vec(self, vec):
                         np.concatenate([old_cols, new_cols]),
                         np.concatenate([old_vals, new_vals]),
                     )
+                    keys_require_summing.append(k)
                 else:
                     result[k] = v
 
             row_offset += m_j
 
-        for k in result:
+        for k in set(keys_require_summing):
             rows, cols, vals = result[k]
             var1, var2 = k
             hess = coo_matrix((vals, (rows, cols)), shape=(var1.size, var2.size))

cvxpy/reductions/dnlp2smooth/canonicalizers/prod_canon.py

@@ -26,6 +26,9 @@ def prod_canon(expr, args):
     Since prod is a smooth function with implemented gradients,
     we simply ensure the argument is a Variable.
     """
+    if isinstance(args[0], Variable):
+        return expr.copy([args[0]]), []
+
     t = Variable(args[0].shape)
 
     if args[0].value is not None: