add double grad for expand (#27183) (#27236)

* add double grad for expand, test=develop

paddle/fluid/operators/expand_op.cc

@@ -228,6 +228,26 @@ class ExpandGradOpMaker : public framework::SingleGradOpMaker<T> {
   }
 };
 
+template <typename T>
+class ExpandDoubleGradOpMaker : public framework::SingleGradOpMaker<T> {
+ public:
+  using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
+
+ protected:
+  void Apply(GradOpPtr<T> op) const override {
+    op->SetInput("X", this->OutputGrad(framework::GradVarName("X")));
+    op->SetOutput("Out", this->InputGrad(framework::GradVarName("Out")));
+    if (this->HasInput("expand_times_tensor")) {
+      op->SetInput("expand_times_tensor", this->Input("expand_times_tensor"));
+    }
+    if (this->HasInput("ExpandTimes")) {
+      op->SetInput("ExpandTimes", this->Input("ExpandTimes"));
+    }
+    op->SetAttrMap(this->Attrs());
+    op->SetType("expand");
+  }
+};
+
 DECLARE_NO_NEED_BUFFER_VARS_INFERER(ExpandGradNoNeedBufVarsInferer, "X");
 
 }  // namespace operators
@@ -238,6 +258,8 @@ REGISTER_OPERATOR(expand, ops::ExpandOp, ops::ExpandOpMaker,
                   ops::ExpandGradOpMaker<paddle::framework::OpDesc>,
                   ops::ExpandGradOpMaker<paddle::imperative::OpBase>);
 REGISTER_OPERATOR(expand_grad, ops::ExpandGradOp,
+                  ops::ExpandDoubleGradOpMaker<paddle::framework::OpDesc>,
+                  ops::ExpandDoubleGradOpMaker<paddle::imperative::OpBase>,
                   ops::ExpandGradNoNeedBufVarsInferer);
 REGISTER_OP_CPU_KERNEL(
     expand, ops::ExpandKernel<paddle::platform::CPUDeviceContext, float>,

python/paddle/fluid/tests/unittests/test_nn_grad.py

@@ -153,6 +153,30 @@ class TestMulDoubleGradCheck(unittest.TestCase):
 
 
 class TestReshapeDoubleGradCheck(unittest.TestCase):
+    @prog_scope()
+    def func(self, place):
+        x_shape = [3, 12]
+        expand_times = [4, 9]
+        eps = 0.005
+        dtype = np.float64
+
+        x = layers.data('x', x_shape, False, dtype)
+        x.persistable = True
+        out = layers.expand(x, expand_times)
+        x_arr = np.random.uniform(-1, 1, x_shape).astype(dtype)
+
+        gradient_checker.double_grad_check(
+            [x], out, x_init=x_arr, place=place, eps=eps)
+
+    def test_grad(self):
+        places = [fluid.CPUPlace()]
+        if core.is_compiled_with_cuda():
+            places.append(fluid.CUDAPlace(0))
+        for p in places:
+            self.func(p)
+
+
+class TestExpandDoubleGradCheck(unittest.TestCase):
     @prog_scope()
     def func(self, place):
         x_shape = [3, 12]