[Cherry-Pick][BugFix]Fix reduce_mean/min/sum/prod, cumsum grad_op infershape bug (#46409)

* [BugFix]Fix reduce_mean/min/sum/prod, cumsum grad_op infershape bug

* fix typo

* fix typo

paddle/fluid/operators/cum_op.cc

@@ -72,13 +72,9 @@ class CumsumGradMaker : public framework::SingleGradOpMaker<T> {
     grad_op->SetType("cumsum");
     grad_op->SetInput("X", this->OutputGrad("Out"));
     grad_op->SetOutput("Out", this->InputGrad("X"));
-    grad_op->SetAttr("axis", PADDLE_GET_CONST(int, this->GetAttr("axis")));
-    grad_op->SetAttr("flatten",
-                     PADDLE_GET_CONST(bool, this->GetAttr("flatten")));
+    grad_op->SetAttrMap(this->Attrs());
     grad_op->SetAttr("reverse",
                      !PADDLE_GET_CONST(bool, this->GetAttr("reverse")));
-    grad_op->SetAttr("exclusive",
-                     PADDLE_GET_CONST(bool, this->GetAttr("exclusive")));
   }
 };
 

paddle/fluid/operators/reduce_ops/reduce_op.h

@@ -634,20 +634,26 @@ class ReduceGradOp : public framework::OperatorWithKernel {
                    "ReduceOp");
     auto x_dims = ctx->GetInputDim("X");
     auto x_rank = x_dims.size();
-    auto dims = ctx->Attrs().Get<std::vector<int>>("dim");
-    for (size_t i = 0; i < dims.size(); ++i) {
-      PADDLE_ENFORCE_LT(dims[i],
-                        x_rank,
-                        platform::errors::InvalidArgument(
-                            "The reduce dim index %d should be in the "
-                            "range [-dimension(X), dimension(X)], "
-                            "which dimesion = %d. But received dim index = %d.",
-                            i,
-                            x_rank,
-                            dims[i]));
-      if (dims[i] < 0) dims[i] = x_rank + dims[i];
+    // TODO(dev): We should delete Infershape and migrate it into
+    // UnchangeInferMeta.In case of 'dim' is Variable, it will
+    // not exist in Attrs but in Inputs.
+    if (ctx->HasAttr("dim")) {
+      auto dims = ctx->Attrs().Get<std::vector<int>>("dim");
+      for (size_t i = 0; i < dims.size(); ++i) {
+        PADDLE_ENFORCE_LT(
+            dims[i],
+            x_rank,
+            platform::errors::InvalidArgument(
+                "The reduce dim index %d should be in the "
+                "range [-dimension(X), dimension(X)], "
+                "which dimesion = %d. But received dim index = %d.",
+                i,
+                x_rank,
+                dims[i]));
+        if (dims[i] < 0) dims[i] = x_rank + dims[i];
+      }
     }
-    sort(dims.begin(), dims.end());
+
     auto x_grad_name = framework::GradVarName("X");
     if (ctx->HasOutput(x_grad_name)) {
       ctx->SetOutputDim(x_grad_name, x_dims);

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

@@ -356,6 +356,9 @@ class TestTensorAxis(unittest.TestCase):
             relu_out = paddle.nn.functional.relu(linear_out)
             axis = paddle.full([1], 2, dtype='int64')
             out = paddle.cumsum(relu_out, axis=axis)
+            loss = paddle.mean(out)
+            sgd = paddle.optimizer.SGD(learning_rate=0.)
+            sgd.minimize(paddle.mean(out))
 
             exe = paddle.static.Executor(self.place)
             exe.run(starup_prog)

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

@@ -543,6 +543,9 @@ class TestReduceOPTensorAxisBase(unittest.TestCase):
             linear = paddle.nn.Linear(x.shape[-1], 5)
             linear_out = linear(x)
             out = self.pd_api(linear_out, axis, keepdim=self.keepdim)
+
+            sgd = paddle.optimizer.SGD(learning_rate=0.)
+            sgd.minimize(paddle.mean(out))
             exe = paddle.static.Executor(self.place)
             exe.run(starup_prog)
             static_out = exe.run(feed={'x': self.x.numpy().astype('float32')},