[NPU] Refine variable name (#34330)

* fix variable name

* fix variable name

paddle/fluid/operators/matmul_op_npu.cc

@@ -140,20 +140,22 @@ class MatMulGradNPUKernel : public framework::OpKernel<T> {
           dy->mutable_data<T>(ctx.GetPlace());
           if ((x->dims().size() == 3) && (dout->dims().size() == 3) &&
               (dy->dims().size() == 2)) {
-            framework::Tensor dout_;
-            dout_.ShareDataWith(*dout);
-            std::vector<int> vec_dim = framework::vectorize<int>(dout_.dims());
+            framework::Tensor dout_tmp;
+            dout_tmp.ShareDataWith(*dout);
+            std::vector<int> vec_dim =
+                framework::vectorize<int>(dout_tmp.dims());
             std::vector<int> vec_dim_v{vec_dim[0] * vec_dim[1], vec_dim[2]};
-            dout_.Resize(framework::make_ddim(vec_dim_v));
+            dout_tmp.Resize(framework::make_ddim(vec_dim_v));
 
-            framework::Tensor x_;
-            x_.ShareDataWith(*x);
-            std::vector<int> vec_dim_x = framework::vectorize<int>(x_.dims());
+            framework::Tensor x_tmp;
+            x_tmp.ShareDataWith(*x);
+            std::vector<int> vec_dim_x =
+                framework::vectorize<int>(x_tmp.dims());
             std::vector<int> vec_dim_x_v{vec_dim_x[0] * vec_dim_x[1],
                                          vec_dim_x[2]};
-            x_.Resize(framework::make_ddim(vec_dim_x_v));
+            x_tmp.Resize(framework::make_ddim(vec_dim_x_v));
             const auto& runner_dy =
-                NpuOpRunner("MatMul", {x_, dout_}, {*dy},
+                NpuOpRunner("MatMul", {x_tmp, dout_tmp}, {*dy},
                             {{"transpose_x1", true}, {"transpose_x2", false}});
             runner_dy.Run(stream);
           } else {

paddle/fluid/operators/matmul_v2_op_npu.cc

@@ -140,20 +140,22 @@ class MatMulV2GradNPUKernel : public framework::OpKernel<T> {
           dy->mutable_data<T>(ctx.GetPlace());
           if ((x->dims().size() == 3) && (dout->dims().size() == 3) &&
               (dy->dims().size() == 2)) {
-            framework::Tensor dout_;
-            dout_.ShareDataWith(*dout);
-            std::vector<int> vec_dim = framework::vectorize<int>(dout_.dims());
+            framework::Tensor dout_tmp;
+            dout_tmp.ShareDataWith(*dout);
+            std::vector<int> vec_dim =
+                framework::vectorize<int>(dout_tmp.dims());
             std::vector<int> vec_dim_v{vec_dim[0] * vec_dim[1], vec_dim[2]};
-            dout_.Resize(framework::make_ddim(vec_dim_v));
+            dout_tmp.Resize(framework::make_ddim(vec_dim_v));
 
-            framework::Tensor x_;
-            x_.ShareDataWith(*x);
-            std::vector<int> vec_dim_x = framework::vectorize<int>(x_.dims());
+            framework::Tensor x_tmp;
+            x_tmp.ShareDataWith(*x);
+            std::vector<int> vec_dim_x =
+                framework::vectorize<int>(x_tmp.dims());
             std::vector<int> vec_dim_x_v{vec_dim_x[0] * vec_dim_x[1],
                                          vec_dim_x[2]};
-            x_.Resize(framework::make_ddim(vec_dim_x_v));
+            x_tmp.Resize(framework::make_ddim(vec_dim_x_v));
             const auto& runner_dy =
-                NpuOpRunner("MatMul", {x_, dout_}, {*dy},
+                NpuOpRunner("MatMul", {x_tmp, dout_tmp}, {*dy},
                             {{"transpose_x1", true}, {"transpose_x2", false}});
             runner_dy.Run(stream);
           } else {