diff --git a/mmcv/ops/csrc/pytorch/npu/roi_pool_npu.cpp b/mmcv/ops/csrc/pytorch/npu/roi_pool_npu.cpp
index c7a11e8c6d..b7015439b9 100644
--- a/mmcv/ops/csrc/pytorch/npu/roi_pool_npu.cpp
+++ b/mmcv/ops/csrc/pytorch/npu/roi_pool_npu.cpp
@@ -50,23 +50,29 @@ void roi_pool_backward_npu(Tensor grad_output, Tensor rois, Tensor argmax,
   int64_t pooled_height_64 = pooled_height;
   int64_t pooled_width_64 = pooled_width;
   int64_t pooled_channel = 1;
+  at::Tensor argmax_trans = argmax.transpose(1, 2).transpose(2, 3);
+  at::Tensor grad_output_trans = grad_output.transpose(1, 2).transpose(2, 3);
   at::Tensor roi_actual_num =
       at::empty_like(rois, rois.options().dtype(at::kInt));
-  at::Tensor x = at::ones_like(grad_input);
+  at::Tensor x = at::ones_like(grad_input).transpose(1, 2).transpose(2, 3);
+  at::Tensor y = at::zeros_like(x);
   OpCommand cmd;
   cmd.Name("RoiPoolingGradWithArgMax")
-      .Input(grad_output)
+      .Input(grad_output_trans)
       .Input(x)
       .Input(rois)
       .Input(roi_actual_num)
-      .Input(argmax)
-      .Output(grad_input)
+      .Input(argmax_trans)
+      .Output(y)
       .Attr("pooled_h", pooled_height_64)
       .Attr("pooled_w", pooled_width_64)
       .Attr("spatial_scale_h", spatial_scale)
       .Attr("spatial_scale_w", spatial_scale)
       .Attr("pool_channel", pooled_channel)
       .Run();
+  at::Tensor result = y.transpose(2, 3).transpose(1, 2);
+  at::Tensor res = result.contiguous();
+  grad_input.copy_(res);
 }
 
 void roi_pool_forward_impl(Tensor input, Tensor rois, Tensor output,