fix lint

momo609 · Apr 23, 2024 · f8b17a5 · f8b17a5
1 parent 1fc2c2d
commit f8b17a5
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Showing 5 changed files with 39 additions and 29 deletions.
diff --git a/mmcv/ops/csrc/pytorch/npu/furthest_point_sample_npu.cpp b/mmcv/ops/csrc/pytorch/npu/furthest_point_sample_npu.cpp
@@ -6,15 +6,17 @@ using namespace std;
 void furthest_point_sampling_forward_npu(Tensor points_tensor,
                                          Tensor temp_tensor, Tensor idx_tensor,
                                          int b, int n, int m) {
-  TORCH_CHECK((points_tensor.sizes()[1] >= m),
-              "the num of sampled points should smaller than total num of points.");
+  TORCH_CHECK(
+      (points_tensor.sizes()[1] >= m),
+      "the num of sampled points should smaller than total num of points.");
   at::Tensor points_xyz = points_tensor.transpose(1, 2).contiguous();
   at::Tensor nearest_dist = temp_tensor.contiguous();
   EXEC_NPU_CMD(aclnnFurthestPointSampling, points_xyz, nearest_dist, m,
                idx_tensor);
 }
 
-void furthest_point_sampling_forward_impl(Tensor points_tensor, Tensor temp_tensor, Tensor idx_tensor,
+void furthest_point_sampling_forward_impl(Tensor points_tensor,
+                                          Tensor temp_tensor, Tensor idx_tensor,
                                           int b, int n, int m);
 
 REGISTER_NPU_IMPL(furthest_point_sampling_forward_impl,

diff --git a/mmcv/ops/csrc/pytorch/npu/furthest_point_sampling_with_dist_npu.cpp b/mmcv/ops/csrc/pytorch/npu/furthest_point_sampling_with_dist_npu.cpp
@@ -4,18 +4,19 @@ using namespace std;
 
 void furthest_point_sampling_with_dist_npu(Tensor points_tensor,
                                            Tensor temp_tensor,
-                                           Tensor idx_tensor, int b,
-                                           int n, int m) {
+                                           Tensor idx_tensor, int b, int n,
+                                           int m) {
   auto output_size = {b, m};
   at::Tensor result =
       at::empty(output_size, points_tensor.options().dtype(at::kInt));
-  EXEC_NPU_CMD(aclnnFurthestPointSamplingWithDist, points_tensor, temp_tensor, m, result);
+  EXEC_NPU_CMD(aclnnFurthestPointSamplingWithDist, points_tensor, temp_tensor,
+               m, result);
 }
 
 void  furthest_point_sampling_with_dist_forward_impl(Tensor points_tensor,
-                                                    Tensor temp_tensor,
-                                                    Tensor idx_tensor, int b, int n,
-                                                    int m);
+                                                     Tensor temp_tensor,
+                                                     Tensor idx_tensor, int b,
+                                                     int n, int m);
 
 REGISTER_NPU_IMPL(furthest_point_sampling_with_dist_forward_impl,
                   furthest_point_sampling_with_dist_npu);
diff --git a/mmcv/ops/csrc/pytorch/npu/ms_deform_attn_npu.cpp b/mmcv/ops/csrc/pytorch/npu/ms_deform_attn_npu.cpp
@@ -3,12 +3,13 @@
 using namespace NPU_NAME_SPACE;
 using namespace std;
 
-Tensor ms_deform_attn_impl_forward(const Tensor &value,
-                                   const Tensor &value_spatial_shapes,
-                                   const Tensor &value_level_start_index,
-                                   const Tensor &sampling_locations,
-                                   const Tensor &attention_weights,
-                                   const int im2col_step);
+Tensor ms_deform_attn_impl_forward(
+    const Tensor &value,
+    const Tensor &value_spatial_shapes,
+    const Tensor &value_level_start_index,
+    const Tensor &sampling_locations,
+    const Tensor &attention_weights,
+    const int im2col_step);
 
 void check_support(const Tensor &value, const Tensor &attention_weights) {
   TORCH_CHECK(
@@ -25,12 +26,13 @@ void check_support(const Tensor &value, const Tensor &attention_weights) {
               "num_points should be in the range of [4, 8]");
 }
 
-Tensor ms_deform_attn_forward_npu(const Tensor &value,
-                                  const Tensor &value_spatial_shapes,
-                                  const Tensor &value_level_start_index,
-                                  const Tensor &sampling_locations,
-                                  const Tensor &attention_weights,
-                                  const int im2col_step) {
+Tensor ms_deform_attn_forward_npu(
+    const Tensor &value,
+    const Tensor &value_spatial_shapes,
+    const Tensor &value_level_start_index,
+    const Tensor &sampling_locations,
+    const Tensor &attention_weights,
+    const int im2col_step) {
   check_support(value, attention_weights);
   at::Tensor value_fp32 = value;
   at::Tensor value_spatial_shapes_int32 = value_spatial_shapes;
@@ -87,9 +89,11 @@ void ms_deform_attn_backward_npu(const Tensor &value, const Tensor &spatial_shap
                                  const Tensor &level_start_index,
                                  const Tensor &sampling_loc,
                                  const Tensor &attn_weight,
-                                 const Tensor &grad_output, Tensor &grad_value,
+                                 const Tensor &grad_output,
+                                 Tensor &grad_value,
                                  Tensor &grad_sampling_loc,
-                                 Tensor &grad_attn_weight, const int im2col_step) {
+                                 Tensor &grad_attn_weight,
+                                 const int im2col_step) {
   check_support(value, attn_weight);
   at::Tensor value_fp32 = value;
   at::Tensor spatial_shapes_int32 = spatial_shapes;

diff --git a/mmcv/ops/csrc/pytorch/npu/nms3d_normal_npu.cpp b/mmcv/ops/csrc/pytorch/npu/nms3d_normal_npu.cpp
@@ -3,19 +3,22 @@
 using namespace NPU_NAME_SPACE;
 
 void iou3d_nms3d_normal_forward_npu(const Tensor boxes, Tensor &keep,
-                                    Tensor &keep_num, float nms_overlap_thresh) {
+                                    Tensor &keep_num,
+                                    float nms_overlap_thresh) {
   int32_t box_num = boxes.size(0);
   int32_t data_align = 16;
   int32_t mask_num = ((box_num - 1) / data_align + 1) * data_align;
-  at::Tensor mask = at::empty({ box_num, mask_num }, boxes.options().dtype(at::kShort));
+  at::Tensor mask =
+      at::empty({ box_num, mask_num }, boxes.options().dtype(at::kShort));
   EXEC_NPU_CMD(aclnnNms3dNormal, boxes, nms_overlap_thresh, mask);
 
-  keep = at::zeros({ box_num }, mask.options());
+  keep = at::zeros({box_num}, mask.options());
   keep_num = at::zeros(1, mask.options());
   EXEC_NPU_CMD(aclnnGatherNms3dMask, mask, keep, keep_num);
 }
 
 void iou3d_nms3d_normal_forward_impl(const Tensor boxes, Tensor &keep,
-                                     Tensor &keep_num, float nms_overlap_thresh);
+                                     Tensor &keep_num,
+                                     float nms_overlap_thresh);
 
 REGISTER_NPU_IMPL(iou3d_nms3d_normal_forward_impl, iou3d_nms3d_normal_forward_npu);
diff --git a/mmcv/ops/csrc/pytorch/npu/nms3d_npu.cpp b/mmcv/ops/csrc/pytorch/npu/nms3d_npu.cpp
@@ -5,8 +5,8 @@ using namespace std;
 
 constexpr int32_t BOX_DIM = 7;
 
-void iou3d_nms3d_forward_npu(const Tensor boxes, Tensor &keep,
-                             Tensor &keep_num, float nms_overlap_thresh)
+void iou3d_nms3d_forward_npu(const Tensor boxes, Tensor &keep, Tensor &keep_num,
+                             float nms_overlap_thresh) {
 {
   TORCH_CHECK((boxes.sizes()[1] == BOX_DIM),
               "Input boxes shape should be (N, 7)");