docs(cuda): correct our cuda chamfer dis speed

previously I first print time but the thing may didn't return back so print  loss to make sure we finished calculation.

Author: Kin-Zhang

assets/cuda/README.md

@@ -17,5 +17,5 @@ The number of points: (pc0: 88132, pc1: 88101)
 | Faiss | 817.698 |
 | CUDA([SCOOP](https://github.com/itailang/SCOOP/tree/master/auxiliary/ChamferDistancePytorch), Batch) | 83.275 |
 | Pytorch3D | 68.256 |
-| CUDA([SeFlow](https://github.com/KTH-RPL/SeFlow), SharedM) | **1.667** |
+| CUDA([SeFlow](https://github.com/KTH-RPL/SeFlow), SharedM) | **14.308** |
 | ~~mmcv~~(chamfer2D) | 651.510 |

assets/cuda/chamfer3D/README.md

@@ -44,7 +44,7 @@ The number of points: (pc0: 88132, pc1: 88101)
 | Faiss | 817.698 |
 | CUDA([SCOOP](https://github.com/itailang/SCOOP/tree/master/auxiliary/ChamferDistancePytorch), Batch) | 83.275 |
 | Pytorch3D | 68.256 |
-| CUDA([SeFlow](https://github.com/KTH-RPL/SeFlow), SharedM) | **1.667** |
+| CUDA([SeFlow](https://github.com/KTH-RPL/SeFlow), SharedM) | **14.308** |
 | ~~mmcv~~(chamfer2D) | 651.510 |
 
 对比命令行：

assets/tests/chamferdis_speed_test.py

@@ -3,12 +3,10 @@
 # Copyright (C) 2023-now, RPL, KTH Royal Institute of Technology
 # Author: Qingwen Zhang  (https://kin-zhang.github.io/)
 #
-# This work is licensed under the terms of the MIT license.
-# For a copy, see <https://opensource.org/licenses/MIT>.
-
+#
 # Description: Test which existing chamfer distance is faster.
 
-Dependence:
+Dependence for this test scripts:
     * faiss-gpu
     * Pytorch3d
     * mmcv
@@ -29,8 +27,8 @@
 CUDA_TEST = True
 
 if __name__ == "__main__":
-    pc0 = np.load('test_pc0.npy')
-    pc1 = np.load('test_pc1.npy')
+    pc0 = np.load(f'{BASEF_DIR}/assets/tests/test_pc0.npy')
+    pc1 = np.load(f'{BASEF_DIR}/assets/tests/test_pc1.npy')
     print('Start status on GPU allocation: {:.3f}MB'.format(torch.cuda.memory_allocated()/1024**2))
     pc0 = torch.from_numpy(pc0[...,:3]).float().cuda().contiguous()
     pc1 = torch.from_numpy(pc1[...,:3]).float().cuda().contiguous()
@@ -101,8 +99,8 @@ def faiss_knn(pc1, pc2):
         from assets.cuda.chamfer3D import nnChamferDis
         start_time = time.time()
         loss = nnChamferDis(truncate_dist=False)(pc0, pc1)
-        print(f"Chamfer Distance Cal time: {(time.time() - start_time)*1000:.3f} ms")
         print("loss: ", loss)
+        print(f"Chamfer Distance Cal time: {(time.time() - start_time)*1000:.3f} ms")
         print()
 
 """
@@ -124,7 +122,7 @@ def faiss_knn(pc1, pc2):
 mmcv Chamfer Distance Cal time: 651.510 ms
 
 ------ START CUDA Chamfer Distance Cal ------
-Chamfer Distance Cal time: 1.667 ms
+Chamfer Distance Cal time: 14.308 ms
 loss:  tensor(0.1710, device='cuda:0', grad_fn=<AddBackward0>)
 
 """