Add type hints in mmcv/ops/points_sampler.py (#2015)

* add typehint in mmcv/ops/points_sampler.py

* Update mmcv/ops/points_sampler.py
Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

* Update mmcv/ops/points_sampler.py
Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>
Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

mmcv/ops/points_sampler.py

 from typing import List
 
 import torch
+from torch import Tensor
 from torch import nn as nn
 
 from mmcv.runner import force_fp32
@@ -8,7 +9,9 @@ from .furthest_point_sample import (furthest_point_sample,
                                     furthest_point_sample_with_dist)
 
 
-def calc_square_dist(point_feat_a, point_feat_b, norm=True):
+def calc_square_dist(point_feat_a: Tensor,
+                     point_feat_b: Tensor,
+                     norm: bool = True) -> Tensor:
     """Calculating square distance between a and b.
 
     Args:
@@ -34,7 +37,7 @@ def calc_square_dist(point_feat_a, point_feat_b, norm=True):
     return dist
 
 
-def get_sampler_cls(sampler_type):
+def get_sampler_cls(sampler_type: str) -> nn.Module:
     """Get the type and mode of points sampler.
 
     Args:
@@ -74,7 +77,7 @@ class PointsSampler(nn.Module):
     def __init__(self,
                  num_point: List[int],
                  fps_mod_list: List[str] = ['D-FPS'],
-                 fps_sample_range_list: List[int] = [-1]):
+                 fps_sample_range_list: List[int] = [-1]) -> None:
         super().__init__()
         # FPS would be applied to different fps_mod in the list,
         # so the length of the num_point should be equal to
@@ -89,7 +92,7 @@ class PointsSampler(nn.Module):
         self.fp16_enabled = False
 
     @force_fp32()
-    def forward(self, points_xyz, features):
+    def forward(self, points_xyz: Tensor, features: Tensor) -> Tensor:
         """
         Args:
             points_xyz (torch.Tensor): (B, N, 3) xyz coordinates of
@@ -134,10 +137,10 @@ class PointsSampler(nn.Module):
 class DFPSSampler(nn.Module):
     """Using Euclidean distances of points for FPS."""
 
-    def __init__(self):
+    def __init__(self) -> None:
         super().__init__()
 
-    def forward(self, points, features, npoint):
+    def forward(self, points: Tensor, features: Tensor, npoint: int) -> Tensor:
         """Sampling points with D-FPS."""
         fps_idx = furthest_point_sample(points.contiguous(), npoint)
         return fps_idx
@@ -146,10 +149,10 @@ class DFPSSampler(nn.Module):
 class FFPSSampler(nn.Module):
     """Using feature distances for FPS."""
 
-    def __init__(self):
+    def __init__(self) -> None:
         super().__init__()
 
-    def forward(self, points, features, npoint):
+    def forward(self, points: Tensor, features: Tensor, npoint: int) -> Tensor:
         """Sampling points with F-FPS."""
         assert features is not None, \
             'feature input to FFPS_Sampler should not be None'
@@ -163,10 +166,10 @@ class FFPSSampler(nn.Module):
 class FSSampler(nn.Module):
     """Using F-FPS and D-FPS simultaneously."""
 
-    def __init__(self):
+    def __init__(self) -> None:
         super().__init__()
 
-    def forward(self, points, features, npoint):
+    def forward(self, points: Tensor, features: Tensor, npoint: int) -> Tensor:
         """Sampling points with FS_Sampling."""
         assert features is not None, \
             'feature input to FS_Sampler should not be None'