1. pytorch3d

import pytorch3d
# 查看顶级模块
print(dir(pytorch3d))

[‘_C’, ‘builtins’, ‘cached’, ‘doc’, ‘file’, ‘loader’, ‘name’, ‘package’, ‘path’, ‘spec’, ‘version’, ‘common’, ‘loss’, ‘ops’, ‘renderer’, ‘structures’, ‘transforms’]

2. from pytorch3d import ops

from pytorch3d import ops
print(dir(ops))  # 查看 ops 模块下的所有函数/类

[‘GraphConv’, ‘SubdivideMeshes’, ‘all’, ‘builtins’, ‘cached’, ‘doc’, ‘file’, ‘loader’, ‘name’, ‘package’, ‘path’, ‘spec’, ‘add_pointclouds_to_volumes’, ‘add_points_features_to_volume_densities_features’, ‘ball_query’, ‘box3d_overlap’, ‘cameras_alignment’, ‘convert_pointclouds_to_tensor’, ‘corresponding_cameras_alignment’, ‘corresponding_points_alignment’, ‘cot_laplacian’, ‘cubify’, ‘efficient_pnp’, ‘estimate_pointcloud_local_coord_frames’, ‘estimate_pointcloud_normals’, ‘eyes’, ‘get_point_covariances’, ‘graph_conv’, ‘interp_face_attrs’, ‘interpolate_face_attributes’, ‘iou_box3d’, ‘is_pointclouds’, ‘iterative_closest_point’, ‘knn’, ‘knn_gather’, ‘knn_points’, ‘laplacian’, ‘laplacian_matrices’, ‘mesh_face_areas_normals’, ‘mesh_filtering’, ‘norm_laplacian’, ‘packed_to_padded’, ‘padded_to_packed’, ‘perspective_n_points’, ‘points_alignment’, ‘points_normals’, ‘points_to_volumes’, ‘sample_farthest_points’, ‘sample_points_from_meshes’, ‘subdivide_meshes’, ‘taubin_smoothing’, ‘utils’, ‘vert_align’, ‘wmean’]

3. from pytorch3d import loss

# 深入子模块
from pytorch3d import loss
print(dir(loss))  # 查看 ops 模块下的所有函数/类

[‘all’, ‘builtins’, ‘cached’, ‘doc’, ‘file’, ‘loader’, ‘name’, ‘package’, ‘path’, ‘spec’, ‘chamfer’, ‘chamfer_distance’, ‘mesh_edge_loss’, ‘mesh_laplacian_smoothing’, ‘mesh_normal_consistency’, ‘point_mesh_distance’, ‘point_mesh_edge_distance’, ‘point_mesh_face_distance’]