在Numpy/PyTorch中生成一批随机旋转矩阵的最佳矢量化方法？

import numpy as np
from scipy.spatial.transform import Rotation as R

def generate_random_rotation_matrices(num_matrices, dtype=np.float32):
    # 生成随机旋转角度
    angles = np.random.rand(num_matrices, 3) * 2 * np.pi
    # 创建旋转对象
    rotations = R.from_euler('xyz', angles)
    # 转换为旋转矩阵
    rotation_matrices = rotations.as_matrix()
    return rotation_matrices.astype(dtype)

# 示例
num_matrices = 5
rotation_matrices = generate_random_rotation_matrices(num_matrices)
print(rotation_matrices)

import torch

def generate_random_rotation_matrices(num_matrices, dtype=torch.float32):
    # 生成随机旋转角度
    angles = torch.rand(num_matrices, 3, dtype=dtype) * 2 * np.pi
    # 使用torch.nn.functional.rotate生成旋转矩阵
    rotation_matrices = torch.zeros((num_matrices, 3, 3), dtype=dtype)
    cosines = torch.cos(angles)
    sines = torch.sin(angles)
    rotation_matrices[:, 0, 0] = cosines[:, 0]
    rotation_matrices[:, 0, 1] = -sines[:, 0]
    rotation_matrices[:, 1, 0] = sines[:, 0]
    rotation_matrices[:, 1, 1] = cosines[:, 0]
    rotation_matrices[:, 0, 2] = torch.randn(num_matrices, dtype=dtype)
    rotation_matrices[:, 1, 2] = torch.randn(num_matrices, dtype=dtype)
    rotation_matrices[:, 2, 0] = torch.randn(num_matrices, dtype=dtype)
    rotation_matrices[:, 2, 1] = torch.randn(num_matrices, dtype=dtype)
    rotation_matrices[:, 2, 2] = torch.ones(num_matrices, dtype=dtype)
    
    # 归一化最后一行和列
    rotation_matrices[:, 2] /= torch.norm(rotation_matrices[:, 2], dim=1, keepdim=True)
    rotation_matrices[:, :, 2] /= torch.norm(rotation_matrices[:, :, 2], dim=0, keepdim=True)
    
    return rotation_matrices

# 示例
num_matrices = 5
rotation_matrices = generate_random_rotation_matrices(num_matrices)
print(rotation_matrices)