code: def so3_log_map(
      R: torch.Tensor, eps: float = 0.0001, cos_bound: float = 1e-4
  ) -> torch.Tensor:
      """
      Convert a batch of 3x3 rotation matrices `R`
      to a batch of 3-dimensional matrix logarithms of rotation matrices
      The conversion has a singularity around `(R=I)`.
  
      Args:
          R: batch of rotation matrices of shape `(minibatch, 3, 3)`.
          eps: (unused, for backward compatibility)
          cos_bound: (unused, for backward compatibility)
  
      Returns:
          Batch of logarithms of input rotation matrices
          of shape `(minibatch, 3)`.
      """
  
      N, dim1, dim2 = R.shape
      if dim1 != 3 or dim2 != 3:
          raise ValueError("Input has to be a batch of 3x3 Tensors.")
  
      return rotation_conversions.matrix_to_axis_angle(R)
  
file_path: pytorch3d/pytorch3d/transforms/so3.py
imports: import warnings
  from typing import Tuple
  import torch
  from pytorch3d.transforms import rotation_conversions
  from ..transforms import acos_linear_extrapolation
label_desc: Use image node_id 6 for calling a global function with example usage: so3_log_map(R, eps, cos_bound) and returns: rotation_conversions