code: def _batched_dotprod(x: torch.Tensor, y: torch.Tensor):
      """
      Takes two tensors of shape (N,3) and returns their batched
      dot product along the last dimension as a tensor of shape
      (N,).
      """
      return torch.einsum("ij,ij->i", x, y)
  
file_path: pytorch3d/tests/test_camera_utils.py
imports: import unittest
  from math import radians
  import torch
  from pytorch3d.renderer.camera_utils import camera_to_eye_at_up, rotate_on_spot
  from pytorch3d.renderer.cameras import get_world_to_view_transform, look_at_view_transform, PerspectiveCameras
  from pytorch3d.transforms import axis_angle_to_matrix
  from torch.nn.functional import normalize
  from .common_testing import TestCaseMixin
label_desc: Use image node_id 1 for calling a global function with example usage: _batched_dotprod(x, y) and returns: torch