code: def multi_view_union(self, tensor_dict, B, N_view):
      for t_name, t in tensor_dict.items():
          t = t.reshape(B, N_view, *t.shape[1:])
          tensor_dict[t_name] = t.reshape(
              B, N_view * t.shape[2], *t.shape[3:]
          )
      return tensor_dict
  
imports: import torch
  import torch.nn
  import torchvision
  import numpy
  import torch
  from torch.nn.functional import silu
  from einops import rearrange, repeat
  from utils.general_utils import matrix_to_quaternion, quaternion_raw_multiply
  from utils.graphics_utils import fov2focal
label_desc: Use image node_id 7 for calling the GaussianSplatPredictor obj's underlying member method code with example usage: obj.multi_view_union(tensor_dict, B, N_view) and returns: tensor_dict