code: def einsum_op_slice_1(q, k, v, slice_size):
      r = torch.zeros(
          q.shape[0],
          q.shape[1],
          v.shape[2],
          device=q.device,
          dtype=q.dtype,
      )
      for i in range(0, q.shape[1], slice_size):
          end = i + slice_size
          r[:, i:end] = einsum_op_compvis(q[:, i:end], k, v)
      return r
  
imports: from __future__ import annotations
  import math
  import psutil
  import platform
  import torch
  from torch import einsum
  from ldm.util import default
  from einops import rearrange
  from modules import shared, errors, devices, sub_quadratic_attention
  from modules.hypernetworks import hypernetwork
  import ldm.modules.attention
  import ldm.modules.diffusionmodules.model
  import sgm.modules.attention
  import sgm.modules.diffusionmodules.model
label_desc: Use image node_id 7 for calling a global function with example usage: einsum_op_slice_1(q, k, v, slice_size) and returns: r