class_docstr: Uses xformers efficient implementation,
  see https://github.com/MatthieuTPHR/diffusers/blob/d80b531ff8060ec1ea982b65a1b8df70f73aa67c/src/diffusers/models/attention.py#L223
  Note: this is a single-head self-attention operation
class_docstr_tok: ["Uses","xformers","efficient","implementation",",","see","https",":","\/\/github.com\/MatthieuTPHR\/diffusers\/blob\/d80b531ff8060ec1ea982b65a1b8df70f73aa67c\/src\/diffusers\/models\/attention.py","#","L223","Note",":","this","is","a","single-head","self-attention","operation"]
code: def forward(self, x, **kwargs):
      h_ = x
      h_ = self.attention(h_)
      h_ = self.proj_out(h_)
      return x + h_
  
imports: import logging
  import math
  from typing import Any, Callable, Optional
  import numpy
  import torch
  import torch.nn
  from einops import rearrange
  from packaging import version
  from ...modules.attention import LinearAttention, MemoryEfficientCrossAttention
label_desc: Use image node_id 3 for calling the MemoryEfficientAttnBlock obj's underlying member method code with example usage: obj.forward(x) and returns: unknown