class_docstr: Transformer block for image-like data. First, project the input (aka embedding) and reshape to b, t, d. Then apply
  standard transformer action. Finally, reshape to image
class_docstr_tok: ["Transformer","block","for","image-like","data",".","First",",","project","the","input","(","aka","embedding",")","and","reshape","to","b",",","t",",","d.","Then","apply","standard","transformer","action",".","Finally",",","reshape","to","image"]
code: def set_weight(self, layer):
      self.norm = layer.norm
      self.proj_in = layer.proj_in
      self.transformer_blocks = layer.transformer_blocks
      self.proj_out = layer.proj_out
  
imports: import math
  from inspect import isfunction
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 3 for calling the SpatialTransformer obj's underlying member method code with example usage: obj.set_weight(layer) without return types