class_docstr: This implements the graph attention as in Watch Your Step: Learning Node Embeddings via Graph Attention
  https://arxiv.org/pdf/1710.09599.pdf.
  
  Args:
      walk_length (int): the length of the random walks. Equivalent to the number of adjacency powers used. Defaults
          to `10` as this value was found to perform well by the authors of the paper.
      attention_initializer (str or func, optional): The initialiser to use for the attention weights.
      attention_regularizer (str or func, optional): The regulariser to use for the attention weights.
      attention_constraint (str or func, optional): The constraint to use for the attention weights.
      input_dim (tuple of int, optional): The shape of the input to the layer.
class_docstr_tok: ["This","implements","the","graph","attention","as","in","Watch","Your","Step",":","Learning","Node","Embeddings","via","Graph","Attention","https",":","\/\/arxiv.org\/pdf\/1710.09599.pdf",".","Args",":","walk_length","(","int",")",":","the","length","of","the","random","walks",".","Equivalent","to","the","number","of","adjacency","powers","used",".","Defaults","to","`","10","`","as","this","value","was","found","to","perform","well","by","the","authors","of","the","paper",".","attention_initializer","(","str","or","func",",","optional",")",":","The","initialiser","to","use","for","the","attention","weights",".","attention_regularizer","(","str","or","func",",","optional",")",":","The","regulariser","to","use","for","the","attention","weights",".","attention_constraint","(","str","or","func",",","optional",")",":","The","constraint","to","use","for","the","attention","weights",".","input_dim","(","tuple","of","int",",","optional",")",":","The","shape","of","the","input","to","the","layer","."]
code: def build(self, input_shapes):
      self.attention_weights = self.add_weight(
          shape=(self.walk_length,),
          initializer=self.attention_initializer,
          name="attention_weights",
          regularizer=self.attention_regularizer,
          constraint=self.attention_constraint,
      )
  
      self.built = True
  
imports: import tensorflow
  from tensorflow.keras.layers import Layer, Embedding, Input, Lambda, Concatenate, Dense
  from tensorflow.keras import backend
  from tensorflow.keras import initializers, constraints, regularizers
  import numpy
  import warnings
  from ..mapper.adjacency_generators import AdjacencyPowerGenerator
  from ..core.validation import require_integer_in_range
  from .misc import deprecated_model_function
label_desc: Use image node_id 4 for calling the AttentiveWalk obj's underlying member method code with example usage: obj.build(input_shapes) without return types