class_docstr: Tests of GraphAttentionSparse layer
class_docstr_tok: ["Tests","of","GraphAttentionSparse","layer"]
code: def get_inputs(self):
      x_inp = [
          Input(batch_shape=(1, self.N, self.F_in)),
          Input(batch_shape=(1, None, 2), dtype="int64"),
          Input(batch_shape=(1, None), dtype="float32"),
      ]
  
      A_mat = SqueezedSparseConversion(shape=(self.N, self.N))(
          x_inp[1:]
      )
  
      # For dense matrix, remove batch dimension
      layer_inp = x_inp[:1] + [A_mat]
  
      return x_inp, layer_inp
  
imports: import pytest
  import scipy.sparse
  import tensorflow
  from tensorflow import keras
  from tensorflow.keras import backend
  from tensorflow.keras.layers import Input
  from stellargraph.mapper import FullBatchNodeGenerator, FullBatchLinkGenerator, GraphSAGENodeGenerator
  from stellargraph.layer import *
  from ..test_utils.graphs import example_graph
  from ..None import test_utils
label_desc: Use image node_id 1 for calling the Test_GraphAttentionSparse obj's underlying member method code with example usage: obj.get_inputs() and returns: x_inp,  layer_inp