class_docstr: Tests of GAT class
class_docstr_tok: ["Tests","of","GAT","class"]
code: def test_kernel_and_bias_defaults(self):
      graph = example_graph(feature_size=self.F_in)
      gen = FullBatchNodeGenerator(
          graph, sparse=self.sparse, method=self.method
      )
      gat = GAT(
          layer_sizes=self.layer_sizes,
          activations=self.activations,
          attn_heads=self.attn_heads,
          generator=gen,
      )
      for layer in gat._layers:
          if isinstance(layer, GraphAttention):
              assert isinstance(
                  layer.kernel_initializer,
                  tf.initializers.GlorotUniform,
              )
              assert isinstance(
                  layer.bias_initializer, tf.initializers.Zeros
              )
              assert isinstance(
                  layer.attn_kernel_initializer,
                  tf.initializers.GlorotUniform,
              )
              assert layer.kernel_regularizer is None
              assert layer.bias_regularizer is None
              assert layer.attn_kernel_regularizer is None
              assert layer.kernel_constraint is None
              assert layer.bias_constraint is None
              assert layer.attn_kernel_constraint is None
  
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 10 for calling the Test_GAT obj's underlying member method code with example usage: obj.test_kernel_and_bias_defaults() without return types