class_docstr: Base class for GraphSAGE aggregators
  
  Args:
      output_dim (int): Output dimension
      bias (bool): Optional flag indicating whether (True) or not (False; default)
          a bias term should be included.
      act (Callable or str): name of the activation function to use (must be a
          Keras activation function), or alternatively, a TensorFlow operation.
      kernel_initializer (str or func): The initialiser to use for the weights
      kernel_regularizer (str or func): The regulariser to use for the weights
      kernel_constraint (str or func): The constraint to use for the weights
      bias_initializer (str or func): The initialiser to use for the bias
      bias_regularizer (str or func): The regulariser to use for the bias
      bias_constraint (str or func): The constraint to use for the bias
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docstr: Override with a method to aggregate tensors over neighbourhood.
  
  Args:
      x_neigh: The input tensor representing the sampled neighbour nodes.
      group_idx: Optional neighbourhood index used for multi-dimensional hops.
  
  Returns:
      A tensor aggregation of the input nodes features.
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code: def aggregate_neighbours(self, x_neigh, group_idx: int = 0):
      """
      Override with a method to aggregate tensors over neighbourhood.
  
      Args:
          x_neigh: The input tensor representing the sampled neighbour nodes.
          group_idx: Optional neighbourhood index used for multi-dimensional hops.
  
      Returns:
          A tensor aggregation of the input nodes features.
      """
      raise NotImplementedError(
          "The GraphSAGEAggregator base class should not be directly instantiated"
      )
  
imports: import warnings
  import numpy
  from tensorflow.keras.layers import Layer
  from tensorflow.keras import Input
  from tensorflow.keras import backend
  from tensorflow.keras.layers import Lambda, Dropout, Reshape, LeakyReLU
  from tensorflow.keras.utils import Sequence
  from tensorflow.keras import activations, initializers, constraints, regularizers
  from typing import List, Tuple, Callable, AnyStr, Union
  from ..mapper import GraphSAGENodeGenerator, GraphSAGELinkGenerator, DirectedGraphSAGENodeGenerator, DirectedGraphSAGELinkGenerator, NodeSequence, LinkSequence
  from .misc import deprecated_model_function
  from ..connector.neo4j.mapper import Neo4jGraphSAGENodeGenerator, Neo4jDirectedGraphSAGENodeGenerator
label_desc: Use image node_id 6 for calling the GraphSAGEAggregator obj's underlying member method code with example usage: obj.aggregate_neighbours(x_neigh, group_idx) without return types