class_docstr: Mean Aggregator for GraphSAGE implemented with Keras base layer
  
  Args:
      output_dim (int): Output dimension
      bias (bool): Optional bias
      act (Callable or str): name of the activation function to use (must be a
          Keras activation function), or alternatively, a TensorFlow operation.
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docstr: Mean aggregator for tensors over the neighbourhood for each group.
  
  Args:
      x_group (tf.Tensor): : The input tensor representing the sampled neighbour nodes.
      group_idx (int, optional): Group index.
  
  Returns:
      :class:`tensorflow.Tensor`: A tensor aggregation of the input nodes features.
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code: def group_aggregate(self, x_group, group_idx=0):
      """
      Mean aggregator for tensors over the neighbourhood for each group.
  
      Args:
          x_group (tf.Tensor): : The input tensor representing the sampled neighbour nodes.
          group_idx (int, optional): Group index.
  
      Returns:
          :class:`tensorflow.Tensor`: A tensor aggregation of the input nodes features.
      """
      # The first group is assumed to be the self-tensor and we do not aggregate over it
      if group_idx == 0:
          x_agg = x_group
      else:
          x_agg = K.mean(x_group, axis=2)
  
      return K.dot(x_agg, self.w_group[group_idx])
  
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 1 for calling the MeanAggregator obj's underlying member method code with example usage: obj.group_aggregate(x_group, group_idx) and returns: K