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: Builds the weight tensor(s) corresponding to the features of the input groups.
  
  Args:
      in_shape (list of int): Shape of input tensor for single group
      out_size (int): The size of the output vector for this group
      group_idx (int): The index of the input group
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code: def _build_group_weights(self, in_shape, out_size, group_idx=0):
      """
      Builds the weight tensor(s) corresponding to the features of the input groups.
  
      Args:
          in_shape (list of int): Shape of input tensor for single group
          out_size (int): The size of the output vector for this group
          group_idx (int): The index of the input group
  
      """
      weight = self.add_weight(
          shape=(int(in_shape[-1]), out_size),
          initializer=self.kernel_initializer,
          regularizer=self.kernel_regularizer,
          constraint=self.kernel_constraint,
          trainable=True,
          name=f"weight_g{group_idx}",
      )
      return weight
  
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 5 for calling the GraphSAGEAggregator obj's underlying member method code with example usage: obj._build_group_weights(in_shape, out_size, group_idx) and returns: weight