code: def _AXWb(A, X, W, b):
      X = tf.matmul(X, W)
      Y = tf.reshape(
          tf.matmul(A, tf.reshape(X, (X.shape[0], -1))), X.shape
      )
      return Y + b
  
imports: from copy import deepcopy
  import backend
  import dgl
  import dgl.function
  import dgl.nn.tensorflow
  import networkx
  import numpy
  import pytest
  import scipy
  import tensorflow
  from tensorflow.keras import layers
  from utils import parametrize_idtype
  from utils.graph_cases import get_cases, random_bipartite, random_dglgraph, random_graph
label_desc: Use image node_id 1 for calling a global function with example usage: _AXWb(A, X, W, b) and returns: unknown