code: def matmul_wrapper(A, B, optype):
      """Wrapper for handling sparse and dense versions of `tf.matmul` operation.
  
      Parameters
      ----------
      A : tf.Tensor
      B : tf.Tensor
      optype : str, {'dense', 'sparse'}
  
      Returns
      -------
      tf.Tensor
      """
      with tf.name_scope("matmul_wrapper") as scope:
          if optype == "dense":
              return tf.matmul(A, B)
          elif optype == "sparse":
              return tf.sparse_tensor_dense_matmul(A, B)
          else:
              raise NameError("Unknown input type in matmul_wrapper")
  
file_path: tffm/tffm/utils.py
imports: import math
  import numpy
  import tensorflow
  import itertools
  from itertools import combinations_with_replacement, takewhile, count
  from collections import defaultdict
label_desc: Use image node_id 5 for calling a global function with example usage: matmul_wrapper(A, B, optype) and returns: tf, tf