code: def dense(
      tensor,
      output_size,
      stddev=0.02,
      bias_start=0.0,
      with_w=False,
      backend="tensorflow",
      name="dense",
  ):
      if backend == "tensorflow":
          with tf.variable_scope(name):
              shape = tensor.get_shape().as_list()
  
              matrix = tf.get_variable(
                  "Matrix",
                  [shape[1], output_size],
                  tf.float32,
                  tf.contrib.layers.xavier_initializer(),
              )
  
              bias = tf.get_variable(
                  "bias",
                  [output_size],
                  initializer=tf.zeros_initializer(),
              )
  
              if with_w:
                  return tf.matmul(tensor, matrix) + bias, matrix, bias
              else:
                  return tf.matmul(tensor, matrix) + bias
  
imports: import tensorflow
label_desc: Use image node_id 18 for calling a global function with example usage: dense(tensor, output_size, stddev, bias_start, with_w, backend, name) and returns: unknown,  matrix,  bias, unknown