class_docstr: A very simple neural network
code: def fprop(self, x, **kwargs):
      del kwargs
      with tf.variable_scope(self.scope, reuse=tf.AUTO_REUSE):
          w1 = tf.constant(
              [[1.5, 0.3], [-2, 0.3]], dtype=tf.as_dtype(x.dtype)
          )
          w2 = tf.constant(
              [[-2.4, 1.2], [0.5, -2.3]], dtype=tf.as_dtype(x.dtype)
          )
      h1 = tf.nn.sigmoid(tf.matmul(x, w1))
      res = tf.matmul(h1, w2)
      return {
          self.O_FEATURES: [h1, res],
          self.O_LOGITS: res,
          self.O_PROBS: tf.nn.softmax(res),
      }
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import unittest
  import numpy
  import tensorflow
  from cleverhans.attacks import FastGradientMethod
  from cleverhans.loss import CrossEntropy, MixUp, FeaturePairing
  from cleverhans.devtools.checks import CleverHansTest
  from cleverhans.model import Model
label_desc: Use image node_id 2 for calling the SimpleModel obj's underlying member method code with example usage: obj.fprop(x) and returns: dict