class_docstr: Model taken from my traffic signs recognition repo.
  https://github.com/waleedka/traffic-signs-tensorflow
class_docstr_tok: ["Model","taken","from","my","traffic","signs","recognition","repo",".","https",":","\/\/github.com\/waleedka\/traffic-signs-tensorflow"]
code: def __init__(self):
      self.graph = tf.Graph()
      with self.graph.as_default():
          # Global step counter
          self.global_step = tf.Variable(
              0, trainable=False, name="global_step"
          )
          # Placeholders
          self.images = tf.placeholder(
              tf.float32, [None, 32, 32, 3], name="images"
          )
          self.labels = tf.placeholder(tf.int32, [None], name="labels")
          # Layers
          self.conv1 = self.conv(self.images, 8)
          self.pool1 = self.pool(self.conv1)
          self.conv2 = self.conv(self.pool1, 12)
          self.pool2 = self.pool(self.conv2)
          self.conv3 = self.conv(self.pool2, 16)
          self.pool3 = self.pool(self.conv3)
          self.flat = layers.flatten(self.pool3)
          # TODO             self.h1 = layers.fully_connected(self.flat, 200, lrelu)
          self.logits = layers.fully_connected(self.flat, 62, lrelu)
          # Convert one-hot vector to label index (int).
          self.predicted_labels = tf.argmax(self.logits, 1)
          # Loss
          self.loss = tf.reduce_mean(
              tf.nn.sparse_softmax_cross_entropy_with_logits(
                  logits=self.logits,
                  labels=self.labels,
                  name="test_name",
              )
          )
          # Training Ops
          self.train = tf.train.AdamOptimizer(
              learning_rate=0.001
          ).minimize(self.loss, global_step=self.global_step)
          self.init = tf.global_variables_initializer()
          # Create session
          self.session = tf.Session()
          # Run initialization op
          self.session.run(self.init)
  
file_path: hiddenlayer/tests/test_tf_graph.py
imports: import os
  import sys
  import shutil
  import unittest
  import tensorflow
  import tensorflow.contrib.slim.nets
  from tensorflow.contrib import layers
  import hiddenlayer
label_desc: Use image node_id 3 to create a new TrafficSignsModel object  with example: obj = TrafficSignsModel()