class_docstr: Standard TensorFlow model for unit testing.
class_docstr_tok: ["Standard","TensorFlow","model","for","unit","testing","."]
code: def __init__(self):
      super(TensorFlowModel, self).__init__()
      self.conv1 = Conv2D(filters=4, kernel_size=5, activation="relu")
      self.conv2 = Conv2D(filters=10, kernel_size=5, activation="relu")
      self.maxpool = MaxPool2D(
          pool_size=(2, 2),
          strides=(2, 2),
          padding="valid",
          data_format=None,
      )
      self.flatten = Flatten()
      self.dense1 = Dense(100, activation="relu")
      self.logits = Dense(10, activation="linear")
  
file_path: adversarial-robustness-toolbox/examples/get_started_tensorflow_v2.py
imports: import numpy
  from art.attacks.evasion import FastGradientMethod
  from art.estimators.classification import TensorFlowV2Classifier
  from art.utils import load_mnist
  import tensorflow
  from tensorflow.keras import Model
  from tensorflow.keras.layers import Dense, Flatten, Conv2D, MaxPool2D
label_desc: Use image node_id 1 to create a new TensorFlowModel object from inherited base classes: Model with example: obj = TensorFlowModel()