input: Write a python function to build and compile a simple Convolutional Neural Network model using TensorFlow for binary classification.
  assert build_compile_cnn_model((64, 64, 3), 2) is not None
output: def build_compile_cnn_model(input_shape, num_classes):
      import tensorflow as tf
      from tensorflow.keras import layers, models
  
      model = models.Sequential()
      model.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=input_shape))
      model.add(layers.MaxPooling2D((2, 2)))
      model.add(layers.Conv2D(64, (3, 3), activation='relu'))
      model.add(layers.MaxPooling2D((2, 2)))
      model.add(layers.Conv2D(64, (3, 3), activation='relu'))
  
      model.add(layers.Flatten())
      model.add(layers.Dense(64, activation='relu'))
      model.add(layers.Dense(num_classes, activation='softmax'))
  
      model.compile(optimizer='adam',
                    loss='sparse_categorical_crossentropy',
                    metrics=['accuracy'])
      return model