code: def convolutional_model_without_final_activation(random_data):
      x, y = random_data
      model = tf.keras.Sequential(
          [
              tf.keras.layers.Conv2D(
                  16,
                  (3, 3),
                  activation=None,
                  name="conv_1",
                  input_shape=list(x.shape[1:]),
              ),
              tf.keras.layers.ReLU(name="activation_1"),
              tf.keras.layers.Flatten(),
              tf.keras.layers.Dense(2)
              # No final Softmax layer
          ]
      )
  
      model.compile(optimizer="adam", loss="categorical_crossentropy")
  
      return model
  
file_path: tf-explain/tests/conftest.py
imports: import shutil
  from pathlib import Path
  import numpy
  import pytest
  import tensorflow
label_desc: Use image node_id 7 for calling a global function with example usage: convolutional_model_without_final_activation(random_data) and returns: model