test.py

import unittest
from GANRandom import nftGAN  

class TestNftGAN(unittest.TestCase):
   
    def setUp(self):
        # Initialize the GAN object and other setup if needed
        self.gan = nftGAN(NOISE_SHAPE, IMAGE_SHAPE)  # Initialize with appropriate arguments

    def tearDown(self):
        # Clean up after each test if necessary
        pass

    def test_generate_noise(self):
        noise = self.gan.generateNoise(10)  # Generate 10 random noise vectors
        self.assertEqual(len(noise), 10)  # Check if the length of generated noise is as expected
        # Add more specific assertions as needed

    def test_generate_generator(self):
        generator = self.gan.generateGenerator()
        # Check if the generator is a Keras model with the expected architecture
        self.assertIsInstance(generator, keras.models.Sequential)
        # Add more specific assertions as needed

    def test_generate_critic(self):
        critic = self.gan.generateCriticer()
        # Check if the critic is a Keras model with the expected architecture
        self.assertIsInstance(critic, keras.models.Sequential)
        # Add more specific assertions as needed

    # Add more test methods for other functions and methods

if __name__ == '__main__':
    unittest.main()