code: def test_mix_gan_reload():
      """Test reloading a GAN with multiple generators and discriminators."""
  
      model_dir = tempfile.mkdtemp()
      gan = ExampleGAN(
          n_generators=2,
          n_discriminators=2,
          learning_rate=0.01,
          model_dir=model_dir,
      )
      gan.fit_gan(generate_data(gan, 1000, 100), generator_steps=0.5)
  
      reloaded_gan = ExampleGAN(
          n_generators=2,
          n_discriminators=2,
          learning_rate=0.01,
          model_dir=model_dir,
      )
      reloaded_gan.restore()
      # See if it has done a plausible job of learning the distribution.
  
      means = 10 * np.random.random([1000, 1])
      batch_size = len(means)
      noise_input = gan.get_noise_batch(batch_size=batch_size)
      for i in range(2):
          values = gan.predict_gan_generator(
              noise_input=noise_input,
              conditional_inputs=[means],
              generator_index=i,
          )
          reloaded_values = reloaded_gan.predict_gan_generator(
              noise_input=noise_input,
              conditional_inputs=[means],
              generator_index=i,
          )
          assert np.all(values == reloaded_values)
      assert gan.get_global_step() == 1000
      # No training has been done after reload
      assert reloaded_gan.get_global_step() == 0
  
file_path: deepchem/deepchem/models/tests/test_gan.py
imports: import deepchem
  import numpy
  import pytest
  import tempfile
  from flaky import flaky
label_desc: Use image node_id 5 for calling a global function with example usage: test_mix_gan_reload() without return types