what algorithm is being used in this generative model?

Question

what neural network is used in this generative models code?

def make_generator_model():
     model = tf.keras.Sequential()
     model.add(layers.Dense(16, use_bias=False, input_shape=(100,)))
     model.add(layers.BatchNormalization())
     model.add(layers.LeakyReLU())

     model.add(layers.Dense(16))
     assert model.output_shape == (None,16 ) # Note: None is the batch size

     model.add(layers.Dense(32)) # what does 32 denote here
     model.add(layers.BatchNormalization())
     model.add(layers.LeakyReLU())

     model.add(layers.Dense(32))
     model.add(layers.BatchNormalization())
     model.add(layers.LeakyReLU())

     model.add(layers.Dense(32))
     model.add(layers.BatchNormalization())
     model.add(layers.LeakyReLU())

     model.add(layers.Dense(8))
     assert model.output_shape == (None,8 )


     return model

this is a code based on the generative adversarial network model. i have a discriminator model also but I need to find out if this generative model is using cnn or lstm or other algorithm to create the generate model.

Answer 1

I think its CNN , If u put your full code it may easy to find

Batch Normalisation maximum used in conventional Neural network only