Ids-Based-On-GAN-CNN/Network/BiGAN/Discriminator.py

from tensorflow.keras import Input, Model
from tensorflow.keras.layers import concatenate, Dense, LeakyReLU, Dropout


def build_discriminator(latent_dim):
    z = Input(shape=(latent_dim,))
    data = Input(shape=(121,))
    d_in = concatenate([z, data])

    model = Dense(128, kernel_initializer='glorot_uniform')(d_in)
    model = LeakyReLU(alpha=0.1)(model)
    model = Dropout(0.2)(model)
    model = Dense(128, kernel_initializer='glorot_uniform')(model)
    model = LeakyReLU(alpha=0.1)(model)
    model = Dropout(0.2)(model)
    model = Dense(128, kernel_initializer='glorot_uniform')(model)
    model = LeakyReLU(alpha=0.1)(model)
    model = Dropout(0.2)(model)
    validity = Dense(1, activation="sigmoid")(model)

    return Model([z, data], validity)