<reponame>limash/python_snippets<gh_stars>0
from tensorflow.keras import layers
from tensorflow import keras

inputs = None

x = layers.Dense(500, kernel_initializer="he_normal",
                 kernel_regularizer=keras.regularizers.l2(0.01),
                 )(inputs)
x = layers.Dropout(rate=0.2)(x)
x = layers.BatchNormalization()(x)
x = layers.LeakyReLU(alpha=0.2)(x)

x = layers.Dense(500, kernel_initializer="he_normal",
                 kernel_regularizer=keras.regularizers.l2(0.01),
                 )(x)
x = layers.Dropout(rate=0.2)(x)
x = layers.BatchNormalization()(x)
x = layers.LeakyReLU(alpha=0.2)(x)

from tensorflow.keras import layers
from tensorflow import keras

inputs = None

x = layers.Dense(500, kernel_initializer="he_normal",
                 kernel_regularizer=keras.regularizers.l2(0.01),
                 )(inputs)
x = layers.Dropout(rate=0.2)(x)
x = layers.BatchNormalization()(x)
x = layers.LeakyReLU(alpha=0.2)(x)

x = layers.Dense(500, kernel_initializer="he_normal",
                 kernel_regularizer=keras.regularizers.l2(0.01),
                 )(x)
x = layers.Dropout(rate=0.2)(x)
x = layers.BatchNormalization()(x)
x = layers.LeakyReLU(alpha=0.2)(x)