lp7.py

#The below is the code generated by get_code() method.
import pickle

import lineapy
import tensorflow as tf
from lineapy.utils.utils import prettify
from tensorflow import keras
from tensorflow.keras import layers

normalizer = tf.keras.layers.Normalization(axis=-1)
train_features1 = pickle.load(open("/root/.lineapy/linea_pickles/yzU2NLl", "rb"))
train_labels1 = pickle.load(open("/root/.lineapy/linea_pickles/GPSupKi", "rb"))


def build_and_compile_model(norm):
    model = keras.Sequential(
        [
            norm,
            layers.Dense(64, activation="relu"),
            layers.Dense(64, activation="relu"),
            layers.Dense(1),
        ]
    )

    model.compile(loss="mean_absolute_error", optimizer=tf.keras.optimizers.Adam(0.001))
    return model


dnn_model = build_and_compile_model(normalizer)
history = dnn_model.fit(
    train_features1, train_labels1, validation_split=0.2, verbose=0, epochs=100
)