keras sequential model

import numpy as np
import pandas as pd
from tensorflow import keras
from tensorflow.keras import layers

def rm_main(data):

print(data.columns)
x_train = (data.drop(["Window id"],axis=1).values)[:, :, np.newaxis]
print(x_train.shape)



    model = keras.Sequential(
        [
            layers.Input(shape=(x_train.shape[1], x_train.shape[2])),
            layers.Conv1D(
                filters=32, kernel_size=7, padding="same", strides=2, activation="relu"
            ),
            layers.Dropout(rate=0.2),
            layers.Conv1D(
                filters=16, kernel_size=7, padding="same", strides=2, activation="relu"
            ),
            layers.Conv1DTranspose(
                filters=16, kernel_size=7, padding="same", strides=2, activation="relu"
            ),
            layers.Dropout(rate=0.2),
            layers.Conv1DTranspose(
                filters=32, kernel_size=7, padding="same", strides=2, activation="relu"
            ),
            layers.Conv1DTranspose(filters=1, kernel_size=7, padding="same"),
        ]
    )
    model.compile(optimizer=keras.optimizers.Adam(learning_rate=0.001), loss="mse")
    model.summary()
    
    history = model.fit(
    x_train,
    x_train,
    epochs=50,
    batch_size=128,
    validation_split=0.1,
    callbacks=[
        keras.callbacks.EarlyStopping(monitor="val_loss", patience=5, mode="min")
        ],
    )
    
    return model

But, I got the following error. 

TypeError: can't pickle weakref objects

It's because keras sequential model is weakref object. 

And I found this thead. 

https://community.rapidminer.com/discussion/55837/see-the-python-script-of-keras-model

In this thead, I found the following post.

jacobcybulski Posts: 376   Unicorn

July 2019