Failed to load model with CondRNN layer about cond_rnn HOT 1 CLOSED

import numpy as np
from tensorflow.keras.layers import Dense
from tensorflow.keras.models import Sequential

from cond_rnn import ConditionalRNN

i1 = Input(shape = (X_train.shape[1], X_train.shape[2]))
ic_1 = Input(shape=(categorical_appid.shape[1],))
ic_2 = Input(shape=(categorical_advertiser.shape[1],))
cond_rnn_layer = ConditionalRNN(units=64, cell='LSTM', return_sequences=True, mask=-1)([i1, ic_1, ic_2])
out_layer = TimeDistributed(Dense(Y_train_non_lt.shape[2], activation='relu'),name = 'm_output')(cond_rnn_layer)
model = Model([i1, ic_1, ic_2], out_layer)

optim = Adam(lr=0.003,)
model.compile(optimizer=optim, loss={'m_output': 'mse'}, metrics={'m_output': 'mse'})

callbacks = [
                EarlyStopping(patience=30, monitor='val_mse'),
                ModelCheckpoint(filepath='model_tuning/day_20210511/seq_model.{epoch:02d}-{val_loss:.2f}.h5', monitor="val_loss", save_best_only=True),
                TensorBoard(log_dir='./training_logs_0511/seq'),
            ]

out = model.fit(x=[X_train, categorical_appid, categorical_advertiser],  y=Y_train, epochs=100, batch_size = 1024,  verbose=2, callbacks=callbacks, workers = 100, validation_data=([X_eval, categorical_appid_eval, categorical_advertiser_eval], Y_eval),
          sample_weight=None)