How to concatenate two models

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Vivek Kumar

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Nov 3, 2022, 12:42:51 AM11/3/22
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Hi All,
       how to two models concatenate or marge model1 & model2 both are written in TensorFlow. Please help me with this issue.

-------------------------Model 1 --> LSTM Model---------------------------------


model1 = tf.keras.Sequential([
tf.keras.layers.Embedding(vocab_size, embedding_dim, input_length = max_length),
tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32)),
tf.keras.layers.Dense(1, activation='relu'),
tf.keras.layers.Dense(1, activation='sigmoid')
])

model1.compile(loss='binary_crossentropy',optimizer='adam',metrics=['accuracy'])
# history1 = model1.fit(training_padded, training_labels, epochs=2, validation_data=(testing_padded, testing_labels), verbose=2)
score,acc=model1.evaluate(testing_padded,testing_labels)
acc,score

#RNN Model
print('''

-------------------------Model 2 --> RNN Model---------------------------------

''')
model2 = tf.keras.Sequential([
tf.keras.layers.Embedding(vocab_size, embedding_dim, input_length=max_length),
tf.keras.layers.Bidirectional(tf.keras.layers.SimpleRNN(50, return_sequences=True,input_shape=(max_length, embedding_dim))),
tf.keras.layers.Dropout(0.5),
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(1, activation='sigmoid')
])

model2.compile(loss='binary_crossentropy',optimizer='adam',metrics=['accuracy'])
history2 = model2.fit(training_padded, training_labels, epochs=2, validation_data=(testing_padded, testing_labels), verbose=2)
score,acc=model2.evaluate(testing_padded,testing_labels)
acc,score



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