Marge two models in tensorflow

[Vivek Kumar]

Hi All,

       how to two models concat or marge model1 & model2 both are written in TensorFlow. Please help me with this issue.

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

[Vivek Kumar]

LSTM and RNN Models