Help required to implement the below model using Bi-GRU As you can see in above images I need to model Bi-GRUs stacked as shown in table which takes input (N,1,64) and outputs (N,204). The input data is binary number stream and so is output data. Can anyone please help me get started?

Thank you.
from keras.layers import LSTM
from keras.models import Sequential
from keras.layers import LSTM
from keras.layers import Dense,BatchNormalization
model = Sequential()
model.add(LSTM(800, return_sequences=True,
               input_shape=(1, 64)))  # returns a sequence of vectors of dimension 32
model.add(BatchNormalization())  # returns a sequence of vectors of dimension 32
model.add(LSTM(800))  # return a single vector of dimension 32
model.add(BatchNormalization())
model.add(Dense(204, activation='sigmoid'))

model.compile(loss='binary_crossentropy', optimizer='Adam',metrics=['accuracy'])


model.summary()


I figured it out on my own.