from keras.layers import Dense, Embedding, Input
from keras.layers import Bidirectional, Dropout, CuDNNGRU
from keras.models import Model
from keras.optimizers import RMSprop
def get_model(embedding_matrix, sequence_length, dropout_rate, recurrent_units, dense_size):
input_layer = Input(shape=(sequence_length,))
embedding_layer = Embedding(embedding_matrix.shape[0], embedding_matrix.shape[1],
weights=[embedding_matrix], trainable=False)(input_layer)
x = Bidirectional(CuDNNGRU(recurrent_units, return_sequences=True))(embedding_layer)
x = Dropout(dropout_rate)(x)
x = Bidirectional(CuDNNGRU(recurrent_units, return_sequences=False))(x)
x = Dense(dense_size, activation="relu")(x)
output_layer = Dense(6, activation="sigmoid")(x)
model = Model(inputs=input_layer, outputs=output_layer)
model.compile(loss='binary_crossentropy',
optimizer=RMSprop(clipvalue=1, clipnorm=1),
metrics=['accuracy'])
return model
