not able to predict with loaded model using universal embedding

[romass12]

Model architecture ---> adam=keras.optimizers.Adam(lr=0.0001) early_stopping = keras.callbacks.ModelCheckpoint(filepath, monitor='val_acc', verbose=0, save_best_only=True, save_weights_only=False, mode='auto', period=10) input_text = Input(shape=(1,), dtype="string") embedding = Lambda(UniversalEmbedding, output_shape=(512, ))(input_text) dense = Dense(1024)(embedding) bnorm = BatchNormalization()(dense) acti = Activation('relu')(bnorm) pred = Dense(number_classes, activation='softmax')(acti) model = Model(inputs=[input_text], outputs=pred) model.compile(loss='categorical_crossentropy', optimizer=adam, metrics=['accuracy',f1score,sensitivity,precision])

I loaded entire model as ---> with open('universal_model.json', 'r') as f: model = model_from_json(f.read()) model.load_weights('./universal_model.h5')

Now fro prediction --> predicts = model.predict(np.array(["hi"], dtype=object)) I get this error ---> FailedPreconditionError (see above for traceback): Attempting to use uninitialized value module/Encoder_en/DNN/ResidualHidden_3/projection [[{{node module_apply_default/Encoder_en/DNN/ResidualHidden_3/projection/read}} = Identity[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"] . (module/Encoder_en/DNN/ResidualHidden_3/projection)]]

TF version -- 1.11.0 Keras -- 2.2.4