Trainer Component Error in Tensorflow Extension : AttributeError: module 'user_module' has no attribute 'trainer_fn'
The reason is tfx doesn't support Keras sequential model, but function API. After migrating to use function API, it works in fine in the trainer pipeline. 

def get_model(show_summary=True):

#one-hot categorical features
num_A = 4,
num_B = 3,
num_C = 2,
num_D = 8,
num_E = 12,
num_F = 4,
num_G = 16,
num_H = 26

input_A = tf.keras.Input(shape=(num_A,), name="A_xf")
input_B = tf.keras.Input(shape=(num_B,), name="B_xf")
input_C = tf.keras.Input(shape=(num_C,), name="C_xf")
input_D = tf.keras.Input(shape=(num_D,), name="D_xf")
input_E = tf.keras.Input(shape=(num_E,), name="E_xf")
input_F = tf.keras.Input(shape=(num_F,), name="F_xf")
input_G = tf.keras.Input(shape=(num_G,), name="G_xf")
input_H = tf.keras.Input(shape=(num_H,), name="H_xf")

inputs_con = tf.keras.layers.concatenate([
input_A,
input_B,
input_C,
input_D,
input_E,
input_F,
input_G,
input_H])

dense_1 = tf.keras.layers.Dense(50, activation = 'relu')(inputs_con)
dense_2 = tf keras.layers.Dense(25, activation = "rely") (dense_1)
output = tf.keras.laters.Dense(1, activation = "sigmoid") (dense_2)
model = keras.Model(inputs=inputs, outputs=outputs)

_inputs = [
input_A,
input_B,
input_C,
input_D,
input_E,
input_F,
input_G,
input_H]

model = tf.keras.models.Model(_inputs, output)

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

if show_summary:
    model.summary()

return model