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import numpy as np
import tensorflow as tf
import tensorflow.keras.backend as K
from tensorflow.keras.layers import Input, Dense, concatenate, Embedding, Reshape
from tensorflow.keras.models import Model
input_user = Input(shape=(3,))
input_ad = Input(shape=(3,))
gender_samples = Input(shape=(1,), dtype='int32')
gender_values = ['m', 'f', 'a']
gender_embeddings = Embedding(len(gender_values), 1)(gender_samples)
reshape_gender = Reshape(target_shape=[1])(gender_embeddings)
model2 = Model(inputs=[gender_samples], outputs=reshape_gender)
model2.summary()
merged = concatenate([input_user, input_ad, reshape_gender])
output_1 = Dense(64, activation='relu')(merged)
output_2 = Dense(64, activation='relu')(output_1)
predictions = Dense(1)(output_2)
model = Model(inputs=[input_user, input_ad, gender_samples], outputs=predictions)
model.compile(optimizer='adam',
loss='binary_crossentropy',
metrics=['accuracy'])
model.summary()
SAMPLES = 1000
user_data = np.random.rand(SAMPLES,3)
ad_data = np.random.rand(SAMPLES,3)
gender_data = np.random.randint(len(gender_values), size=SAMPLES)
labels = np.random.rand(SAMPLES,1)
print(user_data[:10])
print(ad_data[:10])
print(gender_data[:10])
print(labels[:10])
model.fit([user_data, ad_data, gender_data], labels, epochs=10, ) # starts training
user_data_sample1 = np.random.rand(1, 3)
ad_data_sample1 = np.random.rand(1, 3)
gender_data_sample1 = np.random.randint(len(gender_values), size=1)
print("predicting for:")
print(user_data_sample1)
print(ad_data_sample1)
print(gender_data_sample1)
predictions = model.predict([user_data_sample1, ad_data_sample1, gender_data_sample1])
print(predictions)
signature = tf.saved_model.signature_def_utils.predict_signature_def(
inputs={'input1': model.inputs[0],'input2': model.inputs[1], 'input3': model.inputs[2] }, outputs={'pctrx': model.outputs[0]})
builder = tf.saved_model.builder.SavedModelBuilder('modelv2')
builder.add_meta_graph_and_variables(
sess=K.get_session(),
tags=[tf.saved_model.tag_constants.SERVING],
signature_def_map={
tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY:
signature
})
builder.save()
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