<reponame>wqruan/tf-encrypted<filename>examples/logistic/prediction_single.py
"""Private prediction with a single clients"""
import tf_encrypted as tfe
from common import LogisticRegression
from common import PredictionClient

num_features = 10

model = LogisticRegression(num_features)
prediction_client = PredictionClient("prediction-client", num_features)

x = prediction_client.provide_input()

y = model.forward(x)

reveal_output = prediction_client.receive_output(y)

with tfe.Session() as sess:
    sess.run(tfe.global_variables_initializer(), tag="init")

    sess.run(reveal_output, tag="predict")

"""Private prediction with a single clients"""
import tf_encrypted as tfe
from common import LogisticRegression
from common import PredictionClient

num_features = 10

model = LogisticRegression(num_features)
prediction_client = PredictionClient("prediction-client", num_features)

x = prediction_client.provide_input()

y = model.forward(x)

reveal_output = prediction_client.receive_output(y)

with tfe.Session() as sess:
    sess.run(tfe.global_variables_initializer(), tag="init")

    sess.run(reveal_output, tag="predict")
Private prediction with a single clients