TensorFlow equivalent of neurips_tfe_minimal.py

neurips_tf_minimal.py

import tensorflow as tf


# generic function stubs
def provide_weights(): """Load model weights."""
def provide_input(): """Load input data."""


# get model weights/input data
# (both unencrypted)
w0, b0, w1, b1, w2, b2 = provide_weights()
x = provide_input()




# compute prediction
layer0 = tf.nn.relu((tf.matmul(x, w0) + b0))
layer1 = tf.nn.relu((tf.matmul(layer0, w1) + b1))
logits = tf.matmul(layer2, w2) + b2

# get result of prediction and print
prediction_op = tf.Print(result,
                         [logits],
                         summarize=10)

# run graph execution in a tf.Session
with tf.Session() as sess:
    sess.run(tf.global_variables_initializer(),
             tag="init")
    sess.run(prediction_op, tag="prediction")