tensorflow_privacy/research/pate_2018/ICLR2018/generate_table.sh
Nicolas Papernot 93e9585f18 Add missing licenses.
PiperOrigin-RevId: 229241117
2019-01-14 16:02:35 -08:00

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#!/bin/bash
# Copyright 2017 The 'Scalable Private Learning with PATE' Authors All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
echo "Reproducing Table 2. Takes a couple of hours."
executable="python smooth_sensitivity_table.py"
data_dir="data"
echo
echo "######## MNIST ########"
echo
$executable \
--counts_file=$data_dir"/mnist_250_teachers.npy" \
--threshold=200 \
--sigma1=150 \
--sigma2=40 \
--queries=640 \
--delta=1e-5
echo
echo "######## SVHN ########"
echo
$executable \
--counts_file=$data_dir"/svhn_250_teachers.npy" \
--threshold=300 \
--sigma1=200 \
--sigma2=40 \
--queries=8500 \
--delta=1e-6
echo
echo "######## Adult ########"
echo
$executable \
--counts_file=$data_dir"/adult_250_teachers.npy" \
--threshold=300 \
--sigma1=200 \
--sigma2=40 \
--queries=1500 \
--delta=1e-5
echo
echo "######## Glyph (Confident) ########"
echo
$executable \
--counts_file=$data_dir"/glyph_5000_teachers.npy" \
--threshold=1000 \
--sigma1=500 \
--sigma2=100 \
--queries=12000 \
--delta=1e-8
echo
echo "######## Glyph (Interactive, Round 1) ########"
echo
$executable \
--counts_file=$data_dir"/glyph_round1.npy" \
--threshold=3500 \
--sigma1=1500 \
--sigma2=100 \
--delta=1e-8
echo
echo "######## Glyph (Interactive, Round 2) ########"
echo
$executable \
--counts_file=$data_dir"/glyph_round2.npy" \
--baseline_file=$data_dir"/glyph_round2_student.npy" \
--threshold=3500 \
--sigma1=2000 \
--sigma2=200 \
--teachers=5000 \
--delta=1e-8