1d1a6e087a
1. Split DPQuery.accumulate_record function into preprocess_record and accumulate_preprocessed_record. 2. Add merge_sample_state function. 3. Add default implementations for some functions in DPQuery, and add base class SumAggregationDPQuery that implements some more. Only get_noised_result is still abstract. 4. Enforce that all states and parameters used as inputs and outputs to DPQuery functions are nested structures of tensors by replacing numbers with constants and Nones with empty tuples. PiperOrigin-RevId: 247975791
71 lines
2.4 KiB
Python
71 lines
2.4 KiB
Python
# Copyright 2018, The TensorFlow Authors.
|
|
#
|
|
# 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.
|
|
"""Implements DPQuery interface for no privacy average queries."""
|
|
|
|
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
|
|
from distutils.version import LooseVersion
|
|
import tensorflow as tf
|
|
|
|
from privacy.dp_query import dp_query
|
|
|
|
if LooseVersion(tf.__version__) < LooseVersion('2.0.0'):
|
|
nest = tf.contrib.framework.nest
|
|
else:
|
|
nest = tf.nest
|
|
|
|
|
|
class NoPrivacySumQuery(dp_query.SumAggregationDPQuery):
|
|
"""Implements DPQuery interface for a sum query with no privacy.
|
|
|
|
Accumulates vectors without clipping or adding noise.
|
|
"""
|
|
|
|
def get_noised_result(self, sample_state, global_state):
|
|
"""See base class."""
|
|
return sample_state, global_state
|
|
|
|
|
|
class NoPrivacyAverageQuery(dp_query.SumAggregationDPQuery):
|
|
"""Implements DPQuery interface for an average query with no privacy.
|
|
|
|
Accumulates vectors and normalizes by the total number of accumulated vectors.
|
|
"""
|
|
|
|
def initial_sample_state(self, global_state, template):
|
|
"""See base class."""
|
|
return (
|
|
super(NoPrivacyAverageQuery, self).initial_sample_state(
|
|
global_state, template),
|
|
tf.constant(0.0))
|
|
|
|
def preprocess_record(self, params, record, weight=1):
|
|
"""Multiplies record by weight."""
|
|
weighted_record = nest.map_structure(lambda t: weight * t, record)
|
|
return (weighted_record, weight)
|
|
|
|
def accumulate_record(self, params, sample_state, record, weight=1):
|
|
"""Accumulates record, multiplying by weight."""
|
|
weighted_record = nest.map_structure(lambda t: weight * t, record)
|
|
return self.accumulate_preprocessed_record(
|
|
sample_state, (weighted_record, weight))
|
|
|
|
def get_noised_result(self, sample_state, global_state):
|
|
"""See base class."""
|
|
sum_state, denominator = sample_state
|
|
|
|
return nest.map_structure(
|
|
lambda t: tf.truediv(t, denominator), sum_state), ()
|