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# Copyright 2019, The TensorFlow Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Implements DPQuery interface for normalized queries.
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"""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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2019-04-29 15:00:20 -06:00
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from distutils.version import LooseVersion
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import tensorflow as tf
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from privacy.dp_query import dp_query
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if LooseVersion(tf.__version__) < LooseVersion('2.0.0'):
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nest = tf.contrib.framework.nest
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else:
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nest = tf.nest
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class NormalizedQuery(dp_query.DPQuery):
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"""DPQuery for queries with a DPQuery numerator and fixed denominator."""
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def __init__(self, numerator_query, denominator):
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"""Initializer for NormalizedQuery.
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Args:
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numerator_query: A DPQuery for the numerator.
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denominator: A value for the denominator. May be None if it will be
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supplied via the set_denominator function before get_noised_result is
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called.
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"""
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self._numerator = numerator_query
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self._denominator = (
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tf.cast(denominator, tf.float32) if denominator is not None else None)
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def initial_global_state(self):
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"""See base class."""
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# NormalizedQuery has no global state beyond the numerator state.
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return self._numerator.initial_global_state()
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def derive_sample_params(self, global_state):
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"""See base class."""
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return self._numerator.derive_sample_params(global_state)
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def initial_sample_state(self, global_state, template):
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"""See base class."""
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# NormalizedQuery has no sample state beyond the numerator state.
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return self._numerator.initial_sample_state(global_state, template)
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def preprocess_record(self, params, record):
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return self._numerator.preprocess_record(params, record)
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def accumulate_preprocessed_record(
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self, sample_state, preprocessed_record):
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"""See base class."""
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return self._numerator.accumulate_preprocessed_record(
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sample_state, preprocessed_record)
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def get_noised_result(self, sample_state, global_state):
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"""See base class."""
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noised_sum, new_sum_global_state = self._numerator.get_noised_result(
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sample_state, global_state)
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def normalize(v):
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return tf.truediv(v, self._denominator)
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return nest.map_structure(normalize, noised_sum), new_sum_global_state
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def merge_sample_states(self, sample_state_1, sample_state_2):
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"""See base class."""
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return self._numerator.merge_sample_states(sample_state_1, sample_state_2)
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def set_denominator(self, denominator):
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"""Sets the denominator for the NormalizedQuery."""
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self._denominator = tf.cast(denominator, tf.float32)
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