# Copyright 2019, 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 normalized 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 NormalizedQuery(dp_query.DPQuery):
  """DPQuery for queries with a DPQuery numerator and fixed denominator."""

  def __init__(self, numerator_query, denominator):
    """Initializer for NormalizedQuery.

    Args:
      numerator_query: A DPQuery for the numerator.
      denominator: A value for the denominator. May be None if it will be
        supplied via the set_denominator function before get_noised_result is
        called.
    """
    self._numerator = numerator_query
    self._denominator = (
        tf.cast(denominator, tf.float32) if denominator is not None else None)

  def initial_global_state(self):
    """See base class."""
    # NormalizedQuery has no global state beyond the numerator state.
    return self._numerator.initial_global_state()

  def derive_sample_params(self, global_state):
    """See base class."""
    return self._numerator.derive_sample_params(global_state)

  def initial_sample_state(self, global_state, template):
    """See base class."""
    # NormalizedQuery has no sample state beyond the numerator state.
    return self._numerator.initial_sample_state(global_state, template)

  def preprocess_record(self, params, record):
    return self._numerator.preprocess_record(params, record)

  def accumulate_preprocessed_record(
      self, sample_state, preprocessed_record):
    """See base class."""
    return self._numerator.accumulate_preprocessed_record(
        sample_state, preprocessed_record)

  def get_noised_result(self, sample_state, global_state):
    """See base class."""
    noised_sum, new_sum_global_state = self._numerator.get_noised_result(
        sample_state, global_state)
    def normalize(v):
      return tf.truediv(v, self._denominator)

    return nest.map_structure(normalize, noised_sum), new_sum_global_state

  def merge_sample_states(self, sample_state_1, sample_state_2):
    """See base class."""
    return self._numerator.merge_sample_states(sample_state_1, sample_state_2)

  def set_denominator(self, denominator):
    """Sets the denominator for the NormalizedQuery."""
    self._denominator = tf.cast(denominator, tf.float32)