1/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
2
3Licensed under the Apache License, Version 2.0 (the "License");
4you may not use this file except in compliance with the License.
5You may obtain a copy of the License at
6
7    http://www.apache.org/licenses/LICENSE-2.0
8
9Unless required by applicable law or agreed to in writing, software
10distributed under the License is distributed on an "AS IS" BASIS,
11WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12See the License for the specific language governing permissions and
13limitations under the License.
14==============================================================================*/
15
16#include "tensorflow/core/lib/monitoring/sampler.h"
17
18// We replace this implementation with a null implementation for mobile
19// platforms.
20#include "tensorflow/core/platform/platform.h"
21#ifdef IS_MOBILE_PLATFORM
22// Do nothing.
23#else
24
25namespace tensorflow {
26namespace monitoring {
27namespace {
28
29class ExplicitBuckets : public Buckets {
30 public:
31  ~ExplicitBuckets() override = default;
32
33  explicit ExplicitBuckets(std::vector<double> bucket_limits)
34      : bucket_limits_(std::move(bucket_limits)) {
35    CHECK_GT(bucket_limits_.size(), 0);
36    // Verify that the bucket boundaries are strictly increasing
37    for (size_t i = 1; i < bucket_limits_.size(); i++) {
38      CHECK_GT(bucket_limits_[i], bucket_limits_[i - 1]);
39    }
40    // We augment the bucket limits so that all boundaries are within [-DBL_MAX,
41    // DBL_MAX].
42    //
43    // Since we use ThreadSafeHistogram, we don't have to explicitly add
44    // -DBL_MAX, because it uses these limits as upper-bounds, so
45    // bucket_count[0] is always the number of elements in
46    // [-DBL_MAX, bucket_limits[0]).
47    if (bucket_limits_.back() != DBL_MAX) {
48      bucket_limits_.push_back(DBL_MAX);
49    }
50  }
51
52  const std::vector<double>& explicit_bounds() const override {
53    return bucket_limits_;
54  }
55
56 private:
57  std::vector<double> bucket_limits_;
58
59  TF_DISALLOW_COPY_AND_ASSIGN(ExplicitBuckets);
60};
61
62class ExponentialBuckets : public Buckets {
63 public:
64  ~ExponentialBuckets() override = default;
65
66  ExponentialBuckets(double scale, double growth_factor, int bucket_count)
67      : explicit_buckets_(
68            ComputeBucketLimits(scale, growth_factor, bucket_count)) {}
69
70  const std::vector<double>& explicit_bounds() const override {
71    return explicit_buckets_.explicit_bounds();
72  }
73
74 private:
75  static std::vector<double> ComputeBucketLimits(double scale,
76                                                 double growth_factor,
77                                                 int bucket_count) {
78    CHECK_GT(bucket_count, 0);
79    std::vector<double> bucket_limits;
80    double bound = scale;
81    for (int i = 0; i < bucket_count; i++) {
82      bucket_limits.push_back(bound);
83      bound *= growth_factor;
84    }
85    return bucket_limits;
86  }
87
88  ExplicitBuckets explicit_buckets_;
89
90  TF_DISALLOW_COPY_AND_ASSIGN(ExponentialBuckets);
91};
92
93}  // namespace
94
95// static
96std::unique_ptr<Buckets> Buckets::Explicit(
97    std::initializer_list<double> bucket_limits) {
98  return std::unique_ptr<Buckets>(new ExplicitBuckets(bucket_limits));
99}
100
101// static
102std::unique_ptr<Buckets> Buckets::Exponential(double scale,
103                                              double growth_factor,
104                                              int bucket_count) {
105  return std::unique_ptr<Buckets>(
106      new ExponentialBuckets(scale, growth_factor, bucket_count));
107}
108
109}  // namespace monitoring
110}  // namespace tensorflow
111
112#endif  // IS_MOBILE_PLATFORM
113