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1 /* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
2 
3 Licensed under the Apache License, Version 2.0 (the "License");
4 you may not use this file except in compliance with the License.
5 You may obtain a copy of the License at
6 
7     http://www.apache.org/licenses/LICENSE-2.0
8 
9 Unless required by applicable law or agreed to in writing, software
10 distributed under the License is distributed on an "AS IS" BASIS,
11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 See the License for the specific language governing permissions and
13 limitations under the License.
14 ==============================================================================*/
15 
16 #ifndef TENSORFLOW_CORE_LIB_MONITORING_GAUGE_H_
17 #define TENSORFLOW_CORE_LIB_MONITORING_GAUGE_H_
18 
19 // clang-format off
20 // Required for IS_MOBILE_PLATFORM
21 #include "tensorflow/core/platform/platform.h"
22 // clang-format on
23 
24 // We replace this implementation with a null implementation for mobile
25 // platforms.
26 #ifdef IS_MOBILE_PLATFORM
27 #define TENSORFLOW_INCLUDED_FROM_GAUGE_H  // prevent accidental use of
28                                           // mobile_gauge.h
29 #include "tensorflow/core/lib/monitoring/mobile_gauge.h"
30 #undef TENSORFLOW_INCLUDED_FROM_GAUGE_H
31 #else
32 
33 #include <array>
34 #include <atomic>
35 #include <map>
36 
37 #include "tensorflow/core/lib/core/status.h"
38 #include "tensorflow/core/lib/monitoring/collection_registry.h"
39 #include "tensorflow/core/lib/monitoring/metric_def.h"
40 #include "tensorflow/core/platform/macros.h"
41 #include "tensorflow/core/platform/mutex.h"
42 #include "tensorflow/core/platform/thread_annotations.h"
43 #include "tensorflow/core/platform/types.h"
44 
45 namespace tensorflow {
46 namespace monitoring {
47 
48 // GaugeCell stores each value of a gauge.
49 //
50 // A cell can be passed off to a module which may repeatedly update it without
51 // needing further map-indexing computations. This improves both encapsulation
52 // (separate modules can own a cell each, without needing to know about the map
53 // to which both cells belong) and performance (since map indexing and
54 // associated locking are both avoided).
55 //
56 // This class is thread-safe.
57 template <typename T>
58 class GaugeCell {
59  public:
GaugeCell(const T & value)60   explicit GaugeCell(const T& value) : value_(value) {}
~GaugeCell()61   ~GaugeCell() {}
62 
63   // Atomically sets the value.
64   void Set(const T& value) TF_LOCKS_EXCLUDED(mu_);
65 
66   // Retrieves the current value.
67   T value() const TF_LOCKS_EXCLUDED(mu_);
68 
69  private:
70   T value_ TF_GUARDED_BY(mu_);
71   mutable mutex mu_;
72 
73   TF_DISALLOW_COPY_AND_ASSIGN(GaugeCell);
74 };
75 
76 // Explicit specialization of GaugeCell<int64>. Compared to the primary
77 // template, it uses atomic values as opposed to mutex. This class is
78 // thread-safe.
79 template <>
80 class GaugeCell<int64> {
81  public:
GaugeCell(int64 value)82   explicit GaugeCell(int64 value) : value_(value) {}
~GaugeCell()83   ~GaugeCell() {}
84 
85   // Atomically sets the value.
86   void Set(int64 value);
87 
88   // Retrieves the current value.
89   int64 value() const;
90 
91  private:
92   std::atomic<int64> value_;
93 
94   TF_DISALLOW_COPY_AND_ASSIGN(GaugeCell);
95 };
96 
97 // Explicit specialization of GaugeCell<bool>. Compared to the primary
98 // template, it uses atomic values as opposed to mutex. This class is
99 // thread-safe.
100 template <>
101 class GaugeCell<bool> {
102  public:
GaugeCell(bool value)103   explicit GaugeCell(bool value) : value_(value) {}
~GaugeCell()104   ~GaugeCell() {}
105 
106   // Atomically sets the value.
107   void Set(bool value);
108 
109   // Retrieves the current value.
110   bool value() const;
111 
112  private:
113   std::atomic<bool> value_;
114 
115   TF_DISALLOW_COPY_AND_ASSIGN(GaugeCell);
116 };
117 
118 // A stateful class for updating a gauge-like metric. Allowed ValueType are
119 // int64, string and bool.
120 //
121 // This class encapsulates a set of values (or a single value for a label-less
122 // metric). Each value is identified by a tuple of labels. The class allows the
123 // user to set each value.
124 //
125 // Gauge allocates storage and maintains a cell for each value. You can
126 // retrieve an individual cell using a label-tuple and update it separately.
127 // This improves performance since operations related to retrieval, like
128 // map-indexing and locking, are avoided.
129 //
130 // This class is thread-safe.
131 template <typename ValueType, int NumLabels>
132 class Gauge {
133  public:
~Gauge()134   ~Gauge() {
135     // Deleted here, before the metric_def is destroyed.
136     registration_handle_.reset();
137   }
138 
139   // Creates the metric based on the metric-definition arguments.
140   //
141   // Example:
142   //
143   // auto* string_gauge_with_label = Gauge<string,1>::New(
144   //   "/tensorflow/string_gauge_with_label",
145   //   "String gauge with one label.", "MyLabelName");
146   //
147   // auto* integer_gauge = Gauge<int64, 0>::New("/tensorflow/integer_gauge",
148   //   "Integer gauge")
149   //
150   // auto* bool_gauge = Gauge<bool, 0>::New("/tensorflow/bool_gauge",
151   //   "Bool gauge")
152   template <typename... MetricDefArgs>
153   static Gauge* New(MetricDefArgs&&... metric_def_args);
154 
155   // Retrieves the cell for the specified labels, creating it on demand if not
156   // already present.
157   template <typename... Labels>
158   GaugeCell<ValueType>* GetCell(const Labels&... labels) TF_LOCKS_EXCLUDED(mu_);
159 
GetStatus()160   Status GetStatus() { return status_; }
161 
162  private:
Gauge(const MetricDef<MetricKind::kGauge,ValueType,NumLabels> & metric_def)163   explicit Gauge(
164       const MetricDef<MetricKind::kGauge, ValueType, NumLabels>& metric_def)
165       : metric_def_(metric_def),
166         registration_handle_(CollectionRegistry::Default()->Register(
167             &metric_def_, [&](MetricCollectorGetter getter) {
168               auto metric_collector = getter.Get(&metric_def_);
169 
170               mutex_lock l(mu_);
171               for (const auto& cell : cells_) {
172                 metric_collector.CollectValue(cell.first, cell.second.value());
173               }
174             })) {
175     if (registration_handle_) {
176       status_ = Status::OK();
177     } else {
178       status_ = Status(tensorflow::error::Code::ALREADY_EXISTS,
179                        "Another metric with the same name already exists.");
180     }
181   }
182 
183   mutable mutex mu_;
184 
185   Status status_;
186 
187   // The metric definition. This will be used to identify the metric when we
188   // register it for collection.
189   const MetricDef<MetricKind::kGauge, ValueType, NumLabels> metric_def_;
190 
191   std::unique_ptr<CollectionRegistry::RegistrationHandle> registration_handle_;
192 
193   using LabelArray = std::array<string, NumLabels>;
194   std::map<LabelArray, GaugeCell<ValueType> > cells_ TF_GUARDED_BY(mu_);
195 
196   TF_DISALLOW_COPY_AND_ASSIGN(Gauge);
197 };
198 
199 ////
200 //  Implementation details follow. API readers may skip.
201 ////
202 template <typename T>
Set(const T & value)203 void GaugeCell<T>::Set(const T& value) {
204   mutex_lock l(mu_);
205   value_ = value;
206 }
207 
208 template <typename T>
value()209 T GaugeCell<T>::value() const {
210   mutex_lock l(mu_);
211   return value_;
212 }
213 
Set(int64 value)214 inline void GaugeCell<int64>::Set(int64 value) { value_ = value; }
215 
value()216 inline int64 GaugeCell<int64>::value() const { return value_; }
217 
Set(bool value)218 inline void GaugeCell<bool>::Set(bool value) { value_ = value; }
219 
value()220 inline bool GaugeCell<bool>::value() const { return value_; }
221 
222 template <typename ValueType, int NumLabels>
223 template <typename... MetricDefArgs>
New(MetricDefArgs &&...metric_def_args)224 Gauge<ValueType, NumLabels>* Gauge<ValueType, NumLabels>::New(
225     MetricDefArgs&&... metric_def_args) {
226   static_assert(std::is_same<ValueType, int64>::value ||
227                     std::is_same<ValueType, string>::value ||
228                     std::is_same<ValueType, bool>::value,
229                 "Gauge only allows bool, int64, and string types.");
230   return new Gauge<ValueType, NumLabels>(
231       MetricDef<MetricKind::kGauge, ValueType, NumLabels>(
232           std::forward<MetricDefArgs>(metric_def_args)...));
233 }
234 
235 template <typename ValueType, int NumLabels>
236 template <typename... Labels>
GetCell(const Labels &...labels)237 GaugeCell<ValueType>* Gauge<ValueType, NumLabels>::GetCell(
238     const Labels&... labels) TF_LOCKS_EXCLUDED(mu_) {
239   // Provides a more informative error message than the one during array
240   // construction below.
241   static_assert(
242       sizeof...(Labels) == NumLabels,
243       "Mismatch between Gauge<ValueType, NumLabels> and number of labels "
244       "provided in GetCell(...).");
245 
246   const LabelArray& label_array = {{labels...}};
247   mutex_lock l(mu_);
248   const auto found_it = cells_.find(label_array);
249   if (found_it != cells_.end()) {
250     return &(found_it->second);
251   }
252   return &(cells_
253                .emplace(std::piecewise_construct,
254                         std::forward_as_tuple(label_array),
255                         std::forward_as_tuple(ValueType()))
256                .first->second);
257 }
258 
259 }  // namespace monitoring
260 }  // namespace tensorflow
261 
262 #endif  // IS_MOBILE_PLATFORM
263 #endif  // TENSORFLOW_CORE_LIB_MONITORING_GAUGE_H_
264