/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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==============================================================================*/
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#ifndef TENSORFLOW_CORE_FRAMEWORK_STATS_AGGREGATOR_H_
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#define TENSORFLOW_CORE_FRAMEWORK_STATS_AGGREGATOR_H_
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#include <memory>
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#include <string>
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#include "tensorflow/core/framework/resource_mgr.h"
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#include "tensorflow/core/lib/gtl/array_slice.h"
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namespace tensorflow {
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class Summary;
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namespace data {
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// A `StatsAggregator` accumulates statistics incrementally. A
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// `StatsAggregator` can accumulate multiple different statistics, distinguished
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// by a string name.
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//
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// The class currently supports accumulating `Histogram` objects, and we expect
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// to add other methods in future.
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//
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// NOTE(mrry): `StatsAggregator` is a virtual interface because we anticipate
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// that many different implementations will the same interface. For example, the
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// current implementation in "stats_aggregator_ops.cc" is a simple in-memory
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// implementation that integrates with the pull-based summary API, and we may
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// add implementations that work with the push-based `SummaryWriterInterface`,
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// as well as custom monitoring services.
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class StatsAggregator {
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public:
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virtual ~StatsAggregator() {}
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// Add the given `values` to the histogram with the given `name`. Each
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// element of `values` will be treated as a separate sample in the histogram.
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virtual void AddToHistogram(const string& name,
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gtl::ArraySlice<double> values) = 0;
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// TODO(shivaniagarawal): consistency in double and float usage.
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// Add the given `value` as Scalar with the given `name`.
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virtual void AddScalar(const string& name, float value) = 0;
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// Stores a protocol buffer representation of the aggregator state in the
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// given `out_summary`.
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// TODO(mrry): Consider separating this method from the `StatsAggregator`
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// interface. It is possible that not all implementations will support
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// encoding their state as a protocol buffer.
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virtual void EncodeToProto(Summary* out_summary) = 0;
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// Increment the `label` cell of metrics mapped with `name` by given `value`.
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virtual void IncrementCounter(const string& name, const string& label,
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int64 val) = 0;
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};
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// A `StatsAggregatorResource` wraps a shareable `StatsAggregator` as a resource
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// in the TensorFlow resource manager.
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//
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// NOTE(mrry): This class is separate from `StatsAggregator` in order to
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// simplify the memory management of the shared object. Most users of
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// `StatsAggregator` interact with a `std::shared_ptr<StatsAggregator>` whereas
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// the `ResourceBase` API requires explicit reference counting.
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class StatsAggregatorResource : public ResourceBase {
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public:
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// Creates a new resource from the given `stats_aggregator`.
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StatsAggregatorResource(std::unique_ptr<StatsAggregator> stats_aggregator)
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: stats_aggregator_(stats_aggregator.release()) {}
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// Returns the wrapped `StatsAggregator`.
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std::shared_ptr<StatsAggregator> stats_aggregator() const {
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return stats_aggregator_;
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}
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string DebugString() const override { return "StatsAggregatorResource"; }
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private:
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const std::shared_ptr<StatsAggregator> stats_aggregator_;
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};
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} // namespace data
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} // namespace tensorflow
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#endif // TENSORFLOW_CORE_FRAMEWORK_STATS_AGGREGATOR_H_
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