| /* Copyright 2016 The TensorFlow Authors All Rights Reserved. |
| |
| 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. |
| ==============================================================================*/ |
| |
| // Parent class and utilities for tfprof_code. |
| |
| #ifndef TENSORFLOW_CORE_PROFILER_INTERNAL_TFPROF_SHOW_MULTI_H_ |
| #define TENSORFLOW_CORE_PROFILER_INTERNAL_TFPROF_SHOW_MULTI_H_ |
| |
| #include <algorithm> |
| #include <string> |
| #include <vector> |
| |
| #include "tensorflow/core/lib/core/errors.h" |
| #include "tensorflow/core/profiler/internal/tfprof_constants.h" |
| #include "tensorflow/core/profiler/internal/tfprof_node.h" |
| #include "tensorflow/core/profiler/internal/tfprof_node_show.h" |
| #include "tensorflow/core/profiler/internal/tfprof_show.h" |
| #include "tensorflow/core/profiler/internal/tfprof_tensor.h" |
| #include "tensorflow/core/profiler/internal/tfprof_timeline.h" |
| #include "tensorflow/core/profiler/internal/tfprof_utils.h" |
| #include "tensorflow/core/profiler/tfprof_options.h" |
| #include "tensorflow/core/profiler/tfprof_output.pb.h" |
| |
| namespace tensorflow { |
| namespace tfprof { |
| |
| class TFMultiShow { |
| public: |
| explicit TFMultiShow() {} |
| virtual ~TFMultiShow() {} |
| virtual void AddNode(TFGraphNode* node) = 0; |
| virtual void Build() = 0; |
| const MultiGraphNodeProto& Show(const string& prefix, const Options& opts); |
| |
| protected: |
| virtual const ShowMultiNode* ShowInternal(const Options& opts, |
| Timeline* timeline) = 0; |
| |
| bool LookUpCheckPoint(const string& name, |
| std::unique_ptr<TFProfTensor>* tensor); |
| |
| // Overridden by subclass if extra requirements need to be met. |
| virtual bool ShouldShowIfExtra(const ShowMultiNode* node, const Options& opts, |
| int depth) const { |
| return true; |
| } |
| |
| bool ShouldShow(const ShowMultiNode* node, const Options& opts, |
| int depth) const; |
| |
| bool ShouldTrim(const ShowMultiNode* node, |
| const std::vector<string>& regexes) const; |
| |
| bool ReAccount(ShowMultiNode* node, const Options& opts); |
| |
| string FormatLegend(const Options& opts) const; |
| string FormatInputShapes(const MultiGraphNodeProto& proto) const; |
| std::vector<string> FormatTimes(const ShowMultiNode* node, |
| const Options& opts) const; |
| |
| template <typename T> |
| std::vector<T*> SortNodes(const std::vector<T*>& nodes, const Options& opts) { |
| if (opts.order_by.empty() || nodes.empty()) { |
| return nodes; |
| } |
| std::vector<T*> sorted_nodes = nodes; |
| std::stable_sort(sorted_nodes.begin(), sorted_nodes.end(), |
| [&opts](const T* n1, const T* n2) { |
| if (n1->name() == kTFProfRoot) return true; |
| if (n2->name() == kTFProfRoot) return false; |
| bool name_cmp = n1->name() < n2->name(); |
| if (opts.order_by == kOrderBy[0]) { |
| return name_cmp; |
| } else if (opts.order_by == kOrderBy[1]) { |
| return n1->proto().total_requested_bytes() > |
| n2->proto().total_requested_bytes(); |
| } else if (opts.order_by == kOrderBy[2]) { |
| return n1->proto().total_peak_bytes() > |
| n2->proto().total_peak_bytes(); |
| } else if (opts.order_by == kOrderBy[3]) { |
| return n1->proto().total_residual_bytes() > |
| n2->proto().total_residual_bytes(); |
| } else if (opts.order_by == kOrderBy[4]) { |
| return n1->proto().total_output_bytes() > |
| n2->proto().total_output_bytes(); |
| } else if (opts.order_by == kOrderBy[5]) { |
| return n1->proto().total_exec_micros() > |
| n2->proto().total_exec_micros(); |
| } else if (opts.order_by == kOrderBy[6]) { |
| return n1->proto().total_accelerator_exec_micros() > |
| n2->proto().total_accelerator_exec_micros(); |
| } else if (opts.order_by == kOrderBy[7]) { |
| return n1->proto().total_cpu_exec_micros() > |
| n2->proto().total_cpu_exec_micros(); |
| } else if (opts.order_by == kOrderBy[8]) { |
| return n1->proto().total_parameters() > |
| n2->proto().total_parameters(); |
| } else if (opts.order_by == kOrderBy[9]) { |
| return n1->proto().total_float_ops() > |
| n2->proto().total_float_ops(); |
| } else if (opts.order_by == kOrderBy[10]) { |
| return n1->node->graph_nodes().size() > |
| n2->node->graph_nodes().size(); |
| } |
| return name_cmp; |
| }); |
| return sorted_nodes; |
| } |
| }; |
| |
| } // namespace tfprof |
| } // namespace tensorflow |
| |
| #endif // TENSORFLOW_CORE_PROFILER_INTERNAL_TFPROF_SHOW_MULTI_H_ |