text: /* 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.
  ==============================================================================*/
  
  #include "tensorflow/core/profiler/internal/tfprof_op.h"
  
  #include <stdio.h>
  #include <utility>
  
  #include "tensorflow/core/lib/strings/strcat.h"
  #include "tensorflow/core/lib/strings/stringprintf.h"
  #include "tensorflow/core/platform/regexp.h"
  #include "tensorflow/core/profiler/internal/tfprof_constants.h"
  #include "tensorflow/core/profiler/internal/tfprof_tensor.h"
  
  namespace tensorflow {
  namespace tfprof {
  namespace {
  string FormatToalExecTime(const ShowMultiNode* node,
                            const ShowMultiNode* root) {
    double accu_pct = 0.0;
    double pct = 0.0;
    if (node->proto().total_exec_micros() > 0) {
      accu_pct = 100.0 * node->proto().total_exec_micros() /
                 root->proto().total_exec_micros();
      pct =
          100.0 * node->proto().exec_micros() / root->proto().total_exec_micros();
    }
  
    return strings::Printf(
        "%30s", strings::Printf("%s (%.2f%%, %.2f%%)",
                                FormatTime(node->proto().exec_micros()).c_str(),
                                accu_pct, pct)
                    .c_str());
  }
  string FormatCPUExecTime(const ShowMultiNode* node, const ShowMultiNode* root) {
    double accu_pct = 0.0;
    double pct = 0.0;
    if (node->proto().total_cpu_exec_micros() > 0) {
      accu_pct = 100.0 * node->proto().total_cpu_exec_micros() /
                 root->proto().total_cpu_exec_micros();
      pct = 100.0 * node->proto().cpu_exec_micros() /
            root->proto().total_cpu_exec_micros();
    }
  
    return strings::Printf(
        "%30s",
        strings::Printf("%s (%.2f%%, %.2f%%)",
                        FormatTime(node->proto().cpu_exec_micros()).c_str(),
                        accu_pct, pct)
            .c_str());
  }
  string FormatAcceleratorExecTime(const ShowMultiNode* node,
                                   const ShowMultiNode* root) {
    double accu_pct = 0.0;
    double pct = 0.0;
    if (node->proto().total_accelerator_exec_micros() > 0) {
      accu_pct = 100.0 * node->proto().total_accelerator_exec_micros() /
                 root->proto().total_accelerator_exec_micros();
      pct = 100.0 * node->proto().accelerator_exec_micros() /
            root->proto().total_accelerator_exec_micros();
    }
  
    return strings::Printf(
        "%30s", strings::Printf(
                    "%s (%.2f%%, %.2f%%)",
                    FormatTime(node->proto().accelerator_exec_micros()).c_str(),
                    accu_pct, pct)
                    .c_str());
  }
  }  // namespace
  
  void TFOp::AddNode(TFGraphNode* node) {
    const string& op = node->op();
    if (tfcnodes_map_.find(op) == tfcnodes_map_.end()) {
      tfcnodes_map_[op] =
          std::unique_ptr<TFMultiGraphNode>(new TFMultiGraphNode(op));
    }
    TFMultiGraphNode* tfcnode = tfcnodes_map_[op].get();
    tfcnode->AddGraphNode(node);
  }
  
  void TFOp::Build() {
    for (auto& tn : tfcnodes_map_) {
      cnodes_map_[tn.first] =
          std::unique_ptr<OpNode>(new OpNode(tn.second.get()));
    }
  
    tfcnodes_map_[kTFProfRoot] =
        std::unique_ptr<TFMultiGraphNode>(new TFMultiGraphNode(kTFProfRoot));
    root_.reset(new OpNode(tfcnodes_map_[kTFProfRoot].get()));
  }
  
  const ShowMultiNode* TFOp::ShowInternal(const Options& opts,
                                          Timeline* timeline) {
    root_->ResetTotalStats();
    if (opts.output_type == kOutput[3]) {
      fprintf(stderr, "Only 'code' view supports pprof output now.\n");
      return root_.get();
    }
    if (opts.output_type == kOutput[1] || opts.output_type == kOutput[2]) {
      root_->formatted_str = FormatNode(root_.get(), root_.get(), opts);
    }
    if (timeline) {
      fprintf(stderr,
              "op view doesn't support timeline yet. "
              "Consider graph/scope/code view.\n");
      return root_.get();
    }
    if (cnodes_map_.empty()) {
      return root_.get();
    }
  
    std::vector<OpNode*> nodes;
    for (auto& n : cnodes_map_) {
      n.second->account = ReAccount(n.second.get(), opts);
      n.second->ResetTotalStats();
      n.second->AddSelfToTotalStats();
      nodes.push_back(n.second.get());
    }
    nodes = SortNodes(nodes, opts);
    // pre keeps track of previous visited node.
    OpNode* pre = nullptr;
    std::vector<OpNode*> account_nodes;
    for (auto it = nodes.rbegin(); it != nodes.rend(); ++it) {
      if ((*it)->account) {
        if (pre) (*it)->AggregateTotalStats(pre);
        account_nodes.push_back(*it);
        pre = *it;
      }
    }
    std::reverse(std::begin(account_nodes), std::end(account_nodes));
    if (pre) {
      root_->AggregateTotalStats(pre);
    }
  
    // Perform the display and optionally redo accounting.
    int64 depth = 0;
    std::vector<OpNode*> show_nodes;
    int64 start = SearchRoot(account_nodes, opts.start_name_regexes);
    for (int64 i = start; i < account_nodes.size(); ++i, ++depth) {
      OpNode* n = account_nodes[i];
      if (ShouldTrim(n, opts.trim_name_regexes) || depth > opts.max_depth) {
        break;
      }
      n->show = ShouldShow(n, opts, depth);
      if (n->show) show_nodes.push_back(n);
    }
  
    pre = nullptr;
    for (auto it = show_nodes.rbegin(); it != show_nodes.rend(); ++it) {
      if (opts.account_displayed_op_only) {
        (*it)->ResetTotalStats();
        (*it)->AddSelfToTotalStats();
        if (pre) (*it)->AggregateTotalStats(pre);
      }
      pre = *it;
    }
    if (opts.account_displayed_op_only) {
      root_->ResetTotalStats();
      if (pre) {
        root_->AggregateTotalStats(pre);
      }
    }
    if (opts.output_type == kOutput[1] || opts.output_type == kOutput[2]) {
      string display_str = FormatLegend(opts);
      for (OpNode* node : show_nodes) {
        display_str += FormatNode(node, root_.get(), opts);
      }
      // In op view, we don't show root (total). But it will still in proto.
      // TODO(xpan): Is it the right choice?
      root_->formatted_str = display_str;
    }
    // Populate the children field.
    auto* pre_pb = root_->mutable_proto();
    for (auto& show_node : show_nodes) {
      pre_pb->clear_children();
      pre_pb->add_children()->Swap(show_node->mutable_proto());
      pre_pb = pre_pb->mutable_children(0);
    }
    return root_.get();
  }
  
  int64 TFOp::SearchRoot(const std::vector<OpNode*> nodes,
                         const std::vector<string>& regexes) {
    if (regexes.empty() || (regexes.size() == 1 && regexes[0] == ".*")) {
      return 0;
    }
    int64 i = 0;
    for (; i < nodes.size(); ++i) {
      for (const string& regex : regexes) {
        if (RE2::FullMatch(nodes[i]->name(), regex)) {
          return i;
        }
      }
    }
    return i;
  }
  
  string TFOp::FormatMemoryNode(int64 node_total_bytes, int64 root_total_bytes,
                                int64 node_bytes) const {
    double accu_pct = 0.0;
    double pct = 0.0;
    if (node_bytes > 0) {
      accu_pct = 100.0 * node_total_bytes / root_total_bytes;
      pct = 100.0 * node_bytes / root_total_bytes;
    }
    return strings::Printf(
        "%30s", strings::Printf("%s (%.2f%%, %.2f%%)",
                                FormatMemory(node_bytes).c_str(), accu_pct, pct)
                    .c_str());
  }
  
  string TFOp::FormatNode(OpNode* node, OpNode* root, const Options& opts) const {
    std::vector<string> attrs;
  
    if (opts.select.find(kShown[0]) != opts.select.end()) {
      attrs.push_back(FormatMemoryNode(node->proto().total_requested_bytes(),
                                       root->proto().total_requested_bytes(),
                                       node->proto().requested_bytes()));
    }
  
    if (opts.select.find(kShown[11]) != opts.select.end()) {
      attrs.push_back(FormatMemoryNode(node->proto().total_peak_bytes(),
                                       root->proto().total_peak_bytes(),
                                       node->proto().peak_bytes()));
    }
  
    if (opts.select.find(kShown[12]) != opts.select.end()) {
      attrs.push_back(FormatMemoryNode(node->proto().total_residual_bytes(),
                                       root->proto().total_residual_bytes(),
                                       node->proto().residual_bytes()));
    }
    if (opts.select.find(kShown[13]) != opts.select.end()) {
      attrs.push_back(FormatMemoryNode(node->proto().total_output_bytes(),
                                       root->proto().total_output_bytes(),
                                       node->proto().output_bytes()));
    }
  
    if (opts.select.find(kShown[1]) != opts.select.end()) {
      attrs.push_back(FormatToalExecTime(node, root));
      attrs.push_back(FormatAcceleratorExecTime(node, root));
      attrs.push_back(FormatCPUExecTime(node, root));
    }
    if (opts.select.find(kShown[9]) != opts.select.end() &&
        opts.select.find(kShown[1]) == opts.select.end()) {
      attrs.push_back(FormatAcceleratorExecTime(node, root));
    }
    if (opts.select.find(kShown[10]) != opts.select.end() &&
        opts.select.find(kShown[1]) == opts.select.end()) {
      attrs.push_back(FormatCPUExecTime(node, root));
    }
    if (opts.select.find(kShown[2]) != opts.select.end()) {
      double accu_pct = 0.0;
      double pct = 0.0;
      if (node->proto().total_parameters() > 0) {
        accu_pct = 100.0 * node->proto().total_parameters() /
                   root->proto().total_parameters();
        pct =
            100.0 * node->proto().parameters() / root->proto().total_parameters();
      }
      attrs.push_back(strings::Printf(
          "%30s",
          strings::Printf("%s params (%.2f%%, %.2f%%)",
                          FormatNumber(node->proto().parameters()).c_str(),
                          accu_pct, pct)
              .c_str()));
    }
  
    if (opts.select.find(kShown[3]) != opts.select.end()) {
      double accu_pct = 0.0;
      double pct = 0.0;
      if (node->proto().total_float_ops() > 0) {
        accu_pct = 100.0 * node->proto().total_float_ops() /
                   root->proto().total_float_ops();
        pct = 100.0 * node->proto().float_ops() / root->proto().total_float_ops();
      }
  
      attrs.push_back(strings::Printf(
          "%30s", strings::Printf("%s float_ops (%.2f%%, %.2f%%)",
                                  FormatNumber(node->proto().float_ops()).c_str(),
                                  accu_pct, pct)
                      .c_str()));
    }
  
    if (opts.select.find(kShown[5]) != opts.select.end()) {
      attrs.push_back(absl::StrJoin(node->node->devices(), "|"));
    }
  
    if (opts.select.find(kShown[6]) != opts.select.end()) {
      std::set<string> op_types = node->node->op_types();
      attrs.push_back(absl::StrJoin(op_types, "|"));
    }
  
    if (opts.select.find(kShown[7]) != opts.select.end()) {
      int64 total_runs = 0;
      for (const auto& gnode : node->proto().graph_nodes()) {
        total_runs += gnode.run_count();
      }
      attrs.push_back(strings::Printf(
          "%10s",
          strings::Printf("%lld|%d", total_runs, node->proto().graph_nodes_size())
              .c_str()));
    }
  
    string node_str = strings::Printf("%-25s%s\n", node->name().c_str(),
                                      absl::StrJoin(attrs, ", ").c_str());
  
    if (opts.select.find(kShown[8]) != opts.select.end()) {
      string input_shape_str = FormatInputShapes(node->proto());
      if (!input_shape_str.empty()) {
        node_str = strings::Printf("%s\n%s\n\n", node_str.c_str(),
                                   input_shape_str.c_str());
      }
    }
    return node_str;
  }
  }  // namespace tfprof
  }  // namespace tensorflow
  