From 14d4bdb4067cee72290d22cd4bf3a623f49fcab2 Mon Sep 17 00:00:00 2001
From: Fei Sun <feisun@fb.com>
Date: Mon, 23 Jul 2018 10:54:25 -0700
Subject: [PATCH] Reformat output data format to make it more general for other
 binaries (#9555)

Summary:
This is to simplify the data format during benchmarking. After this change, we can use the same benchmarking harness data conversion method to parse data from multiple binaries.

This change should be coordinated with the PR: https://github.com/facebook/FAI-PEP/pull/63
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9555

Reviewed By: pjh5

Differential Revision: D8903024

Pulled By: sf-wind

fbshipit-source-id: 61cabcff99f0873729142ec6cb6dc230c685d13a
---
 .../observers/net_observer_reporter_print.cc  | 83 +++++++++----------
 1 file changed, 40 insertions(+), 43 deletions(-)

diff --git a/modules/observers/net_observer_reporter_print.cc b/modules/observers/net_observer_reporter_print.cc
index 2355fedc9a1..b3341bef6ae 100644
--- a/modules/observers/net_observer_reporter_print.cc
+++ b/modules/observers/net_observer_reporter_print.cc
@@ -14,63 +14,60 @@ void NetObserverReporterPrint::report(
     NetBase* net,
     std::map<std::string, PerformanceInformation>& info) {
   // Not allowed to use json library
-  std::map<
-      std::string,
-      std::map<std::string, std::map<std::string, std::string>>>
-      caffe2_perf;
+  std::vector<std::map<std::string, std::string>> caffe2_perf;
 
   for (auto& p : info) {
     if ((p.first == "NET_DELAY") && (info.size() == 1)) {
       // for Net_delay perf
-      caffe2_perf["NET"] = {
-          {"latency",
-           {{"value", caffe2::to_string(p.second.latency * 1000)},
-            {"unit", "us"}}},
-          {"flops", {{"value", "-1"}, {"unit", "flops"}}}};
+      caffe2_perf.push_back(
+          {{"type", "NET"},
+           {"value", caffe2::to_string(p.second.latency * 1000)},
+           {"unit", "us"},
+           {"metric", "latency"}});
     } else if (p.first != "NET_DELAY") {
       // for operator perf
       std::string shape_str = get_tensor_shapes(p.second);
       std::string args_str = get_op_args(p.second);
 
-      caffe2_perf[p.first] = {
-          {"latency",
-           {{"value", caffe2::to_string(p.second.latency * 1000)},
-            {"unit", "us"}}},
-          {"flops",
-           {{
-                "value",
-                caffe2::to_string(p.second.flops),
-            },
-            {"unit", "flops"}}},
-          {"tensor_shapes", {{"info_string", shape_str}, {"unit", ""}}},
-          {"op_args", {{"info_string", args_str}, {"unit", ""}}}};
+      caffe2_perf.push_back(
+          {{"type", p.first},
+           {"value", caffe2::to_string(p.second.latency * 1000)},
+           {"unit", "us"},
+           {"metric", "latency"}});
+      if (p.second.flops > 0) {
+        caffe2_perf.push_back({{"type", p.first},
+                               {"value", caffe2::to_string(p.second.flops)},
+                               {"unit", "flop"},
+                               {"metric", "flops"}});
+      }
+      if (shape_str != "") {
+        caffe2_perf.push_back({{"type", p.first},
+                               {"info_string", shape_str},
+                               {"unit", ""},
+                               {"metric", "tensor_shapes"}});
+      }
+      if (args_str != "") {
+        caffe2_perf.push_back({{"type", p.first},
+                               {"info_string", args_str},
+                               {"unit", ""},
+                               {"metric", "op_args"}});
+      }
     }
   }
 
   for (auto it = caffe2_perf.begin(); it != caffe2_perf.end(); it++) {
     std::stringstream buffer;
+    auto entry = *it;
     buffer << IDENTIFIER << "{";
-    buffer << "\"" << it->first << "\""
-           << ": {";
-    for (auto jt = it->second.begin(); jt != it->second.end(); jt++) {
-      buffer << "\"" << jt->first << "\""
-             << ": {";
-      for (auto kt = jt->second.begin(); kt != jt->second.end(); kt++) {
-        buffer << "\"" << kt->first << "\""
-               << ": "
-               << "\"" << kt->second << "\"";
-        auto lt = kt;
-        if ((++lt) != jt->second.end()) {
-          buffer << ", ";
-        }
-      }
-      buffer << "}";
-      auto lt = jt;
-      if ((++lt) != it->second.end()) {
-        buffer << ", ";
-      }
+    buffer << "\"type\": \"" << entry["type"] << "\","
+           << "\"unit\": \"" << entry["unit"] << "\","
+           << "\"metric\": \"" << entry["metric"] << "\",";
+    if (entry.find("value") != entry.end()) {
+      buffer << "\"value\": \"" << entry["value"] << "\"";
+    } else if (entry.find("info_string") != entry.end()) {
+      buffer << "\"info_string\": \"" << entry["info_string"] << "\"";
     }
-    buffer << "}}";
+    buffer << "}";
     LOG(INFO) << buffer.str();
   }
 }
@@ -90,7 +87,7 @@ static std::string get_tensor_shapes(PerformanceInformation p) {
     shape_stream << "]";
     shape_str = shape_stream.str();
   } else {
-    shape_str = "[]";
+    shape_str = "";
   }
   return shape_str;
 }
@@ -118,7 +115,7 @@ static std::string get_op_args(PerformanceInformation p) {
     args << "]";
     args_str = args.str();
   } else {
-    args_str = "[]";
+    args_str = "";
   }
   return args_str;
 }