From ae180917b44984524567d86461f9289b8b102c4f Mon Sep 17 00:00:00 2001
From: "zuchen.wang" <zuchen.wang@vipshop.com>
Date: Sun, 21 Nov 2021 15:20:07 +0800
Subject: [PATCH] comment tensorboard output and output cls_accuracy in train
 loop

---
 fastreid/engine/defaults.py |  4 ++--
 fastreid/utils/events.py    | 10 ++++++++--
 2 files changed, 10 insertions(+), 4 deletions(-)

diff --git a/fastreid/engine/defaults.py b/fastreid/engine/defaults.py
index e17877d..0cb964a 100644
--- a/fastreid/engine/defaults.py
+++ b/fastreid/engine/defaults.py
@@ -208,7 +208,7 @@ class DefaultTrainer(TrainerBase):
             # ref to https://github.com/pytorch/pytorch/issues/22049 to set `find_unused_parameters=True`
             # for part of the parameters is not updated.
             model = DistributedDataParallel(
-                model, device_ids=[comm.get_local_rank()], broadcast_buffers=False, find_unused_parameters=True
+                model, device_ids=[comm.get_local_rank()], broadcast_buffers=False, find_unused_parameters=False
             )
 
         self._trainer = (AMPTrainer if cfg.SOLVER.AMP.ENABLED else SimpleTrainer)(
@@ -336,7 +336,7 @@ class DefaultTrainer(TrainerBase):
             # It may not always print what you want to see, since it prints "common" metrics only.
             CommonMetricPrinter(self.max_iter),
             JSONWriter(os.path.join(self.cfg.OUTPUT_DIR, "metrics.json")),
-            TensorboardXWriter(self.cfg.OUTPUT_DIR),
+            # TensorboardXWriter(self.cfg.OUTPUT_DIR),
         ]
 
     def train(self):
diff --git a/fastreid/utils/events.py b/fastreid/utils/events.py
index 8891d8f..31142e5 100644
--- a/fastreid/utils/events.py
+++ b/fastreid/utils/events.py
@@ -229,6 +229,11 @@ class CommonMetricPrinter(EventWriter):
         except KeyError:
             lr = "N/A"
 
+        try:
+            cls_accuracy = "{:.4f}".format( storage.history("cls_accuracy").latest())
+        except KeyError:
+            accuracy = "N/A"
+
         if torch.cuda.is_available():
             max_mem_mb = torch.cuda.max_memory_allocated() / 1024.0 / 1024.0
         else:
@@ -236,7 +241,7 @@ class CommonMetricPrinter(EventWriter):
 
         # NOTE: max_mem is parsed by grep in "dev/parse_results.sh"
         self.logger.info(
-            " {eta}epoch/iter: {epoch}/{iter}  {losses}  {time}{data_time}lr: {lr}  {memory}".format(
+                " {eta}epoch/iter: {epoch}/{iter}  {losses} cls_accuracy: {cls_accuracy} {time}{data_time}lr: {lr}  {memory}".format(
                 eta=f"eta: {eta_string}  " if eta_string else "",
                 epoch=epoch,
                 iter=iteration,
@@ -247,6 +252,7 @@ class CommonMetricPrinter(EventWriter):
                         if "loss" in k
                     ]
                 ),
+                cls_accuracy = cls_accuracy,
                 time="time: {:.4f}  ".format(iter_time) if iter_time is not None else "",
                 data_time="data_time: {:.4f}  ".format(data_time) if data_time is not None else "",
                 lr=lr,
@@ -458,4 +464,4 @@ class EventStorage:
         Delete all the stored histograms for visualization.
         This should be called after histograms are written to tensorboard.
         """
-        self._histograms = []
\ No newline at end of file
+        self._histograms = []