From 7338be22f26a47ca0bb13ef7f24077964e28cc73 Mon Sep 17 00:00:00 2001
From: Miguel Varela Ramos <miguelvramos@ist.utl.pt>
Date: Fri, 31 May 2019 20:02:17 +0200
Subject: [PATCH] Save full configuration in output dir (#835)

* Merge branch 'master' of /home/braincreator/projects/maskrcnn-benchmark with conflicts.

* update Dockerfile

* save config in output dir

* replace string format with os.path.join
---
 maskrcnn_benchmark/utils/miscellaneous.py | 7 +++++++
 tools/train_net.py                        | 7 ++++++-
 2 files changed, 13 insertions(+), 1 deletion(-)

diff --git a/maskrcnn_benchmark/utils/miscellaneous.py b/maskrcnn_benchmark/utils/miscellaneous.py
index db9a8b367..ecd3ef6a2 100644
--- a/maskrcnn_benchmark/utils/miscellaneous.py
+++ b/maskrcnn_benchmark/utils/miscellaneous.py
@@ -1,6 +1,7 @@
 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
 import errno
 import os
+from .comm import is_main_process
 
 
 def mkdir(path):
@@ -9,3 +10,9 @@ def mkdir(path):
     except OSError as e:
         if e.errno != errno.EEXIST:
             raise
+
+
+def save_config(cfg, path):
+    if is_main_process():
+        with open(path, 'w') as f:
+            f.write(cfg.dump())
diff --git a/tools/train_net.py b/tools/train_net.py
index 9f4761b3f..3468fbb4a 100644
--- a/tools/train_net.py
+++ b/tools/train_net.py
@@ -23,7 +23,7 @@
 from maskrcnn_benchmark.utils.comm import synchronize, get_rank
 from maskrcnn_benchmark.utils.imports import import_file
 from maskrcnn_benchmark.utils.logger import setup_logger
-from maskrcnn_benchmark.utils.miscellaneous import mkdir
+from maskrcnn_benchmark.utils.miscellaneous import mkdir, save_config
 
 # See if we can use apex.DistributedDataParallel instead of the torch default,
 # and enable mixed-precision via apex.amp
@@ -176,6 +176,11 @@ def main():
         logger.info(config_str)
     logger.info("Running with config:\n{}".format(cfg))
 
+    output_config_path = os.path.join(cfg.OUTPUT_DIR, 'config.yml')
+    logger.info("Saving config into: {}".format(output_config_path))
+    # save overloaded model config in the output directory
+    save_config(cfg, output_config_path)
+
     model = train(cfg, args.local_rank, args.distributed)
 
     if not args.skip_test: