Adding option to save the pipeline config file during evaluation.

PiperOrigin-RevId: 362353183

research/object_detection/model_lib_v2.py

@@ -506,6 +506,8 @@ def train_loop(
 
   # Write the as-run pipeline config to disk.
   if save_final_config:
+    tf.logging.info('Saving pipeline config file to directory {}'.format(
+        model_dir))
     pipeline_config_final = create_pipeline_proto_from_configs(configs)
     config_util.save_pipeline_config(pipeline_config_final, model_dir)
 
@@ -991,6 +993,7 @@ def eval_continuously(
     wait_interval=180,
     timeout=3600,
     eval_index=0,
+    save_final_config=False,
     **kwargs):
   """Run continuous evaluation of a detection model eagerly.
 
@@ -1022,7 +1025,8 @@ def eval_continuously(
       will terminate if no new checkpoints are found after these many seconds.
     eval_index: int, If given, only evaluate the dataset at the given
       index. By default, evaluates dataset at 0'th index.
-
+    save_final_config: Whether to save the pipeline config file to the model
+      directory.
     **kwargs: Additional keyword arguments for configuration override.
   """
   get_configs_from_pipeline_file = MODEL_BUILD_UTIL_MAP[
@@ -1046,7 +1050,9 @@ def eval_continuously(
         'Forced number of epochs for all eval validations to be 1.')
   configs = merge_external_params_with_configs(
       configs, None, kwargs_dict=kwargs)
-  if model_dir:
+  if model_dir and save_final_config:
+    tf.logging.info('Saving pipeline config file to directory {}'.format(
+        model_dir))
     pipeline_config_final = create_pipeline_proto_from_configs(configs)
     config_util.save_pipeline_config(pipeline_config_final, model_dir)