Make output dir computation dependence on datasets config fields explicit

Reviewed By: rbgirshick

Differential Revision: D7086631

fbshipit-source-id: 8d1a756bdd187eb33cde0dac0dc73c5293ca17eb

lib/core/config.py

@@ -1032,12 +1032,15 @@ def cache_cfg_urls():
     )
 
 
-def get_output_dir(training=True):
+def get_output_dir(datasets, training=True):
     """Get the output directory determined by the current global config."""
-    dataset = ':'.join(__C.TRAIN.DATASETS) if training else __C.TEST.DATASET
+    assert isinstance(datasets, (tuple, list, basestring)), \
+        'datasets argument must be of type tuple, list or string'
+    is_string = isinstance(datasets, basestring)
+    dataset_name = datasets if is_string else ':'.join(datasets)
     tag = 'train' if training else 'test'
-    # <output-dir>/<train|test>/<dataset>/<model-type>/
-    outdir = osp.join(__C.OUTPUT_DIR, tag, dataset, __C.MODEL.TYPE)
+    # <output-dir>/<train|test>/<dataset-name>/<model-type>/
+    outdir = osp.join(__C.OUTPUT_DIR, tag, dataset_name, __C.MODEL.TYPE)
     if not osp.exists(outdir):
         os.makedirs(outdir)
     return outdir

lib/core/test_engine.py

@@ -81,9 +81,7 @@ def run_inference(ind_range=None, multi_gpu_testing=False, gpu_id=0):
             cfg.TEST.DATASET = cfg.TEST.DATASETS[i]
             if cfg.TEST.PRECOMPUTED_PROPOSALS:
                 cfg.TEST.PROPOSAL_FILE = cfg.TEST.PROPOSAL_FILES[i]
-            # Note that output dir computation cannot be moved before the
-            # if statement since it depends on the value of cfg.TEST.DATASET
-            output_dir = get_output_dir(training=False)
+            output_dir = get_output_dir(cfg.TEST.DATASET, training=False)
             results = parent_func(output_dir, multi_gpu=multi_gpu_testing)
             all_results.update(results)
 
@@ -93,7 +91,7 @@ def run_inference(ind_range=None, multi_gpu_testing=False, gpu_id=0):
         # In this case test_net was called via subprocess.Popen to execute on a
         # range of inputs on a single dataset (i.e., use cfg.TEST.DATASET and
         # don't loop over cfg.TEST.DATASETS)
-        output_dir = get_output_dir(training=False)
+        output_dir = get_output_dir(cfg.TEST.DATASET, training=False)
         return child_func(output_dir, ind_range=ind_range, gpu_id=gpu_id)
 
 

tools/train_net.py

@@ -175,7 +175,7 @@ def create_model():
     logger = logging.getLogger(__name__)
     start_iter = 0
     checkpoints = {}
-    output_dir = get_output_dir(training=True)
+    output_dir = get_output_dir(cfg.TRAIN.DATASETS, training=True)
     if cfg.TRAIN.AUTO_RESUME:
         # Check for the final model (indicates training already finished)
         final_path = os.path.join(output_dir, 'model_final.pkl')