Clean det ref (#1109)

* Doc multigpu and propagate data path.

* Use raw doc because of backslash.

references/detection/train.py

+r"""PyTorch Detection Training.
+
+To run in a multi-gpu environment, use the distributed launcher::
+
+    python -m torch.distributed.launch --nproc_per_node=$NGPU --use_env \
+        train.py ... --world-size $NGPU
+
+"""
 import datetime
 import os
 import time
@@ -18,10 +26,10 @@ import utils
 import transforms as T
 
 
-def get_dataset(name, image_set, transform):
+def get_dataset(name, image_set, transform, data_path):
     paths = {
-        "coco": ('/datasets01/COCO/022719/', get_coco, 91),
-        "coco_kp": ('/datasets01/COCO/022719/', get_coco_kp, 2)
+        "coco": (data_path, get_coco, 91),
+        "coco_kp": (data_path, get_coco_kp, 2)
     }
     p, ds_fn, num_classes = paths[name]
 
@@ -46,8 +54,8 @@ def main(args):
     # Data loading code
     print("Loading data")
 
-    dataset, num_classes = get_dataset(args.dataset, "train", get_transform(train=True))
-    dataset_test, _ = get_dataset(args.dataset, "val", get_transform(train=False))
+    dataset, num_classes = get_dataset(args.dataset, "train", get_transform(train=True), args.data_path)
+    dataset_test, _ = get_dataset(args.dataset, "val", get_transform(train=False), args.data_path)
 
     print("Creating data loaders")
     if args.distributed:
@@ -125,7 +133,8 @@ def main(args):
 
 if __name__ == "__main__":
     import argparse
-    parser = argparse.ArgumentParser(description='PyTorch Detection Training')
+    parser = argparse.ArgumentParser(
+        description=__doc__)
 
     parser.add_argument('--data-path', default='/datasets01/COCO/022719/', help='dataset')
     parser.add_argument('--dataset', default='coco', help='dataset')