Added support for plotting scalars through palaas tbwriter interface. (#580)

Summary: Changes for supporting tensorboard scalar plotting.

Reviewed By: myleott

Differential Revision: D15456534

Pulled By: myleott

fbshipit-source-id: a012a4eea028aae764ce11786570b7d96841c4a5

fairseq/options.py

@@ -142,6 +142,8 @@ def get_parser(desc, default_task='translation'):
     parser.add_argument('--tensorboard-logdir', metavar='DIR', default='',
                         help='path to save logs for tensorboard, should match --logdir '
                              'of running tensorboard (default: no tensorboard logging)')
+    parser.add_argument("--tbmf-wrapper", action="store_true",
+                        help="[FB only] ")
     parser.add_argument('--seed', default=1, type=int, metavar='N',
                         help='pseudo random number generator seed')
     parser.add_argument('--cpu', action='store_true', help='use CPU instead of CUDA')

fairseq/progress_bar.py

@@ -21,6 +21,7 @@ from tqdm import tqdm
 from fairseq import distributed_utils
 from fairseq.meters import AverageMeter, StopwatchMeter, TimeMeter
 
+g_tbmf_wrapper = None
 
 def build_progress_bar(args, iterator, epoch=None, prefix=None, default='tqdm', no_progress_bar='none'):
     if args.log_format is None:
@@ -40,7 +41,16 @@ def build_progress_bar(args, iterator, epoch=None, prefix=None, default='tqdm',
     else:
         raise ValueError('Unknown log format: {}'.format(args.log_format))
 
-    if args.tensorboard_logdir and distributed_utils.is_master(args):
+    if args.tbmf_wrapper and distributed_utils.is_master(args):
+        global g_tbmf_wrapper
+        if g_tbmf_wrapper is None:
+            try:
+                from fairseq.fb_tbmf_wrapper import fb_tbmf_wrapper
+            except Exception:
+                raise ImportError("fb_tbmf_wrapper package not found.")
+            g_tbmf_wrapper = fb_tbmf_wrapper
+        bar = g_tbmf_wrapper(bar, args, args.log_interval)
+    elif args.tensorboard_logdir and distributed_utils.is_master(args):
         bar = tensorboard_log_wrapper(bar, args.tensorboard_logdir, args)
 
     return bar