FIX: '--user-dir' on multi-gpu (facebookresearch#449)

Summary:
On a multi-gpu training scenario, the `train.py` script spawns new processes with `torch.multiprocessing.spawn`. Unfortunately those child processes don't inherit the modules imported with `--user-dir`.

This pull request fixes this problem: custom module import in now explicit on every `main()` function.
Pull Request resolved: facebookresearch#449

Differential Revision: D13676922

Pulled By: myleott

fbshipit-source-id: 520358d66155697885b878a37e7d0484bddbc1c6

eval_lm.py

@@ -16,6 +16,7 @@
 from fairseq import options, progress_bar, tasks, utils
 from fairseq.meters import StopwatchMeter, TimeMeter
 from fairseq.sequence_scorer import SequenceScorer
+from fairseq.utils import import_user_module
 
 
 class WordStat(object):
@@ -47,6 +48,8 @@ def __str__(self):
 def main(parsed_args):
     assert parsed_args.path is not None, '--path required for evaluation!'
 
+    import_user_module(parsed_args)
+
     print(parsed_args)
 
     use_cuda = torch.cuda.is_available() and not parsed_args.cpu

fairseq/options.py

@@ -127,9 +127,7 @@ def get_parser(desc, default_task='translation'):
     usr_parser = argparse.ArgumentParser(add_help=False)
     usr_parser.add_argument('--user-dir', default=None)
     usr_args, _ = usr_parser.parse_known_args()
-
-    if usr_args.user_dir is not None:
-        import_user_module(usr_args.user_dir)
+    import_user_module(usr_args)
 
     parser = argparse.ArgumentParser()
     # fmt: off

fairseq/utils.py

@@ -437,10 +437,15 @@ def nullsafe_min(l):
     return max_positions
 
 
-def import_user_module(module_path):
-    module_path = os.path.abspath(module_path)
-    module_parent, module_name = os.path.split(module_path)
-
-    sys.path.insert(0, module_parent)
-    importlib.import_module(module_name)
-    sys.path.pop(0)
+def import_user_module(args):
+    if hasattr(args, 'user_dir'):
+        module_path = args.user_dir
+
+        if module_path is not None:
+            module_path = os.path.abspath(args.user_dir)
+            module_parent, module_name = os.path.split(module_path)
+
+            if module_name not in sys.modules:
+                sys.path.insert(0, module_parent)
+                importlib.import_module(module_name)
+                sys.path.pop(0)

generate.py

@@ -15,6 +15,7 @@
 from fairseq.meters import StopwatchMeter, TimeMeter
 from fairseq.sequence_generator import SequenceGenerator
 from fairseq.sequence_scorer import SequenceScorer
+from fairseq.utils import import_user_module
 
 
 def main(args):
@@ -24,6 +25,8 @@ def main(args):
     assert args.replace_unk is None or args.raw_text, \
         '--replace-unk requires a raw text dataset (--raw-text)'
 
+    import_user_module(args)
+
     if args.max_tokens is None and args.max_sentences is None:
         args.max_tokens = 12000
     print(args)

interactive.py

@@ -17,7 +17,7 @@
 
 from fairseq import data, options, tasks, tokenizer, utils
 from fairseq.sequence_generator import SequenceGenerator
-
+from fairseq.utils import import_user_module
 
 Batch = namedtuple('Batch', 'srcs tokens lengths')
 Translation = namedtuple('Translation', 'src_str hypos pos_scores alignments')
@@ -56,6 +56,8 @@ def make_batches(lines, args, task, max_positions):
 
 
 def main(args):
+    import_user_module(args)
+
     if args.buffer_size < 1:
         args.buffer_size = 1
     if args.max_tokens is None and args.max_sentences is None:

preprocess.py

@@ -20,6 +20,8 @@
 from fairseq.tokenizer import Tokenizer, tokenize_line
 from multiprocessing import Pool
 
+from fairseq.utils import import_user_module
+
 
 def get_parser():
     parser = argparse.ArgumentParser()
@@ -66,6 +68,8 @@ def get_parser():
 
 
 def main(args):
+    import_user_module(args)
+
     print(args)
     os.makedirs(args.destdir, exist_ok=True)
     target = not args.only_source

train.py

@@ -21,9 +21,12 @@
 from fairseq.data import iterators
 from fairseq.trainer import Trainer
 from fairseq.meters import AverageMeter, StopwatchMeter
+from fairseq.utils import import_user_module
 
 
 def main(args):
+    import_user_module(args)
+
     if args.max_tokens is None:
         args.max_tokens = 6000
     print(args)