Fix arg formatting in preprocess.py and add fmt control for black formatting (#399)

Summary:
Not switching to Black formatting just yet, but adding fmt: off directives in case we decide to later.
Pull Request resolved: https://github.com/pytorch/fairseq/pull/399

Differential Revision: D13364674

Pulled By: myleott

fbshipit-source-id: a20a11a18be3d583ee30eff770278fb4bd05b93c

fairseq/criterions/composite_loss.py

@@ -19,8 +19,10 @@ class CompositeLoss(FairseqCriterion):
     @staticmethod
     def add_args(parser):
         """Add criterion-specific arguments to the parser."""
+        # fmt: off
         parser.add_argument('--underlying-criterion', type=str, metavar='VAL', required=True,
                             help='underlying criterion to use for the composite loss')
+        # fmt: on
 
     def __init__(self, args, task):
         super().__init__(args, task)

fairseq/criterions/label_smoothed_cross_entropy.py

@@ -22,8 +22,10 @@ class LabelSmoothedCrossEntropyCriterion(FairseqCriterion):
     @staticmethod
     def add_args(parser):
         """Add criterion-specific arguments to the parser."""
+        # fmt: off
         parser.add_argument('--label-smoothing', default=0., type=float, metavar='D',
                             help='epsilon for label smoothing, 0 means no label smoothing')
+        # fmt: on
 
     def forward(self, model, sample, reduce=True):
         """Compute the loss for the given sample.

fairseq/models/fconv.py

@@ -48,6 +48,7 @@ class FConvModel(FairseqModel):
     @staticmethod
     def add_args(parser):
         """Add model-specific arguments to the parser."""
+        # fmt: off
         parser.add_argument('--dropout', type=float, metavar='D',
                             help='dropout probability')
         parser.add_argument('--encoder-embed-dim', type=int, metavar='N',
@@ -70,6 +71,7 @@ class FConvModel(FairseqModel):
                             help='share input and output embeddings (requires'
                                  ' --decoder-out-embed-dim and --decoder-embed-dim'
                                  ' to be equal)')
+        # fmt: on
 
     @classmethod
     def build_model(cls, args, task):

fairseq/models/fconv_self_att.py

@@ -41,6 +41,7 @@ class FConvModelSelfAtt(FairseqModel):
     @staticmethod
     def add_args(parser):
         """Add model-specific arguments to the parser."""
+        # fmt: off
         parser.add_argument('--dropout', type=float, metavar='D',
                             help='dropout probability')
         parser.add_argument('--encoder-embed-dim', type=int, metavar='N',
@@ -75,6 +76,7 @@ class FConvModelSelfAtt(FairseqModel):
                             help='path to load checkpoint from pretrained model')
         parser.add_argument('--pretrained', type=str, metavar='EXPR',
                             help='use pretrained model when training [True, ...]')
+        # fmt: on
 
     @classmethod
     def build_model(cls, args, task):

fairseq/models/lstm.py

@@ -25,6 +25,7 @@ class LSTMModel(FairseqModel):
     @staticmethod
     def add_args(parser):
         """Add model-specific arguments to the parser."""
+        # fmt: off
         parser.add_argument('--dropout', type=float, metavar='D',
                             help='dropout probability')
         parser.add_argument('--encoder-embed-dim', type=int, metavar='N',
@@ -68,6 +69,7 @@ class LSTMModel(FairseqModel):
         parser.add_argument('--share-all-embeddings', default=False, action='store_true',
                             help='share encoder, decoder and output embeddings'
                                  ' (requires shared dictionary and embed dim)')
+        # fmt: on
 
     @classmethod
     def build_model(cls, args, task):

fairseq/models/transformer.py

@@ -49,6 +49,7 @@ class TransformerModel(FairseqModel):
     @staticmethod
     def add_args(parser):
         """Add model-specific arguments to the parser."""
+        # fmt: off
         parser.add_argument('--dropout', type=float, metavar='D',
                             help='dropout probability')
         parser.add_argument('--attention-dropout', type=float, metavar='D',
@@ -93,6 +94,7 @@ class TransformerModel(FairseqModel):
                                  'Must be used with adaptive_loss criterion'),
         parser.add_argument('--adaptive-softmax-dropout', type=float, metavar='D',
                             help='sets adaptive softmax dropout for the tail projections')
+        # fmt: on
 
     @classmethod
     def build_model(cls, args, task):
@@ -153,6 +155,7 @@ class TransformerLanguageModel(FairseqLanguageModel):
     @staticmethod
     def add_args(parser):
         """Add model-specific arguments to the parser."""
+        # fmt: off
         parser.add_argument('--dropout', default=0.1, type=float, metavar='D',
                             help='dropout probability')
         parser.add_argument('--attention-dropout', default=0., type=float, metavar='D',
@@ -205,6 +208,7 @@ class TransformerLanguageModel(FairseqLanguageModel):
                             help='if set, ties the projection weights of adaptive softmax and adaptive input')
         parser.add_argument('--decoder-learned-pos', action='store_true',
                             help='use learned positional embeddings in the decoder')
+        # fmt: on
 
     @classmethod
     def build_model(cls, args, task):

fairseq/optim/adam.py

@@ -21,10 +21,12 @@ class FairseqAdam(FairseqOptimizer):
     @staticmethod
     def add_args(parser):
         """Add optimizer-specific arguments to the parser."""
+        # fmt: off
         parser.add_argument('--adam-betas', default='(0.9, 0.999)', metavar='B',
                             help='betas for Adam optimizer')
         parser.add_argument('--adam-eps', type=float, default=1e-8, metavar='D',
                             help='epsilon for Adam optimizer')
+        # fmt: on
 
     @property
     def optimizer_config(self):

fairseq/optim/lr_scheduler/cosine_lr_scheduler.py

@@ -63,6 +63,7 @@ class CosineSchedule(FairseqLRScheduler):
     @staticmethod
     def add_args(parser):
         """Add arguments to the parser for this LR scheduler."""
+        # fmt: off
         parser.add_argument('--warmup-updates', default=0, type=int, metavar='N',
                             help='warmup the learning rate linearly for the first N updates')
         parser.add_argument('--warmup-init-lr', default=-1, type=float, metavar='LR',
@@ -73,6 +74,7 @@ class CosineSchedule(FairseqLRScheduler):
                             help='factor to grow the length of each period')
         parser.add_argument('--lr-period-updates', default=5000, type=float, metavar='LR',
                             help='initial number of updates per period')
+        # fmt: on
 
     def step(self, epoch, val_loss=None):
         """Update the learning rate at the end of the given epoch."""
@@ -102,4 +104,4 @@ class CosineSchedule(FairseqLRScheduler):
             self.lr = min_lr + 0.5 * (max_lr - min_lr) * (1 + math.cos(math.pi * t_curr / t_i))
 
         self.optimizer.set_lr(self.lr)
-        return self.lr
+        return self.lr
\ No newline at end of file

fairseq/optim/lr_scheduler/fixed_schedule.py

@@ -27,10 +27,12 @@ class FixedSchedule(FairseqLRScheduler):
     @staticmethod
     def add_args(parser):
         """Add arguments to the parser for this LR scheduler."""
+        # fmt: off
         parser.add_argument('--force-anneal', '--fa', type=int, metavar='N',
                             help='force annealing at specified epoch')
         parser.add_argument('--warmup-updates', default=0, type=int, metavar='N',
                             help='warmup the learning rate linearly for the first N updates')
+        # fmt: on
 
     def get_next_lr(self, epoch):
         lrs = self.args.lr

fairseq/optim/lr_scheduler/inverse_square_root_schedule.py

@@ -55,10 +55,12 @@ class InverseSquareRootSchedule(FairseqLRScheduler):
     @staticmethod
     def add_args(parser):
         """Add arguments to the parser for this LR scheduler."""
+        # fmt: off
         parser.add_argument('--warmup-updates', default=4000, type=int, metavar='N',
                             help='warmup the learning rate linearly for the first N updates')
         parser.add_argument('--warmup-init-lr', default=-1, type=float, metavar='LR',
                             help='initial learning rate during warmup phase; default is args.lr')
+        # fmt: on
 
     def step(self, epoch, val_loss=None):
         """Update the learning rate at the end of the given epoch."""

fairseq/optim/lr_scheduler/triangular_lr_scheduler.py

@@ -42,12 +42,14 @@ class TriangularSchedule(FairseqLRScheduler):
     @staticmethod
     def add_args(parser):
         """Add arguments to the parser for this LR scheduler."""
+        # fmt: off
         parser.add_argument('--max-lr', required=True, type=float, metavar='LR',
                             help='max learning rate, must be more than args.lr')
         parser.add_argument('--lr-period-updates', default=5000, type=float, metavar='LR',
                             help='initial number of updates per period (cycle length)')
         parser.add_argument('--shrink-min', action='store_true',
                             help='if set, also shrinks min lr')
+        # fmt: on
 
     def step(self, epoch, val_loss=None):
         """Update the learning rate at the end of the given epoch."""

fairseq/options.py

@@ -120,6 +120,7 @@ def parse_args_and_arch(parser, input_args=None, parse_known=False):
 
 def get_parser(desc, default_task='translation'):
     parser = argparse.ArgumentParser()
+    # fmt: off
     parser.add_argument('--no-progress-bar', action='store_true', help='disable progress bar')
     parser.add_argument('--log-interval', type=int, default=1000, metavar='N',
                         help='log progress every N batches (when progress bar is disabled)')
@@ -134,17 +135,16 @@ def get_parser(desc, default_task='translation'):
                         help='number of updates before increasing loss scale')
 
     # Task definitions can be found under fairseq/tasks/
-    parser.add_argument(
-        '--task', metavar='TASK', default=default_task,
-        choices=TASK_REGISTRY.keys(),
-        help='task',
-    )
-
+    parser.add_argument('--task', metavar='TASK', default=default_task,
+                        choices=TASK_REGISTRY.keys(),
+                        help='task')
+    # fmt: on
     return parser
 
 
 def add_dataset_args(parser, train=False, gen=False):
     group = parser.add_argument_group('Dataset and data loading')
+    # fmt: off
     group.add_argument('--skip-invalid-size-inputs-valid-test', action='store_true',
                        help='ignore too long or too short lines in valid and test set')
     group.add_argument('--max-tokens', type=int, metavar='N',
@@ -168,11 +168,13 @@ def add_dataset_args(parser, train=False, gen=False):
                            help='shard generation over N shards')
         group.add_argument('--shard-id', default=0, type=int, metavar='ID',
                            help='id of the shard to generate (id < num_shards)')
+    # fmt: on
     return group
 
 
 def add_distributed_training_args(parser):
     group = parser.add_argument_group('Distributed training')
+    # fmt: off
     group.add_argument('--distributed-world-size', type=int, metavar='N',
                        default=torch.cuda.device_count(),
                        help='total number of GPUs across all nodes (default: all visible GPUs)')
@@ -196,11 +198,13 @@ def add_distributed_training_args(parser):
                        help='Don\'t shuffle batches between GPUs, this reduces overall '
                             'randomness and may affect precision but avoids the cost of'
                             're-reading the data')
+    # fmt: on
     return group
 
 
 def add_optimization_args(parser):
     group = parser.add_argument_group('Optimization')
+    # fmt: off
     group.add_argument('--max-epoch', '--me', default=0, type=int, metavar='N',
                        help='force stop training at specified epoch')
     group.add_argument('--max-update', '--mu', default=0, type=int, metavar='N',
@@ -235,12 +239,13 @@ def add_optimization_args(parser):
                        help='minimum learning rate')
     group.add_argument('--min-loss-scale', default=1e-4, type=float, metavar='D',
                        help='minimum loss scale (for FP16 training)')
-
+    # fmt: on
     return group
 
 
 def add_checkpoint_args(parser):
     group = parser.add_argument_group('Checkpointing')
+    # fmt: off
     group.add_argument('--save-dir', metavar='DIR', default='checkpoints',
                        help='path to save checkpoints')
     group.add_argument('--restore-file', default='checkpoint_last.pt',
@@ -263,10 +268,12 @@ def add_checkpoint_args(parser):
                        help='only store last and best checkpoints')
     group.add_argument('--validate-interval', type=int, default=1, metavar='N',
                        help='validate every N epochs')
+    # fmt: on
     return group
 
 
 def add_common_eval_args(group):
+    # fmt: off
     group.add_argument('--path', metavar='FILE',
                        help='path(s) to model file(s), colon separated')
     group.add_argument('--remove-bpe', nargs='?', const='@@ ', default=None,
@@ -276,20 +283,24 @@ def add_common_eval_args(group):
                        help='only print final scores')
     group.add_argument('--model-overrides', default="{}", type=str, metavar='DICT',
                        help='a dictionary used to override model args at generation that were used during model training')
+    # fmt: on
 
 
 def add_eval_lm_args(parser):
     group = parser.add_argument_group('LM Evaluation')
     add_common_eval_args(group)
+    # fmt: off
     group.add_argument('--output-word-probs', action='store_true',
                        help='if set, outputs words and their predicted log probabilities to standard output')
     group.add_argument('--output-word-stats', action='store_true',
                        help='if set, outputs word statistics such as word count, average probability, etc')
+    # fmt: on
 
 
 def add_generation_args(parser):
     group = parser.add_argument_group('Generation')
     add_common_eval_args(group)
+    # fmt: off
     group.add_argument('--beam', default=5, type=int, metavar='N',
                        help='beam size')
     group.add_argument('--nbest', default=1, type=int, metavar='N',
@@ -332,17 +343,21 @@ def add_generation_args(parser):
                        help='strength of diversity penalty for Diverse Beam Search')
     group.add_argument('--print-alignment', action='store_true',
                        help='if set, uses attention feedback to compute and print alignment to source tokens')
+    # fmt: on
     return group
 
 
 def add_interactive_args(parser):
     group = parser.add_argument_group('Interactive')
+    # fmt: off
     group.add_argument('--buffer-size', default=0, type=int, metavar='N',
                        help='read this many sentences into a buffer before processing them')
+    # fmt: on
 
 
 def add_model_args(parser):
     group = parser.add_argument_group('Model configuration')
+    # fmt: off
 
     # Model definitions can be found under fairseq/models/
     #
@@ -351,17 +366,13 @@ def add_model_args(parser):
     # 1) model defaults (lowest priority)
     # 2) --arch argument
     # 3) --encoder/decoder-* arguments (highest priority)
-    group.add_argument(
-        '--arch', '-a', default='fconv', metavar='ARCH', required=True,
-        choices=ARCH_MODEL_REGISTRY.keys(),
-        help='Model Architecture',
-    )
+    group.add_argument('--arch', '-a', default='fconv', metavar='ARCH', required=True,
+                       choices=ARCH_MODEL_REGISTRY.keys(),
+                       help='Model Architecture')
 
     # Criterion definitions can be found under fairseq/criterions/
-    group.add_argument(
-        '--criterion', default='cross_entropy', metavar='CRIT',
-        choices=CRITERION_REGISTRY.keys(),
-        help='Training Criterion',
-    )
-
+    group.add_argument('--criterion', default='cross_entropy', metavar='CRIT',
+                       choices=CRITERION_REGISTRY.keys(),
+                       help='Training Criterion')
+    # fmt: on
     return group

fairseq/tasks/__init__.py

@@ -65,10 +65,10 @@ for file in os.listdir(os.path.dirname(__file__)):
         if task_name in TASK_REGISTRY:
             parser = argparse.ArgumentParser(add_help=False)
             group_task = parser.add_argument_group('Task name')
-            group_task.add_argument(
-                '--task', metavar=task_name,
-                help='Enable this task with: ``--task=' + task_name + '``'
-            )
+            # fmt: off
+            group_task.add_argument('--task', metavar=task_name,
+                                    help='Enable this task with: ``--task=' + task_name + '``')
+            # fmt: on
             group_args = parser.add_argument_group('Additional command-line arguments')
             TASK_REGISTRY[task_name].add_args(group_args)
             globals()[task_name + '_parser'] = parser

fairseq/tasks/language_modeling.py

@@ -52,6 +52,7 @@ class LanguageModelingTask(FairseqTask):
     @staticmethod
     def add_args(parser):
         """Add task-specific arguments to the parser."""
+        # fmt: off
         parser.add_argument('data', help='path to data directory')
         parser.add_argument('--sample-break-mode',
                             choices=['none', 'complete', 'eos'],
@@ -71,6 +72,7 @@ class LanguageModelingTask(FairseqTask):
                             help='include future target')
         parser.add_argument('--past-target', action='store_true',
                             help='include past target')
+        # fmt: on
 
     def __init__(self, args, dictionary, output_dictionary, targets=None):
         super().__init__(args)

fairseq/tasks/multilingual_translation.py

@@ -47,6 +47,7 @@ class MultilingualTranslationTask(FairseqTask):
     @staticmethod
     def add_args(parser):
         """Add task-specific arguments to the parser."""
+        # fmt: off
         parser.add_argument('data', metavar='DIR', help='path to data directory')
         parser.add_argument('--lang-pairs', default=None, metavar='PAIRS',
                             help='comma-separated list of language pairs (in training order): en-de,en-fr,de-fr')
@@ -64,6 +65,7 @@ class MultilingualTranslationTask(FairseqTask):
                             help='max number of tokens in the source sequence')
         parser.add_argument('--max-target-positions', default=1024, type=int, metavar='N',
                             help='max number of tokens in the target sequence')
+        # fmt: on
 
     def __init__(self, args, dicts, training):
         super().__init__(args)

fairseq/tasks/translation.py

@@ -43,6 +43,7 @@ class TranslationTask(FairseqTask):
     @staticmethod
     def add_args(parser):
         """Add task-specific arguments to the parser."""
+        # fmt: off
         parser.add_argument('data', nargs='+', help='path(s) to data directorie(s)')
         parser.add_argument('-s', '--source-lang', default=None, metavar='SRC',
                             help='source language')
@@ -60,6 +61,7 @@ class TranslationTask(FairseqTask):
                             help='max number of tokens in the target sequence')
         parser.add_argument('--upsample-primary', default=1, type=int,
                             help='amount to upsample primary dataset')
+        # fmt: on
 
     def __init__(self, args, src_dict, tgt_dict):
         super().__init__(args)

preprocess.py

@@ -23,89 +23,45 @@ from multiprocessing import Pool, Manager, Process
 
 def get_parser():
     parser = argparse.ArgumentParser()
-    parser.add_argument(
-        "-s", "--source-lang", default=None, metavar="SRC", help="source language"
-    )
-    parser.add_argument(
-        "-t", "--target-lang", default=None, metavar="TARGET", help="target language"
-    )
-    parser.add_argument(
-        "--trainpref", metavar="FP", default=None, help="train file prefix"
-    )
-    parser.add_argument(
-        "--validpref",
-        metavar="FP",
-        default=None,
-        help="comma separated, valid file prefixes",
-    )
-    parser.add_argument(
-        "--testpref",
-        metavar="FP",
-        default=None,
-        help="comma separated, test file prefixes",
-    )
-    parser.add_argument(
-        "--destdir", metavar="DIR", default="data-bin", help="destination dir"
-    )
-    parser.add_argument(
-        "--thresholdtgt",
-        metavar="N",
-        default=0,
-        type=int,
-        help="map words appearing less than threshold times to unknown",
-    )
-    parser.add_argument(
-        "--thresholdsrc",
-        metavar="N",
-        default=0,
-        type=int,
-        help="map words appearing less than threshold times to unknown",
-    )
-    parser.add_argument("--tgtdict", metavar="FP", help="reuse given target dictionary")
-    parser.add_argument("--srcdict", metavar="FP", help="reuse given source dictionary")
-    parser.add_argument(
-        "--nwordstgt",
-        metavar="N",
-        default=-1,
-        type=int,
-        help="number of target words to retain",
-    )
-    parser.add_argument(
-        "--nwordssrc",
-        metavar="N",
-        default=-1,
-        type=int,
-        help="number of source words to retain",
-    )
-    parser.add_argument(
-        "--alignfile",
-        metavar="ALIGN",
-        default=None,
-        help="an alignment file (optional)",
-    )
-    parser.add_argument(
-        "--output-format",
-        metavar="FORMAT",
-        default="binary",
-        choices=["binary", "raw"],
-        help="output format (optional)",
-    )
-    parser.add_argument(
-        "--joined-dictionary", action="store_true", help="Generate joined dictionary"
-    )
-    parser.add_argument(
-        "--only-source", action="store_true", help="Only process the source language"
-    )
-    parser.add_argument(
-        "--padding-factor",
-        metavar="N",
-        default=8,
-        type=int,
-        help="Pad dictionary size to be multiple of N",
-    )
-    parser.add_argument(
-        "--workers", metavar="N", default=1, type=int, help="number of parallel workers"
-    )
+    # fmt: off
+    parser.add_argument("-s", "--source-lang", default=None, metavar="SRC",
+                        help="source language")
+    parser.add_argument("-t", "--target-lang", default=None, metavar="TARGET",
+                        help="target language")
+    parser.add_argument("--trainpref", metavar="FP", default=None,
+                        help="train file prefix")
+    parser.add_argument("--validpref", metavar="FP", default=None,
+                        help="comma separated, valid file prefixes")
+    parser.add_argument("--testpref", metavar="FP", default=None,
+                        help="comma separated, test file prefixes")
+    parser.add_argument("--destdir", metavar="DIR", default="data-bin",
+                        help="destination dir")
+    parser.add_argument("--thresholdtgt", metavar="N", default=0, type=int,
+                        help="map words appearing less than threshold times to unknown")
+    parser.add_argument("--thresholdsrc", metavar="N", default=0, type=int,
+                        help="map words appearing less than threshold times to unknown")
+    parser.add_argument("--tgtdict", metavar="FP",
+                        help="reuse given target dictionary")
+    parser.add_argument("--srcdict", metavar="FP",
+                        help="reuse given source dictionary")
+    parser.add_argument("--nwordstgt", metavar="N", default=-1, type=int,
+                        help="number of target words to retain")
+    parser.add_argument("--nwordssrc", metavar="N", default=-1, type=int,
+                        help="number of source words to retain")
+    parser.add_argument("--alignfile", metavar="ALIGN", default=None,
+                        help="an alignment file (optional)")
+    parser.add_argument("--output-format", metavar="FORMAT", default="binary",
+                        choices=["binary", "raw"],
+                        help="output format (optional)")
+    parser.add_argument("--joined-dictionary", action="store_true",
+                        help="Generate joined dictionary")
+    parser.add_argument("--only-source", action="store_true",
+                        help="Only process the source language")
+    parser.add_argument("--padding-factor", metavar="N", default=8, type=int,
+                        help="Pad dictionary size to be multiple of N")
+    parser.add_argument("--workers", metavar="N", default=1, type=int,
+                        help="number of parallel workers")
+    # fmt: on
     return parser
 
 

score.py

@@ -19,12 +19,14 @@ from fairseq.data import dictionary
 
 def get_parser():
     parser = argparse.ArgumentParser(description='Command-line script for BLEU scoring.')
+    # fmt: off
     parser.add_argument('-s', '--sys', default='-', help='system output')
     parser.add_argument('-r', '--ref', required=True, help='references')
     parser.add_argument('-o', '--order', default=4, metavar='N',
                         type=int, help='consider ngrams up to this order')
     parser.add_argument('--ignore-case', action='store_true',
                         help='case-insensitive scoring')
+    # fmt: on
     return parser
 
 
@@ -44,7 +46,7 @@ def main():
         for line in fd.readlines():
             if args.ignore_case:
                 yield line.lower()
-            else:     
+            else:
                 yield line
 
     def score(fdsys):

scripts/average_checkpoints.py

@@ -86,33 +86,19 @@ def main():
         description='Tool to average the params of input checkpoints to '
                     'produce a new checkpoint',
     )
-
-    parser.add_argument(
-        '--inputs',
-        required=True,
-        nargs='+',
-        help='Input checkpoint file paths.',
-    )
-    parser.add_argument(
-        '--output',
-        required=True,
-        metavar='FILE',
-        help='Write the new checkpoint containing the averaged weights to this '
-             'path.',
-    )
+    # fmt: off
+    parser.add_argument('--inputs', required=True, nargs='+',
+                        help='Input checkpoint file paths.')
+    parser.add_argument('--output', required=True, metavar='FILE',
+                        help='Write the new checkpoint containing the averaged weights to this path.')
     num_group = parser.add_mutually_exclusive_group()
-    num_group.add_argument(
-        '--num-epoch-checkpoints',
-        type=int,
-        help='if set, will try to find checkpoints with names checkpoint_xx.pt in the path specified by input, '
-             'and average last this many of them.',
-    )
-    num_group.add_argument(
-        '--num-update-checkpoints',
-        type=int,
-        help='if set, will try to find checkpoints with names checkpoint_ee_xx.pt in the path specified by input, '
-             'and average last this many of them.',
-    )
+    num_group.add_argument('--num-epoch-checkpoints', type=int,
+                           help='if set, will try to find checkpoints with names checkpoint_xx.pt in the path specified by input, '
+                           'and average last this many of them.')
+    num_group.add_argument('--num-update-checkpoints', type=int,
+                           help='if set, will try to find checkpoints with names checkpoint_ee_xx.pt in the path specified by input, '
+                           'and average last this many of them.')
+    # fmt: on
     args = parser.parse_args()
     print(args)
 

scripts/build_sym_alignment.py

@@ -32,6 +32,7 @@ from itertools import zip_longest
 
 def main():
     parser = argparse.ArgumentParser(description='symmetric alignment builer')
+    # fmt: off
     parser.add_argument('--fast_align_dir',
                         help='path to fast_align build directory')
     parser.add_argument('--mosesdecoder_dir',
@@ -47,6 +48,7 @@ def main():
                              'in the target language')
     parser.add_argument('--output_dir',
                         help='output directory')
+    # fmt: on
     args = parser.parse_args()
 
     fast_align_bin = os.path.join(args.fast_align_dir, 'fast_align')