Commit 82a9f923 authored by Myle Ott's avatar Myle Ott Committed by Facebook Github Bot
Browse files

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
parent 0693c351

fairseq/criterions/composite_loss.py

+2 −0
Original line number Diff line number Diff line
@@ -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

+2 −0
Original line number Diff line number Diff line
@@ -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

+2 −0
Original line number Diff line number Diff line
@@ -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

+2 −0
Original line number Diff line number Diff line
@@ -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

+2 −0
Original line number Diff line number Diff line
@@ -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):