Commit 0b05467d authored by Liezl Puzon's avatar Liezl Puzon Committed by Facebook Github Bot
Browse files

Black formatting in fairseq/test_noising (#341) 

Summary:
Pull Request resolved: https://github.com/pytorch/fairseq/pull/341

Use black formatting in test_noising.py

Reviewed By: xianxl

Differential Revision: D12810285

fbshipit-source-id: 5517dd5d2f086831f487d88acf6bc2fa18820297
parent 726a47dc

tests/test_noising.py

+7 −10
Original line number Diff line number Diff line
@@ -5,17 +5,17 @@ 
# the root directory of this source tree. An additional grant of patent rights

# can be found in the PATENTS file in the same directory.



import torch

import unittest



import tests.utils as test_utils

import torch

from fairseq import utils

from fairseq.data import (

    AppendEosDataset,

    Dictionary,

    LanguagePairDataset,

    data_utils,

    noising,

    LanguagePairDataset,

)
@@ -74,7 +74,7 @@ class TestDataNoising(unittest.TestCase): 
                (

                    "Expected eos (token id {eos}) at the end of sentence {i} but "

                    "got {other} instead"

                ).format(i=i, eos=eos, other=x[i][-1])

                ).format(i=i, eos=eos, other=x[i][-1]),

            )



    def assert_word_dropout_correct(self, x, x_noised, x_len, l_noised):
@@ -200,8 +200,8 @@ class TestDataNoising(unittest.TestCase): 
                x[x_len[i] - 1][i],

                eos,

                "Expected no eos (token id {eos}) at the end of sentence {i}.".format(

                    eos=eos, i=i,

                )

                    eos=eos, i=i

                ),

            )



    def test_word_dropout_without_eos(self):
@@ -273,10 +273,7 @@ class TestDataNoising(unittest.TestCase): 
        if use_append_eos_dataset:

            tgt = AppendEosDataset(src_dataset, src_dict.eos())

        language_pair_dataset = LanguagePairDataset(

            src=noising_dataset,

            tgt=tgt,

            src_sizes=None,

            src_dict=src_dict

            src=noising_dataset, tgt=tgt, src_sizes=None, src_dict=src_dict

        )



        dataloader = torch.utils.data.DataLoader(
@@ -361,5 +358,5 @@ class TestDataNoising(unittest.TestCase): 
        self.assertEqual(t1.ne(t2).long().sum(), 0)





if __name__ == '__main__':

if __name__ == "__main__":

    unittest.main()