Merge pull request #2538 from huggingface/py3_super

💄 super
This commit is contained in:
Thomas Wolf
2020-01-16 13:17:15 +01:00
committed by GitHub
75 changed files with 328 additions and 331 deletions

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@@ -30,7 +30,7 @@ class AlbertTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer_class = AlbertTokenizer
def setUp(self):
super(AlbertTokenizationTest, self).setUp()
super().setUp()
# We have a SentencePiece fixture for testing
tokenizer = AlbertTokenizer(SAMPLE_VOCAB)

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@@ -38,7 +38,7 @@ class BertTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
test_rust_tokenizer = True
def setUp(self):
super(BertTokenizationTest, self).setUp()
super().setUp()
vocab_tokens = [
"[UNK]",

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@@ -35,7 +35,7 @@ class BertJapaneseTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer_class = BertJapaneseTokenizer
def setUp(self):
super(BertJapaneseTokenizationTest, self).setUp()
super().setUp()
vocab_tokens = [
"[UNK]",
@@ -135,7 +135,7 @@ class BertJapaneseCharacterTokenizationTest(TokenizerTesterMixin, unittest.TestC
tokenizer_class = BertJapaneseTokenizer
def setUp(self):
super(BertJapaneseCharacterTokenizationTest, self).setUp()
super().setUp()
vocab_tokens = ["[UNK]", "[CLS]", "[SEP]", "", "", "", "", "", "", "", "", "", ""]

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@@ -27,7 +27,7 @@ class CTRLTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer_class = CTRLTokenizer
def setUp(self):
super(CTRLTokenizationTest, self).setUp()
super().setUp()
# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
vocab = ["adapt", "re@@", "a@@", "apt", "c@@", "t", "<unk>"]

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@@ -29,7 +29,7 @@ class GPT2TokenizationTest(TokenizerTesterMixin, unittest.TestCase):
test_rust_tokenizer = True
def setUp(self):
super(GPT2TokenizationTest, self).setUp()
super().setUp()
# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
vocab = [

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@@ -28,7 +28,7 @@ class OpenAIGPTTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer_class = OpenAIGPTTokenizer
def setUp(self):
super(OpenAIGPTTokenizationTest, self).setUp()
super().setUp()
# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
vocab = [

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@@ -28,7 +28,7 @@ class RobertaTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer_class = RobertaTokenizer
def setUp(self):
super(RobertaTokenizationTest, self).setUp()
super().setUp()
# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
vocab = [

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@@ -31,7 +31,7 @@ class T5TokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer_class = T5Tokenizer
def setUp(self):
super(T5TokenizationTest, self).setUp()
super().setUp()
# We have a SentencePiece fixture for testing
tokenizer = T5Tokenizer(SAMPLE_VOCAB)

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@@ -33,7 +33,7 @@ class TransfoXLTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer_class = TransfoXLTokenizer if is_torch_available() else None
def setUp(self):
super(TransfoXLTokenizationTest, self).setUp()
super().setUp()
vocab_tokens = [
"<unk>",

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@@ -29,7 +29,7 @@ class XLMTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer_class = XLMTokenizer
def setUp(self):
super(XLMTokenizationTest, self).setUp()
super().setUp()
# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
vocab = [

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@@ -31,7 +31,7 @@ class XLNetTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer_class = XLNetTokenizer
def setUp(self):
super(XLNetTokenizationTest, self).setUp()
super().setUp()
# We have a SentencePiece fixture for testing
tokenizer = XLNetTokenizer(SAMPLE_VOCAB, keep_accents=True)