




import os
import unittest

from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class 		lowercase							(     UpperCamelCase__,unittest.TestCase	):
     _a											=		FunnelTokenizer
     _a											=		FunnelTokenizerFast
     _a											=		True
     _a											=		True

     def       a__			(						self       )		->							List[Any]:
           super().setUp()

           _A							:  Union[str, Any]    =		[
               """<unk>""",
               """<cls>""",
               """<sep>""",
               """want""",
               """##want""",
               """##ed""",
               """wa""",
               """un""",
               """runn""",
               """##ing""",
               """,""",
               """low""",
               """lowest""",
           ]
           _A							:  Optional[int]    =		os.path.join(self.tmpdirname	,  VOCAB_FILES_NAMES["""vocab_file"""]       )
           with open(self.vocab_file	,  """w"""	,  encoding="""utf-8"""       ) as vocab_writer:
                 vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]       )       )

     def       a__			(						self	,  **_a       )		->							Dict:
           return FunnelTokenizer.from_pretrained(self.tmpdirname	,  **_a       )

     def       a__			(						self	,  **_a       )		->							Optional[Any]:
           return FunnelTokenizerFast.from_pretrained(self.tmpdirname	,  **_a       )

     def       a__			(						self	,  _a       )		->							Any:
           _A							:  int    =		"""UNwant\u00E9d,running"""
           _A							:  Union[str, Any]    =		"""unwanted, running"""
           return input_text, output_text

     def       a__			(						self       )		->							Optional[Any]:
           _A							:  List[str]    =		self.tokenizer_class(self.vocab_file       )

           _A							:  int    =		tokenizer.tokenize("""UNwant\u00E9d,running"""       )
           self.assertListEqual(_a	,  ["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]       )
           self.assertListEqual(tokenizer.convert_tokens_to_ids(_a       )	,  [7, 4, 5, 10, 8, 9]       )



     def       a__			(						self       )		->							Union[str, Any]:
           _A							:  Any    =		self.get_tokenizers(do_lower_case=_a       )
           for tokenizer in tokenizers:
                 _A							:  str    =		tokenizer("""UNwant\u00E9d,running"""       )
                 _A							:  List[Any]    =		len(inputs["""input_ids"""]       ) - 1
                 self.assertListEqual(inputs["""token_type_ids"""]	,  [2] + [0] * sentence_len       )

                 _A							:  Tuple    =		tokenizer("""UNwant\u00E9d,running"""	,  """UNwant\u00E9d,running"""       )
                 self.assertListEqual(inputs["""token_type_ids"""]	,  [2] + [0] * sentence_len + [1] * sentence_len       )










from unittest import TestCase

from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset







class 		lowercase							(     UpperCamelCase__	):

     def       a__			(						self       )		->							Optional[int]:
           return [
               {"col_1": 3, "col_2": "a"},
               {"col_1": 2, "col_2": "b"},
               {"col_1": 1, "col_2": "c"},
               {"col_1": 0, "col_2": "d"},
           ]

     def       a__			(						self       )		->							Optional[int]:
           _A							:  Union[str, Any]    =		{"""col_1""": [3, 2, 1, 0], """col_2""": ["""a""", """b""", """c""", """d"""]}
           return Dataset.from_dict(_a       )

     def       a__			(						self       )		->							Any:
           _A							:  str    =		self._create_example_records()
           _A							:  List[Any]    =		Dataset.from_list(_a       )
           self.assertListEqual(dset.column_names	,  ["""col_1""", """col_2"""]       )
           for i, r in enumerate(_a       ):
                 self.assertDictEqual(_a	,  example_records[i]       )

     def       a__			(						self       )		->							List[str]:
           _A							:  Dict    =		self._create_example_records()
           _A							:  List[str]    =		Dataset.from_list(_a       )
           _A							:  str    =		Dataset.from_dict({k: [r[k] for r in example_records] for k in example_records[0]}       )
           self.assertEqual(dset.info	,  dset_from_dict.info       )

     def       a__			(						self       )		->							str:  # checks what happens with missing columns
           _A							:  List[str]    =		[{"""col_1""": 1}, {"""col_2""": """x"""}]
           _A							:  List[str]    =		Dataset.from_list(_a       )
           self.assertDictEqual(dset[0]	,  {"""col_1""": 1}       )
           self.assertDictEqual(dset[1]	,  {"""col_1""": None}       )  # NB: first record is used for columns

     def       a__			(						self       )		->							Dict:  # checks if the type can be inferred from the second record
           _A							:  List[Any]    =		[{"""col_1""": []}, {"""col_1""": [1, 2]}]
           _A							:  str    =		Dataset.from_list(_a       )
           self.assertEqual(dset.info.features["""col_1"""]	,  Sequence(Value("""int64"""       )       )       )



     def       a__			(						self       )		->							Dict:
           _A							:  List[str]    =		Dataset.from_list([]       )
           self.assertEqual(len(_a       )	,  0       )
           self.assertListEqual(dset.column_names	,  []       )

