



"""simple docstring"""
import unittest

from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


A:     str										=	get_tests_dir("fixtures/test_sentencepiece_with_bytefallback.model")



@require_sentencepiece
@require_tokenizers
class    SCREAMING_SNAKE_CASE__						(      UpperCAmelCase__   ,    unittest.TestCase				):
   __lowerCAmelCase						:     Dict		=		GPTSwaTokenizer
   __lowerCAmelCase						:     List[str]		=		False
   __lowerCAmelCase						:     Any		=		True
   __lowerCAmelCase						:     Tuple		=		False

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   str:





     '''simple docstring'''




     super().setUp()

     # We have a SentencePiece fixture for testing
     UpperCAmelCase			:      int			=			GPTSwaTokenizer(_SCREAMING_SNAKE_CASE   ,  eos_token="""<unk>"""   ,  bos_token="""<unk>"""   ,  pad_token="""<unk>"""		)

     tokenizer.save_pretrained(self.tmpdirname		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE		)						->   int:





     '''simple docstring'''




     UpperCAmelCase			:      str			=			"""This is a test"""
     UpperCAmelCase			:      int			=			"""This is a test"""
     return input_text, output_text

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





     '''simple docstring'''




     UpperCAmelCase			:      Dict			=			"""<s>"""
     UpperCAmelCase			:      Optional[Any]			=			1

     self.assertEqual(self.get_tokenizer()._convert_token_to_id(_SCREAMING_SNAKE_CASE		)   ,  _SCREAMING_SNAKE_CASE		)
     self.assertEqual(self.get_tokenizer()._convert_id_to_token(_SCREAMING_SNAKE_CASE		)   ,  _SCREAMING_SNAKE_CASE		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Dict:





     '''simple docstring'''




     UpperCAmelCase			:      Optional[int]			=			list(self.get_tokenizer().get_vocab().keys()		)

     self.assertEqual(vocab_keys[0]   ,  """<unk>"""		)
     self.assertEqual(vocab_keys[1]   ,  """<s>"""		)
     self.assertEqual(vocab_keys[-1]   ,  """j"""		)
     self.assertEqual(len(_SCREAMING_SNAKE_CASE		)   ,  2000		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   List[Any]:





     '''simple docstring'''




     self.assertEqual(self.get_tokenizer().vocab_size   ,  2000		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





     '''simple docstring'''




     UpperCAmelCase			:      Dict			=			GPTSwaTokenizer(_SCREAMING_SNAKE_CASE		)

     UpperCAmelCase			:      Tuple			=			tokenizer.tokenize("""This is a test"""		)
     self.assertListEqual(_SCREAMING_SNAKE_CASE   ,  ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]		)

     self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE		)   ,  [465, 287, 265, 631, 842]		)

     UpperCAmelCase			:      List[Any]			=			tokenizer.tokenize("""I was born in 92000, and this is falsé."""		)
     # fmt: off
     self.assertListEqual(
         _SCREAMING_SNAKE_CASE   ,  ["""▁I""", """▁was""", """▁bor""", """n""", """▁in""", """▁""", """<0x39>""", """2""", """0""", """0""", """0""", """,""", """▁and""", """▁this""", """▁is""", """▁f""", """al""", """s""", """<0xC3>""", """<0xA9>""", """."""]   ,  )
     # fmt: on

     UpperCAmelCase			:      List[str]			=			tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE		)
     self.assertListEqual(
         _SCREAMING_SNAKE_CASE   ,  [262, 272, 1525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260]   ,  )

     UpperCAmelCase			:      int			=			tokenizer.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE		)
     # fmt: off
     self.assertListEqual(
         _SCREAMING_SNAKE_CASE   ,  ["""▁I""", """▁was""", """▁bor""", """n""", """▁in""", """▁""", """<0x39>""", """2""", """0""", """0""", """0""", """,""", """▁and""", """▁this""", """▁is""", """▁f""", """al""", """s""", """<0xC3>""", """<0xA9>""", """."""]		)
     # fmt: on

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Optional[Any]:





     '''simple docstring'''




     UpperCAmelCase			:      List[str]			=			GPTSwaTokenizer(_SCREAMING_SNAKE_CASE		)
     UpperCAmelCase			:      List[str]			=			["""This is a test""", """I was born in 92000, and this is falsé."""]
     UpperCAmelCase			:      Union[str, Any]			=			[
         [465, 287, 265, 631, 842],
         [262, 272, 1525, 286, 271, 268, 60, 916, 633, 633, 633, 259, 266, 301, 287, 384, 367, 263, 198, 172, 260],
     ]

     # Test that encode_fast returns the same as tokenize + convert_tokens_to_ids
     for text, expected_ids in zip(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		):
       self.assertListEqual(tokenizer.encode_fast(_SCREAMING_SNAKE_CASE		)   ,  _SCREAMING_SNAKE_CASE		)

     # Test that decode_fast returns the input text
     for text, token_ids in zip(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		):
       self.assertEqual(tokenizer.decode_fast(_SCREAMING_SNAKE_CASE		)   ,  _SCREAMING_SNAKE_CASE		)




   @slow
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Tuple:





     '''simple docstring'''




     UpperCAmelCase			:      Any			=			[
         """<|python|>def fibonacci(n)\n    if n < 0:\n        print('Incorrect input')""",
         """Hey there, how are you doing this fine day?""",
         """This is a text with a trailing spaces followed by a dot     .""",
         """Häj sväjs lillebrör! =)""",
         """Det är inget fel på Mr. Cool""",
     ]

     # fmt: off
     UpperCAmelCase			:      Tuple			=			{"""input_ids""": [[63423, 5, 6811, 14954, 282, 816, 3821, 63466, 63425, 63462, 18, 63978, 678, 301, 1320, 63423, 63455, 63458, 18, 63982, 4246, 3940, 1901, 47789, 5547, 18994], [19630, 1100, 63446, 1342, 633, 544, 4488, 593, 5102, 2416, 63495, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1652, 428, 268, 1936, 515, 268, 58593, 22413, 9106, 546, 268, 33213, 63979, 698, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [55130, 63450, 924, 63449, 2249, 4062, 1558, 318, 63504, 21498, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [509, 377, 2827, 2559, 332, 6575, 63443, 26801, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """token_type_ids""": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}
     # fmt: on
     self.tokenizer_integration_test_util(
         expected_encoding=_SCREAMING_SNAKE_CASE   ,  model_name="""AI-Sweden/gpt-sw3-126m"""   ,  sequences=_SCREAMING_SNAKE_CASE   ,  )





"""simple docstring"""
import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict

@pytest.mark.parametrize(
    """files"""    ,	[
        ["""full:README.md""", """dataset_infos.json"""],
        ["""empty:README.md""", """dataset_infos.json"""],
        ["""dataset_infos.json"""],
        ["""full:README.md"""],
    ]    ,	)
def    _snake_case		(		UpperCamelCase		:	str    ,	UpperCamelCase		:	Optional[Any]		):
 UpperCAmelCase			:      List[Any]			=			tmp_path_factory.mktemp("""dset_infos_dir"""		)
 if "full:README.md" in files:
  with open(dataset_infos_dir / """README.md"""    ,	"""w"""		) as f:
   f.write("""---\ndataset_info:\n  dataset_size: 42\n---"""		)
 if "empty:README.md" in files:
  with open(dataset_infos_dir / """README.md"""    ,	"""w"""		) as f:
   f.write(""""""		)
    # we want to support dataset_infos.json for backward compatibility
 if "dataset_infos.json" in files:
  with open(dataset_infos_dir / """dataset_infos.json"""    ,	"""w"""		) as f:
   f.write("""{\"default\": {\"dataset_size\": 42}}"""		)
 UpperCAmelCase			:      str			=			DatasetInfosDict.from_directory(UpperCamelCase		)
 assert dataset_infos
 assert dataset_infos["default"].dataset_size == 42

@pytest.mark.parametrize(
    """dataset_info"""    ,	[
        DatasetInfo(),
        DatasetInfo(
            description="""foo"""    ,	features=Features({"""a""": Value("""int32"""		)}		)    ,	builder_name="""builder"""    ,	config_name="""config"""    ,	version="""1.0.0"""    ,	splits=[{"""name""": """train"""}]    ,	download_size=42    ,	),
    ]    ,	)
def    _snake_case		(		UpperCamelCase		:	str    ,	UpperCamelCase		:	DatasetInfo		):
 UpperCAmelCase			:      List[Any]			=			str(UpperCamelCase		)
 dataset_info.write_to_directory(UpperCamelCase		)
 UpperCAmelCase			:      List[str]			=			DatasetInfo.from_directory(UpperCamelCase		)
 assert dataset_info == reloaded
 assert os.path.exists(os.path.join(UpperCamelCase    ,	"""dataset_info.json"""		)		)

def    _snake_case		(		):
 UpperCAmelCase			:      List[str]			=			DatasetInfo(
     description="""foo"""    ,	citation="""bar"""    ,	homepage="""https://foo.bar"""    ,	license="""CC0"""    ,	features=Features({"""a""": Value("""int32"""		)}		)    ,	post_processed={}    ,	supervised_keys=()    ,	task_templates=[]    ,	builder_name="""builder"""    ,	config_name="""config"""    ,	version="""1.0.0"""    ,	splits=[{"""name""": """train""", """num_examples""": 42}]    ,	download_checksums={}    ,	download_size=1337    ,	post_processing_size=442    ,	dataset_size=1234    ,	size_in_bytes=1337 + 442 + 1234    ,	)
 UpperCAmelCase			:      str			=			dataset_info._to_yaml_dict()
 assert sorted(UpperCamelCase		) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML		)
 for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
  assert key in dataset_info_yaml_dict
  assert isinstance(dataset_info_yaml_dict[key]    ,	(list, dict, int, str)		)
 UpperCAmelCase			:      Union[str, Any]			=			yaml.safe_dump(UpperCamelCase		)
 UpperCAmelCase			:      List[str]			=			yaml.safe_load(UpperCamelCase		)
 assert dataset_info_yaml_dict == reloaded

def    _snake_case		(		):
 UpperCAmelCase			:      List[str]			=			DatasetInfo()
 UpperCAmelCase			:      Union[str, Any]			=			dataset_info._to_yaml_dict()
 assert dataset_info_yaml_dict == {}

@pytest.mark.parametrize(
    """dataset_infos_dict"""    ,	[
        DatasetInfosDict(),
        DatasetInfosDict({"""default""": DatasetInfo()}		),
        DatasetInfosDict({"""my_config_name""": DatasetInfo()}		),
        DatasetInfosDict(
            {
                """default""": DatasetInfo(
                    description="""foo"""    ,	features=Features({"""a""": Value("""int32"""		)}		)    ,	builder_name="""builder"""    ,	config_name="""config"""    ,	version="""1.0.0"""    ,	splits=[{"""name""": """train"""}]    ,	download_size=42    ,	)
            }		),
        DatasetInfosDict(
            {
                """v1""": DatasetInfo(dataset_size=42		),
                """v2""": DatasetInfo(dataset_size=1337		),
            }		),
    ]    ,	)
def    _snake_case		(		UpperCamelCase		:	Optional[int]    ,	UpperCamelCase		:	DatasetInfosDict		):
 UpperCAmelCase			:      List[str]			=			str(UpperCamelCase		)
 dataset_infos_dict.write_to_directory(UpperCamelCase		)
 UpperCAmelCase			:      List[Any]			=			DatasetInfosDict.from_directory(UpperCamelCase		)

 # the config_name of the dataset_infos_dict take over the attribute
 for config_name, dataset_info in dataset_infos_dict.items():
  UpperCAmelCase			:      Union[str, Any]			=			config_name
  # the yaml representation doesn't include fields like description or citation
  # so we just test that we can recover what we can from the yaml
  UpperCAmelCase			:      Optional[Any]			=			DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()		)
 assert dataset_infos_dict == reloaded

 if dataset_infos_dict:
  assert os.path.exists(os.path.join(UpperCamelCase    ,	"""README.md"""		)		)
