
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
      from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


a_											=						get_tests_dir("fixtures/test_sentencepiece.model")

a_											=						{'target_lang': 'fi', 'source_lang': 'en'}
a_											=						'>>zh<<'
a_											=						'Helsinki-NLP/'

if is_torch_available():
      a_											=						'pt'
elif is_tf_available():
      a_											=						'tf'
else:
      a_											=						'jax'






@require_sentencepiece
class    UpperCAmelCase_				(	UpperCamelCase_    ,						unittest.TestCase					):
 UpperCAmelCase_		    =						MarianTokenizer
 UpperCAmelCase_		    =						False
 UpperCAmelCase_		    =						True





 def        snake_case__		(    self):
     super().setUp()
     snake_case_ :    Dict     			=						['''</s>''', '''<unk>''', '''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''', '''\u0120''', '''<pad>''']
     snake_case_ :    List[Any]     			=						dict(zip(UpperCamelCase__ ,       range(len(UpperCamelCase__))))
     snake_case_ :    Optional[int]     			=						Path(self.tmpdirname)
     save_json(UpperCamelCase__ ,       save_dir / VOCAB_FILES_NAMES["vocab"])
     save_json(UpperCamelCase__ ,       save_dir / VOCAB_FILES_NAMES["tokenizer_config_file"])
     if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
         copyfile(UpperCamelCase__ ,       save_dir / VOCAB_FILES_NAMES["source_spm"])
         copyfile(UpperCamelCase__ ,       save_dir / VOCAB_FILES_NAMES["target_spm"])

     snake_case_ :    int     			=						MarianTokenizer.from_pretrained(self.tmpdirname)
     tokenizer.save_pretrained(self.tmpdirname)





 def        snake_case__		(    self ,       **lowercase_):
     return MarianTokenizer.from_pretrained(self.tmpdirname ,       **UpperCamelCase__)





 def        snake_case__		(    self ,       lowercase_):
     return (
         "This is a test",
         "This is a test",
     )





 def        snake_case__		(    self):
     snake_case_ :    Optional[Any]     			=						'''</s>'''
     snake_case_ :    Any     			=						0

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





 def        snake_case__		(    self):
     snake_case_ :    Any     			=						list(self.get_tokenizer().get_vocab().keys())

     self.assertEqual(vocab_keys[0] ,       "</s>")
     self.assertEqual(vocab_keys[1] ,       "<unk>")
     self.assertEqual(vocab_keys[-1] ,       "<pad>")
     self.assertEqual(len(UpperCamelCase__) ,       9)





 def        snake_case__		(    self):
     self.assertEqual(self.get_tokenizer().vocab_size ,       9)





 def        snake_case__		(    self):
     snake_case_ :    int     			=						MarianTokenizer.from_pretrained(F'{ORG_NAME}opus-mt-en-de')
     snake_case_ :    List[str]     			=						en_de_tokenizer(["I am a small frog"] ,       return_tensors=UpperCamelCase__)
     self.assertIsInstance(UpperCamelCase__ ,       UpperCamelCase__)
     snake_case_ :    int     			=						[38, 1_21, 14, 6_97, 3_88_48, 0]
     self.assertListEqual(UpperCamelCase__ ,       batch.input_ids[0])

     snake_case_ :    Dict     			=						tempfile.mkdtemp()
     en_de_tokenizer.save_pretrained(UpperCamelCase__)
     snake_case_ :    str     			=						[x.name for x in Path(UpperCamelCase__).glob("*")]
     self.assertIn("source.spm" ,       UpperCamelCase__)
     MarianTokenizer.from_pretrained(UpperCamelCase__)





 def        snake_case__		(    self):
     snake_case_ :    Tuple     			=						self.get_tokenizer()

     snake_case_ :    Optional[Any]     			=						tok(
         ["I am a small frog" * 10_00, "I am a small frog"] ,       padding=UpperCamelCase__ ,       truncation=UpperCamelCase__ ,       return_tensors=UpperCamelCase__)
     self.assertIsInstance(UpperCamelCase__ ,       UpperCamelCase__)
     self.assertEqual(batch.input_ids.shape ,       (2, 5_12))





 def        snake_case__		(    self):
     snake_case_ :    Tuple     			=						self.get_tokenizer()
     snake_case_ :    int     			=						tok(["I am a tiny frog", "I am a small frog"] ,       padding=UpperCamelCase__ ,       return_tensors=UpperCamelCase__)
     self.assertIsInstance(UpperCamelCase__ ,       UpperCamelCase__)
     self.assertEqual(batch_smaller.input_ids.shape ,       (2, 10))





 @slow
 def        snake_case__		(    self):
     snake_case_ :    Any     			=						{'''input_ids''': [[4_34_95, 4_62, 20, 4_21_64, 13_69, 52, 4_64, 1_32, 17_03, 4_92, 13, 74_91, 3_89_99, 6, 8, 4_64, 1_32, 17_03, 4_92, 13, 46_69, 3_78_67, 13, 75_25, 27, 15_93, 9_88, 13, 3_39_72, 70_29, 6, 20, 82_51, 3_83, 2, 2_70, 58_66, 37_88, 2, 23_53, 82_51, 1_23_38, 2, 1_39_58, 3_87, 2, 36_29, 69_53, 1_88, 29_00, 2, 1_39_58, 80_11, 1_15_01, 23, 84_60, 40_73, 3_40_09, 20, 4_35, 1_14_39, 27, 8, 84_60, 40_73, 60_04, 20, 99_88, 3_75, 27, 33, 2_66, 19_45, 10_76, 13_50, 3_78_67, 32_88, 5, 5_77, 10_76, 43_74, 8, 50_82, 5, 2_64_53, 2_57, 5_56, 4_03, 2, 2_42, 1_32, 3_83, 3_16, 4_92, 8, 1_07_67, 6, 3_16, 3_04, 42_39, 3, 0], [1_48, 1_57_22, 19, 18_39, 12, 13_50, 13, 2_23_27, 50_82, 54_18, 4_75_67, 3_59_38, 59, 3_18, 1_95_52, 1_08, 21_83, 54, 1_49_76, 48_35, 32, 5_47, 11_14, 8, 3_15, 24_17, 5, 92, 1_90_88, 3, 0, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00], [36, 63_95, 1_25_70, 3_91_47, 1_15_97, 6, 2_66, 4, 4_54_05, 72_96, 3, 0, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00, 5_81_00]], '''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, 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, 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, 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, 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], [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, 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]]}  # noqa: E501
     # fmt: on

     self.tokenizer_integration_test_util(
         expected_encoding=UpperCamelCase__ ,       model_name="Helsinki-NLP/opus-mt-en-de" ,       revision="1a8c2263da11e68e50938f97e10cd57820bd504c" ,       decode_kwargs={"use_source_tokenizer": True} ,       )





 def        snake_case__		(    self):
     snake_case_ :    Optional[Any]     			=						MarianTokenizer.from_pretrained("hf-internal-testing/test-marian-two-vocabs")

     snake_case_ :    List[Any]     			=						'''Tämä on testi'''
     snake_case_ :    Dict     			=						'''This is a test'''

     snake_case_ :    List[Any]     			=						[76, 7, 20_47, 2]
     snake_case_ :    int     			=						[69, 12, 11, 9_40, 2]

     snake_case_ :    List[Any]     			=						tokenizer(UpperCamelCase__).input_ids
     self.assertListEqual(UpperCamelCase__ ,       UpperCamelCase__)

     snake_case_ :    Tuple     			=						tokenizer(text_target=UpperCamelCase__).input_ids
     self.assertListEqual(UpperCamelCase__ ,       UpperCamelCase__)

     snake_case_ :    Any     			=						tokenizer.decode(UpperCamelCase__ ,       skip_special_tokens=UpperCamelCase__)
     self.assertEqual(UpperCamelCase__ ,       UpperCamelCase__)






'''simple docstring'''
from __future__ import annotations

from cmath import sqrt

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    if a == 0:
        raise ValueError("Coefficient 'a' must not be zero."       )
    snake_case_ :    Union[str, Any]     			=						b * b - 4 * a * c

    snake_case_ :    List[str]     			=						(-b + sqrt(__SCREAMING_SNAKE_CASE       )) / (2 * a)
    snake_case_ :    int     			=						(-b - sqrt(__SCREAMING_SNAKE_CASE       )) / (2 * a)

    return (
        root_a.real if not root_a.imag else root_a,
        root_a.real if not root_a.imag else root_a,
    )

def 						UpperCamelCase_     (	):
    """simple docstring"""






    snake_case_			, snake_case_ :    str     			=						quadratic_roots(a=5,		b=6,		c=1       )
    print(f'The solutions are: {solutiona} and {solutiona}'       )


if __name__ == "__main__":
  main()




