




import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase__    :							Optional[int]       		=     get_tests_dir('fixtures/spiece.model')

@require_sentencepiece
@require_tokenizers
class   UpperCAmelCase    (      a__ ,       unittest.TestCase ):
   __SCREAMING_SNAKE_CASE		:				Dict      					=       ErnieMTokenizer
   __SCREAMING_SNAKE_CASE		:				int      					=       False
   __SCREAMING_SNAKE_CASE		:				Any      					=       True
   __SCREAMING_SNAKE_CASE		:				Any      					=       False
   __SCREAMING_SNAKE_CASE		:				Tuple      					=       False






   def 			_a    (						self :							Any  )->      Tuple:
     super().setUp()

     # We have a SentencePiece fixture for testing
     _lowercase:			Any      =     ErnieMTokenizer(lowercase__    ,       unk_token='<unk>'    ,       pad_token='<pad>'  )
     tokenizer.save_pretrained(self.tmpdirname  )






   def 			_a    (						self :							Union[str, Any]    ,       UpperCamelCase_ :							List[Any]  )->      int:
     _lowercase:			Tuple      =     'this is a test'
     _lowercase:			Union[str, Any]      =     'this is a test'
     return input_text, output_text






   def 			_a    (						self :							Union[str, Any]  )->      List[str]:
     _lowercase:			Union[str, Any]      =     '<pad>'
     _lowercase:			Dict      =     0

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






   def 			_a    (						self :							Optional[int]  )->      Union[str, Any]:
     _lowercase:			Optional[int]      =     list(self.get_tokenizer().get_vocab().keys()  )

     self.assertEqual(vocab_keys[0]    ,       '<pad>'  )
     self.assertEqual(vocab_keys[1]    ,       '<unk>'  )
     self.assertEqual(vocab_keys[-1]    ,       '▁eloquent'  )
     self.assertEqual(len(lowercase__  )    ,       3_00_00  )






   def 			_a    (						self :							List[Any]  )->      Union[str, Any]:
     self.assertEqual(self.get_tokenizer().vocab_size    ,       3_00_00  )






   def 			_a    (						self :							List[Any]  )->      int:
     if not self.test_rust_tokenizer:
       return

     _lowercase:			Any      =     self.get_tokenizer()
     _lowercase:			str      =     self.get_rust_tokenizer()

     _lowercase:			Optional[Any]      =     'I was born in 92000, and this is falsé.'

     _lowercase:			List[Any]      =     tokenizer.tokenize(lowercase__  )
     _lowercase:			Union[str, Any]      =     rust_tokenizer.tokenize(lowercase__  )
     self.assertListEqual(lowercase__    ,       lowercase__  )

     _lowercase:			str      =     tokenizer.encode(lowercase__    ,       add_special_tokens=lowercase__  )
     _lowercase:			Dict      =     rust_tokenizer.encode(lowercase__    ,       add_special_tokens=lowercase__  )
     self.assertListEqual(lowercase__    ,       lowercase__  )

     _lowercase:			Tuple      =     self.get_rust_tokenizer()
     _lowercase:			Tuple      =     tokenizer.encode(lowercase__  )
     _lowercase:			str      =     rust_tokenizer.encode(lowercase__  )
     self.assertListEqual(lowercase__    ,       lowercase__  )






   def 			_a    (						self :							List[str]  )->      Any:
     _lowercase:			List[Any]      =     ErnieMTokenizer(lowercase__    ,       do_lower_case=lowercase__    ,       unk_token='<unk>'    ,       pad_token='<pad>'  )

     _lowercase:			Dict      =     tokenizer.tokenize('This is a test'  )
     self.assertListEqual(lowercase__    ,       ['▁this', '▁is', '▁a', '▁test']  )

     self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase__  )    ,       [48, 25, 21, 12_89]  )

     _lowercase:			Any      =     tokenizer.tokenize('I was born in 92000, and this is falsé.'  )
     # ErnieMTokenizer(paddlenlp implementation) outputs '9' instead of '_9' so to mimic that '_9' is changed to '9'
     self.assertListEqual(
         lowercase__    ,       ['▁i', '▁was', '▁born', '▁in', '9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', 'é', '.']  )
     _lowercase:			Any      =     tokenizer.convert_tokens_to_ids(lowercase__  )
     self.assertListEqual(lowercase__    ,       [31, 23, 3_86, 19, 5_18, 30_50, 15, 17, 48, 25, 82_56, 18, 1, 9]  )

     _lowercase:			Tuple      =     tokenizer.convert_ids_to_tokens(lowercase__  )
     self.assertListEqual(
         lowercase__    ,       ['▁i', '▁was', '▁born', '▁in', '9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '.']    ,       )






   def 			_a    (						self :							Dict  )->      Optional[Any]:
     _lowercase:			Optional[int]      =     ErnieMTokenizer(lowercase__    ,       unk_token='<unk>'    ,       pad_token='<pad>'  )

     _lowercase:			str      =     tokenizer.encode('sequence builders'  )
     _lowercase:			Optional[Any]      =     tokenizer.encode('multi-sequence build'  )

     _lowercase:			Optional[int]      =     tokenizer.build_inputs_with_special_tokens(lowercase__  )
     _lowercase:			Any      =     tokenizer.build_inputs_with_special_tokens(lowercase__    ,       lowercase__  )

     assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
     assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + [
         tokenizer.sep_token_id
     ] + text_a + [tokenizer.sep_token_id]






   @slow
   def 			_a    (						self :							Optional[int]  )->      List[Any]:
     # fmt: off
     _lowercase:			List[str]      =     {'input_ids': [[0, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 9, 3_04, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 5, 5, 5, 16, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 64_60, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 35_59, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [0, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 7, 5, 2, 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, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 5, 2, 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]]}
     # fmt: on

     self.tokenizer_integration_test_util(
         expected_encoding=lowercase__    ,       model_name='susnato/ernie-m-base_pytorch'    ,       sequences=[
             'Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides '
             'general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet...) for Natural '
             'Language Understanding (NLU) and Natural Language Generation (NLG) with over32+ pretrained '
             'models in100+ languages and deep interoperability between Jax, PyTorch and TensorFlow.',
             'BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly '
             'conditioning on both left and right context in all layers.',
             'The quick brown fox jumps over the lazy dog.',
         ]    ,       )






import io
import json
import subprocess


UpperCamelCase__       				=	[
    ['''en''', '''ru'''],
    ['''ru''', '''en'''],
    ['''en''', '''de'''],
    ['''de''', '''en'''],
]

UpperCamelCase__       				=	8






def 				UpperCAmelCase__  (							_A      ,      _A			):






  """simple docstring"""


  a_		    =  {}
  for src, tgt in pairs:
    a_		    =  f"{src}-{tgt}"
    a_		    =  f"sacrebleu -t wmt19 -l {pair} --echo src".split()
    a_		    =  subprocess.run(_A      ,      stdout=subprocess.PIPE			).stdout.decode('''utf-8'''			).splitlines()
    a_		    =  f"sacrebleu -t wmt19 -l {pair} --echo ref".split()
    a_		    =  subprocess.run(_A      ,      stdout=subprocess.PIPE			).stdout.decode('''utf-8'''			).splitlines()
    a_		    =  {'''src''': src_lines[:n_objs], '''tgt''': tgt_lines[:n_objs]}
  return text


UpperCamelCase__       				=	get_all_data(pairs, n_objs)
UpperCamelCase__       				=	'''./fsmt_val_data.json'''
with io.open(filename, '''w''', encoding='''utf-8''') as f:
  UpperCamelCase__       				=	json.dump(text, f, indent=2, ensure_ascii=False)
