


import json
import os
import unittest

from transformers.models.fsmt.tokenization_fsmt import VOCAB_FILES_NAMES, FSMTTokenizer
from transformers.testing_utils import slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


# using a different tiny model than the one used for default params defined in init to ensure proper testing
_A							     =       'stas/tiny-wmt19-en-ru'

class 			lowerCamelCase_					(    _SCREAMING_SNAKE_CASE   ,		unittest.TestCase    ):
							_lowerCamelCase				: int       =					FSMTTokenizer
							_lowerCamelCase				: List[Any]       =					False





							def   __magic_name__      (							self    ):
								super().setUp()

								# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
								a_     			=   [
								    """l""",
								    """o""",
								    """w""",
								    """e""",
								    """r""",
								    """s""",
								    """t""",
								    """i""",
								    """d""",
								    """n""",
								    """w</w>""",
								    """r</w>""",
								    """t</w>""",
								    """lo""",
								    """low""",
								    """er</w>""",
								    """low</w>""",
								    """lowest</w>""",
								    """newer</w>""",
								    """wider</w>""",
								    """<unk>""",
								]
								a_     			=   dict(zip(lowercase__			,       range(len(lowercase__    )    )    )    )
								a_     			=   ["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

								a_     			=   ["""en""", """ru"""]
								a_     			=   {
								    """langs""": self.langs,
								    """src_vocab_size""": 10,
								    """tgt_vocab_size""": 20,
								}

								a_     			=   os.path.join(self.tmpdirname			,       VOCAB_FILES_NAMES["""src_vocab_file"""]    )
								a_     			=   os.path.join(self.tmpdirname			,       VOCAB_FILES_NAMES["""tgt_vocab_file"""]    )
								a_     			=   os.path.join(self.tmpdirname			,       """tokenizer_config.json"""    )
								a_     			=   os.path.join(self.tmpdirname			,       VOCAB_FILES_NAMES["""merges_file"""]    )
								with open(self.src_vocab_file			,       """w"""    ) as fp:
									fp.write(json.dumps(lowercase__    )    )
								with open(self.tgt_vocab_file			,       """w"""    ) as fp:
									fp.write(json.dumps(lowercase__    )    )
								with open(self.merges_file			,       """w"""    ) as fp:
									fp.write("""\n""".join(lowercase__    )    )
								with open(lowercase__			,       """w"""    ) as fp:
									fp.write(json.dumps(lowercase__    )    )





							@cached_property
							def   __magic_name__      (							self    ):
								return FSMTTokenizer.from_pretrained("""facebook/wmt19-ru-en"""    )





							@cached_property
							def   __magic_name__      (							self    ):
								return FSMTTokenizer.from_pretrained("""facebook/wmt19-en-ru"""    )





							def   __magic_name__      (							self    ):
								a_     			=   FSMTTokenizer.from_pretrained(lowercase__    )
								self.assertListEqual([tokenizer.src_lang, tokenizer.tgt_lang]			,       ["""en""", """ru"""]    )
								self.assertEqual(tokenizer.src_vocab_size			,       21    )
								self.assertEqual(tokenizer.tgt_vocab_size			,       21    )





							def   __magic_name__      (							self    ):
								a_     			=   FSMTTokenizer(self.langs			,       self.src_vocab_file			,       self.tgt_vocab_file			,       self.merges_file    )

								a_     			=   """lower"""
								a_     			=   ["""low""", """er</w>"""]
								a_     			=   tokenizer.tokenize(lowercase__    )
								self.assertListEqual(lowercase__			,       lowercase__    )

								a_     			=   tokens + ["""<unk>"""]
								a_     			=   [14, 15, 20]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase__    )			,       lowercase__    )





							@slow
							def   __magic_name__      (							self    ):
								a_     			=   self.tokenizer_ru_en

								a_     			=   tokenizer.encode("""sequence builders"""			,       add_special_tokens=lowercase__    )
								a_     			=   tokenizer.encode("""multi-sequence build"""			,       add_special_tokens=lowercase__    )

								a_     			=   tokenizer.build_inputs_with_special_tokens(lowercase__    )
								a_     			=   tokenizer.build_inputs_with_special_tokens(lowercase__			,       lowercase__    )

								assert encoded_sentence == text + [2]
								assert encoded_pair == text + [2] + text_a + [2]





							@slow
							def   __magic_name__      (							self    ):
								a_     			=   self.tokenizer_en_ru
								a_     			=   self.tokenizer_ru_en

								a_     			=   [
								    [
								        """Here\'s a little song I wrote. Don\'t worry, be happy.""",
								        [2470, 39, 11, 2349, 7222, 70, 5979, 7, 8450, 1050, 1_3160, 5, 26, 6445, 7, 2],
								    ],
								    ["""This is it. No more. I\'m done!""", [132, 21, 37, 7, 1434, 86, 7, 70, 6476, 1305, 427, 2]],
								]

								# if data needs to be recreated or added, run:
								# import torch
								# model = torch.hub.load("pytorch/fairseq", "transformer.wmt19.en-ru", checkpoint_file="model4.pt", tokenizer="moses", bpe="fastbpe")
								# for src_text, _ in targets: print(f"""[\n"{src_text}",\n {model.encode(src_text).tolist()}\n],""")

								for src_text, tgt_input_ids in targets:
									a_     			=   tokenizer_enc.encode(lowercase__			,       return_tensors=lowercase__    )
									self.assertListEqual(lowercase__			,       lowercase__    )

									# and decode backward, using the reversed languages model
									a_     			=   tokenizer_dec.decode(lowercase__			,       skip_special_tokens=lowercase__    )
									self.assertEqual(lowercase__			,       lowercase__    )





							@slow
							def   __magic_name__      (							self    ):
								a_     			=   FSMTTokenizer.from_pretrained("""facebook/wmt19-ru-en"""			,       do_lower_case=lowercase__    )
								a_     			=   tokenizer.tokenize("""USA is United States of America"""    )
								a_     			=   ["""us""", """a</w>""", """is</w>""", """un""", """i""", """ted</w>""", """st""", """ates</w>""", """of</w>""", """am""", """er""", """ica</w>"""]
								self.assertListEqual(lowercase__			,       lowercase__    )





							@unittest.skip("""FSMTConfig.__init__  requires non-optional args"""    )
							def   __magic_name__      (							self    ):
								pass





							@unittest.skip("""FSMTConfig.__init__  requires non-optional args"""    )
							def   __magic_name__      (							self    ):
								pass
import unittest

from cer import CER


lowerCAmelCase__      		=					CER()
class 							a_					(		unittest.TestCase		):






 '''simple docstring'''






 def 						__snake_case		(     self   :    Any):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['White House']
        lowerCAmelCase__	      =   ['white house']
        # S = 2, D = 0, I = 0, N = 11, CER = 2 / 11
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.1_818_181_818) < 1e-6)




 def 						__snake_case		(     self   :    List[Any]):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['were wolf']
        lowerCAmelCase__	      =   ['werewolf']
        # S = 0, D = 0, I = 1, N = 9, CER = 1 / 9
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.1_111_111) < 1e-6)

        lowerCAmelCase__	      =   ['werewolf']
        lowerCAmelCase__	      =   ['weae     wolf']
        # S = 1, D = 1, I = 0, N = 8, CER = 0.25
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.25) < 1e-6)

        # consecutive whitespaces case 1
        lowerCAmelCase__	      =   ['were wolf']
        lowerCAmelCase__	      =   ['were               wolf']
        # S = 0, D = 0, I = 0, N = 9, CER = 0
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.0) < 1e-6)

        # consecutive whitespaces case 2
        lowerCAmelCase__	      =   ['were   wolf']
        lowerCAmelCase__	      =   ['were               wolf']
        # S = 0, D = 0, I = 0, N = 9, CER = 0
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.0) < 1e-6)




 def 						__snake_case		(     self   :    Optional[Any]):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['werewolf']
        lowerCAmelCase__	      =   ['weaewolf']
        # S = 1, D = 0, I = 0, N = 8, CER = 0.125
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.125) < 1e-6)




 def 						__snake_case		(     self   :    Tuple):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['werewolf']
        lowerCAmelCase__	      =   ['wereawolf']
        # S = 0, D = 1, I = 0, N = 8, CER = 0.125
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.125) < 1e-6)




 def 						__snake_case		(     self   :    Optional[int]):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['werewolf']
        lowerCAmelCase__	      =   ['wereolf']
        # S = 0, D = 0, I = 1, N = 8, CER = 0.125
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.125) < 1e-6)




 def 						__snake_case		(     self   :    str):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['werewolf']
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertEqual(lowercase__     ,       0.0)




 def 						__snake_case		(     self   :    Tuple):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['werewolf', 'I am your father']
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertEqual(lowercase__     ,       0.0)

        lowerCAmelCase__	      =   ['werewolf', 'I am your father', 'doge']
        lowerCAmelCase__	      =   ['werxwolf', 'I       am your father', 'doge']
        # S = 1, D = 0, I = 0, N = 28, CER = 1 / 28
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.03_571_428) < 1e-6)




 def 						__snake_case		(     self   :    Tuple):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['My hovercraft', 'is full of eels']
        lowerCAmelCase__	      =   ['My hovercraft is full', ' of eels']
        # S = 0, D = 0, I = 2, N = 28, CER = 2 / 28
        # whitespace at the front of " of eels" will be strip during preporcessing
        # so need to insert 2 whitespaces
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__     ,       concatenate_texts=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.071_428) < 1e-6)




 def 						__snake_case		(     self   :    Dict):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['我能吞下玻璃而不伤身体']
        lowerCAmelCase__	      =   [' 能吞虾玻璃而 不霜身体啦']
        # S = 3, D = 2, I = 0, N = 11, CER = 5 / 11
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.4_545_454_545) < 1e-6)

        lowerCAmelCase__	      =   ['我能吞下玻璃', '而不伤身体']
        lowerCAmelCase__	      =   ['我    能 吞 下 玻 璃', '而不伤身体']
        # S = 0, D = 5, I = 0, N = 11, CER = 5 / 11
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertTrue(abs(char_error_rate - 0.454_545_454_545) < 1e-6)

        lowerCAmelCase__	      =   ['我能吞下玻璃而不伤身体']
        lowerCAmelCase__	      =   cer.compute(predictions=lowercase__     ,       references=lowercase__)
        self.assertFalse(lowercase__     ,       0.0)




 def 						__snake_case		(     self   :    Dict):







        '''simple docstring'''



        lowerCAmelCase__	      =   ['']
        lowerCAmelCase__	      =   ['Hypothesis']
        with self.assertRaises(lowercase__):
               cer.compute(predictions=lowercase__     ,       references=lowercase__)


if __name__ == "__main__":
    unittest.main()
