


"""simple docstring"""
import json
import os
import re
import warnings
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE					:       Tuple							   =							logging.get_logger(__name__)

SCREAMING_SNAKE_CASE					:       List[str]							   =							{
    """source_spm""": """source.spm""",
    """target_spm""": """target.spm""",
    """vocab""": """vocab.json""",
    """target_vocab_file""": """target_vocab.json""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

SCREAMING_SNAKE_CASE					:       Tuple							   =							{
    """source_spm""": {
        """Helsinki-NLP/opus-mt-en-de""": """https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/source.spm"""
    },
    """target_spm""": {
        """Helsinki-NLP/opus-mt-en-de""": """https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/target.spm"""
    },
    """vocab""": {
        """Helsinki-NLP/opus-mt-en-de""": """https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/vocab.json"""
    },
    """tokenizer_config_file""": {
        """Helsinki-NLP/opus-mt-en-de""": (
            """https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/tokenizer_config.json"""
        )
    },
}

SCREAMING_SNAKE_CASE					:       Optional[int]							   =							{"""Helsinki-NLP/opus-mt-en-de""": 512}
SCREAMING_SNAKE_CASE					:       Optional[int]							   =							{}



class      _UpperCAmelCase					(				__snake_case							):






		'''simple docstring'''

		lowerCamelCase__           =VOCAB_FILES_NAMES
		lowerCamelCase__           =PRETRAINED_VOCAB_FILES_MAP
		lowerCamelCase__           =PRETRAINED_INIT_CONFIGURATION
		lowerCamelCase__           =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowerCamelCase__           =['input_ids', 'attention_mask']
		lowerCamelCase__           =re.compile('>>.+<<'							)  # type: re.Pattern



		def __init__(self							,			a_							,			a_							,			a_							,			a_=None							,			a_=None							,			a_=None							,			a_="<unk>"							,			a_="</s>"							,			a_="<pad>"							,			a_=5_12							,			a_ = None							,			a_=False							,			**a_							,			):





			'''simple docstring'''

			__snake_case      :		Tuple         =							{} if sp_model_kwargs is None else sp_model_kwargs

			super().__init__(
			    # bos_token=bos_token,  unused. Start decoding with config.decoder_start_token_id
			    source_lang=a_							,			target_lang=a_							,			unk_token=a_							,			eos_token=a_							,			pad_token=a_							,			model_max_length=a_							,			sp_model_kwargs=self.sp_model_kwargs							,			target_vocab_file=a_							,			separate_vocabs=a_							,			**a_							,			)
			assert Path(a_   ).exists(), f"""cannot find spm source {source_spm}"""

			__snake_case      :		Any         =							separate_vocabs
			__snake_case      :		List[str]         =							load_json(a_   )
			if self.unk_token not in self.encoder:
				raise KeyError('''<unk> token must be in vocab'''   )
			assert self.pad_token in self.encoder

			if separate_vocabs:
				__snake_case      :		List[Any]         =							load_json(a_   )
				__snake_case      :		Optional[Any]         =							{v: k for k, v in self.target_encoder.items()}
				__snake_case      :		List[str]         =							[]
			else:
				__snake_case      :		str         =							{v: k for k, v in self.encoder.items()}
				__snake_case      :		list         =							[k for k in self.encoder if k.startswith('''>>'''   ) and k.endswith('''<<'''   )]

			__snake_case      :		int         =							source_lang
			__snake_case      :		int         =							target_lang
			__snake_case      :		List[str]         =							[source_spm, target_spm]

			# load SentencePiece model for pre-processing
			__snake_case      :		Any         =							load_spm(a_							,			self.sp_model_kwargs   )
			__snake_case      :		Union[str, Any]         =							load_spm(a_							,			self.sp_model_kwargs   )
			__snake_case      :		List[str]         =							self.spm_source
			__snake_case      :		Dict         =							self.encoder

			# Multilingual target side: default to using first supported language code.

			self._setup_normalizer()



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			try:
				from sacremoses import MosesPunctNormalizer

				__snake_case      :		Dict         =							MosesPunctNormalizer(self.source_lang   ).normalize
			except (ImportError, FileNotFoundError):
				warnings.warn('''Recommended: pip install sacremoses.'''   )
				__snake_case      :		Dict         =							lambda a_   : x



		def 							SCREAMING_SNAKE_CASE    (self							,			a_   ):





			'''simple docstring'''

			return self.punc_normalizer(a_   ) if x else ""



		def 							SCREAMING_SNAKE_CASE    (self							,			a_   ):





			'''simple docstring'''

			return self.current_encoder.get(a_							,			self.current_encoder[self.unk_token]   )



		def 							SCREAMING_SNAKE_CASE    (self							,			a_   ):





			'''simple docstring'''

			__snake_case      :		List[str]         =							self.language_code_re.match(a_   )
			__snake_case      :		list         =							[match.group(0   )] if match else []
			return code, self.language_code_re.sub(''''''							,			a_   )



		def 							SCREAMING_SNAKE_CASE    (self							,			a_   ):





			'''simple docstring'''

			__snake_case      ,				__snake_case      :		List[str]         =							self.remove_language_code(a_   )
			__snake_case      :		int         =							self.current_spm.encode(a_							,			out_type=a_   )
			return code + pieces



		def 							SCREAMING_SNAKE_CASE    (self							,			a_   ):





			'''simple docstring'''

			return self.decoder.get(a_							,			self.unk_token   )



		def 							SCREAMING_SNAKE_CASE    (self							,			a_							,			**a_   ):





			'''simple docstring'''

			return super().batch_decode(a_							,			**a_   )



		def 							SCREAMING_SNAKE_CASE    (self							,			a_							,			**a_   ):





			'''simple docstring'''

			return super().decode(a_							,			**a_   )



		def 							SCREAMING_SNAKE_CASE    (self							,			a_   ):





			'''simple docstring'''

			__snake_case      :		Optional[int]         =							self.spm_source if self._decode_use_source_tokenizer else self.spm_target
			__snake_case      :		List[str]         =							[]
			__snake_case      :		Optional[int]         =							''''''
			for token in tokens:
				# make sure that special tokens are not decoded using sentencepiece model
				if token in self.all_special_tokens:
					out_string += sp_model.decode_pieces(a_   ) + token + " "
					__snake_case      :		Dict         =							[]
				else:
					current_sub_tokens.append(a_   )
			out_string += sp_model.decode_pieces(a_   )
			return out_string.strip()



		def 							SCREAMING_SNAKE_CASE    (self							,			a_							,			a_=None   ):





			'''simple docstring'''

			if token_ids_a is None:
				return token_ids_a + [self.eos_token_id]
			# We don't expect to process pairs, but leave the pair logic for API consistency
			return token_ids_a + token_ids_a + [self.eos_token_id]



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Tuple         =							self.spm_source
			__snake_case      :		Optional[Any]         =							self.encoder



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Tuple         =							self.spm_target
			if self.separate_vocabs:
				__snake_case      :		Dict         =							self.target_encoder



		@property
		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			return len(self.encoder   )



		def 							SCREAMING_SNAKE_CASE    (self							,			a_							,			a_ = None   ):





			'''simple docstring'''

			if not os.path.isdir(a_   ):
				logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""   )
				return
			__snake_case      :		int         =							[]

			if self.separate_vocabs:
				__snake_case      :		List[str]         =							os.path.join(
				    a_							,			(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab''']							,			)
				__snake_case      :		Tuple         =							os.path.join(
				    a_							,			(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''target_vocab_file''']							,			)
				save_json(self.encoder							,			a_   )
				save_json(self.target_encoder							,			a_   )
				saved_files.append(a_   )
				saved_files.append(a_   )
			else:
				__snake_case      :		List[Any]         =							os.path.join(
				    a_							,			(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab''']   )
				save_json(self.encoder							,			a_   )
				saved_files.append(a_   )

			for spm_save_filename, spm_orig_path, spm_model in zip(
			    [VOCAB_FILES_NAMES['''source_spm'''], VOCAB_FILES_NAMES['''target_spm''']]							,			self.spm_files							,			[self.spm_source, self.spm_target]							,			):
				__snake_case      :		Any         =							os.path.join(
				    a_							,			(filename_prefix + '''-''' if filename_prefix else '''''') + spm_save_filename   )
				if os.path.abspath(a_   ) != os.path.abspath(a_   ) and os.path.isfile(a_   ):
					copyfile(a_							,			a_   )
					saved_files.append(a_   )
				elif not os.path.isfile(a_   ):
					with open(a_							,			'''wb'''   ) as fi:
						__snake_case      :		Optional[Any]         =							spm_model.serialized_model_proto()
						fi.write(a_   )
					saved_files.append(a_   )

			return tuple(a_   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			return self.get_src_vocab()



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			return dict(self.encoder							,			**self.added_tokens_encoder   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			return dict(self.target_encoder							,			**self.added_tokens_decoder   )



		def __getstate__(self   ):





			'''simple docstring'''

			__snake_case      :		Any         =							self.__dict__.copy()
			state.update(
			    {k: None for k in ['''spm_source''', '''spm_target''', '''current_spm''', '''punc_normalizer''', '''target_vocab_file''']}   )
			return state



		def __setstate__(self							,			a_   ):





			'''simple docstring'''

			__snake_case      :		Dict         =							d

			# for backward compatibility
			if not hasattr(self							,			'''sp_model_kwargs'''   ):
				__snake_case      :		Tuple         =							{}

			__snake_case      ,				__snake_case      :		int         =							(load_spm(a_							,			self.sp_model_kwargs   ) for f in self.spm_files)
			__snake_case      :		str         =							self.spm_source
			self._setup_normalizer()



		def 							SCREAMING_SNAKE_CASE    (self							,			*a_							,			**a_   ):





			'''simple docstring'''

			return 1



		def 							SCREAMING_SNAKE_CASE    (self							,			a_   ):





			'''simple docstring'''

			__snake_case      :		Optional[int]         =							set(self.all_special_ids   )  # call it once instead of inside list comp
			all_special_ids.remove(self.unk_token_id   )  # <unk> is only sometimes special
			return [1 if x in all_special_ids else 0 for x in seq]



		def 							SCREAMING_SNAKE_CASE    (self							,			a_							,			a_ = None							,			a_ = False   ):





			'''simple docstring'''

			if already_has_special_tokens:
				return self._special_token_mask(a_   )
			elif token_ids_a is None:
				return self._special_token_mask(a_   ) + [1]
			else:
				return self._special_token_mask(token_ids_a + token_ids_a   ) + [1]






def 						lowercase				(	_snake_case		: str	,  _snake_case		: Dict[str, Any]	)	->sentencepiece.SentencePieceProcessor:
	"""simple docstring"""





	__snake_case      :		Union[str, Any]         =							sentencepiece.SentencePieceProcessor(**_snake_case	)
	spm.Load(_snake_case	)
	return spm






def 						lowercase				(	_snake_case		: Union[str, Any]	,  _snake_case		: str	)	->None:
	"""simple docstring"""





	with open(_snake_case	,  '''w'''	) as f:
		json.dump(_snake_case	,  _snake_case	,  indent=2	)






def 						lowercase				(	_snake_case		: str	)	->Union[Dict, List]:
	"""simple docstring"""





	with open(_snake_case	,  '''r'''	) as f:
		return json.load(_snake_case	)









"""simple docstring"""
import unittest
from dataclasses import dataclass
from typing import Optional

from transformers.utils import ModelOutput



@dataclass
class      _UpperCAmelCase					(				__snake_case							):






		'''simple docstring'''

		lowerCamelCase__           =42
		lowerCamelCase__           =None
		lowerCamelCase__           =None



class      _UpperCAmelCase					(				unittest.TestCase							):






		'''simple docstring'''

		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Union[str, Any]         =							ModelOutputTest(a=30   )
			self.assertEqual(x.a							,			30   )
			self.assertIsNone(x.b   )
			self.assertIsNone(x.c   )
			with self.assertRaises(a_   ):
				__snake_case      :		str         =							x.d



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Union[str, Any]         =							ModelOutputTest(a=30							,			b=10   )
			self.assertEqual(x[0]							,			30   )
			self.assertEqual(x[1]							,			10   )
			self.assertEqual(x[:2]							,			(30, 10)   )
			self.assertEqual(x[:]							,			(30, 10)   )

			__snake_case      :		List[Any]         =							ModelOutputTest(a=30							,			c=10   )
			self.assertEqual(x[0]							,			30   )
			self.assertEqual(x[1]							,			10   )
			self.assertEqual(x[:2]							,			(30, 10)   )
			self.assertEqual(x[:]							,			(30, 10)   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Optional[int]         =							ModelOutputTest(a=30							,			b=10   )
			self.assertEqual(x['''a''']							,			30   )
			self.assertEqual(x['''b''']							,			10   )
			with self.assertRaises(a_   ):
				__snake_case      :		Optional[int]         =							x['''c''']

			__snake_case      :		Any         =							ModelOutputTest(a=30							,			c=10   )
			self.assertEqual(x['''a''']							,			30   )
			self.assertEqual(x['''c''']							,			10   )
			with self.assertRaises(a_   ):
				__snake_case      :		Optional[int]         =							x['''b''']



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Optional[int]         =							ModelOutputTest(a=30   )
			self.assertEqual(list(x.keys()   )							,			['''a''']   )
			self.assertEqual(list(x.values()   )							,			[30]   )
			self.assertEqual(list(x.items()   )							,			[('''a''', 30)]   )
			self.assertEqual(list(a_   )							,			['''a''']   )

			__snake_case      :		Optional[int]         =							ModelOutputTest(a=30							,			b=10   )
			self.assertEqual(list(x.keys()   )							,			['''a''', '''b''']   )
			self.assertEqual(list(x.values()   )							,			[30, 10]   )
			self.assertEqual(list(x.items()   )							,			[('''a''', 30), ('''b''', 10)]   )
			self.assertEqual(list(a_   )							,			['''a''', '''b''']   )

			__snake_case      :		Optional[Any]         =							ModelOutputTest(a=30							,			c=10   )
			self.assertEqual(list(x.keys()   )							,			['''a''', '''c''']   )
			self.assertEqual(list(x.values()   )							,			[30, 10]   )
			self.assertEqual(list(x.items()   )							,			[('''a''', 30), ('''c''', 10)]   )
			self.assertEqual(list(a_   )							,			['''a''', '''c''']   )

			with self.assertRaises(a_   ):
				__snake_case      :		Optional[int]         =							x.update({'''d''': 20}   )
			with self.assertRaises(a_   ):
				del x["a"]
			with self.assertRaises(a_   ):
				__snake_case      :		Union[str, Any]         =							x.pop('''a'''   )
			with self.assertRaises(a_   ):
				__snake_case      :		Optional[Any]         =							x.setdefault('''d'''							,			32   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		List[str]         =							ModelOutputTest(a=30   )
			__snake_case      :		Tuple         =							10
			self.assertEqual(x.a							,			10   )
			self.assertEqual(x['''a''']							,			10   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		List[str]         =							ModelOutputTest(a=30   )
			__snake_case      :		Any         =							10
			self.assertEqual(x.a							,			10   )
			self.assertEqual(x['''a''']							,			10   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		int         =							ModelOutputTest({'''a''': 30, '''b''': 10}   )
			self.assertEqual(list(x.keys()   )							,			['''a''', '''b''']   )
			self.assertEqual(x.a							,			30   )
			self.assertEqual(x.b							,			10   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Any         =							ModelOutputTest([('''a''', 30), ('''b''', 10)]   )
			self.assertEqual(list(x.keys()   )							,			['''a''', '''b''']   )
			self.assertEqual(x.a							,			30   )
			self.assertEqual(x.b							,			10   )

			with self.assertRaises(a_   ):
				__snake_case      :		List[Any]         =							ModelOutputTest([('''a''', 30), (10, 10)]   )

			__snake_case      :		Union[str, Any]         =							ModelOutputTest(a=(30, 30)   )
			self.assertEqual(list(x.keys()   )							,			['''a''']   )
			self.assertEqual(x.a							,			(30, 30)   )





