
'''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


__lowercase							:				Optional[Any]					=       logging.get_logger(__name__)

__lowercase							:				Optional[Any]					=       {
    '''source_spm''': '''source.spm''',
    '''target_spm''': '''target.spm''',
    '''vocab''': '''vocab.json''',
    '''target_vocab_file''': '''target_vocab.json''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

__lowercase							:				List[Any]					=       {
    '''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'''
        )
    },
}

__lowercase							:				int					=       {'''Helsinki-NLP/opus-mt-en-de''': 512}
__lowercase							:				Optional[Any]					=       {}

class 		__lowercase			(					_lowercase      ):
			lowerCamelCase     :						Tuple		 =     VOCAB_FILES_NAMES
			lowerCamelCase     :						Dict		 =     PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase     :						int		 =     PRETRAINED_INIT_CONFIGURATION
			lowerCamelCase     :						Dict		 =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase     :						str		 =     ["input_ids", "attention_mask"]
			lowerCamelCase     :						int		 =     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_1_2     ,				A = None     ,				A=False     ,				**A     ,				):
								lowerCamelCase_   : 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}"""

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

								lowerCamelCase_   : Optional[Any]       =						source_lang
								lowerCamelCase_   : int       =						target_lang
								lowerCamelCase_   : Optional[int]       =						[source_spm, target_spm]

								# load SentencePiece model for pre-processing
								lowerCamelCase_   : Optional[int]       =						load_spm(A     ,				self.sp_model_kwargs )
								lowerCamelCase_   : Any       =						load_spm(A     ,				self.sp_model_kwargs )
								lowerCamelCase_   : Union[str, Any]       =						self.spm_source
								lowerCamelCase_   : Any       =						self.encoder

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

								self._setup_normalizer()

			def     UpperCAmelCase__	(self ):
								try:
													from sacremoses import MosesPunctNormalizer

													lowerCamelCase_   : Optional[int]       =						MosesPunctNormalizer(self.source_lang ).normalize
								except (ImportError, FileNotFoundError):
													warnings.warn('''Recommended: pip install sacremoses.''' )
													lowerCamelCase_   : List[Any]       =						lambda A : x

			def     UpperCAmelCase__	(self     ,				A ):
								return self.punc_normalizer(A ) if x else ""

			def     UpperCAmelCase__	(self     ,				A ):
								return self.current_encoder.get(A     ,				self.current_encoder[self.unk_token] )

			def     UpperCAmelCase__	(self     ,				A ):
								lowerCamelCase_   : Optional[int]       =						self.language_code_re.match(A )
								lowerCamelCase_   : list       =						[match.group(0 )] if match else []
								return code, self.language_code_re.sub(''''''     ,				A )

			def     UpperCAmelCase__	(self     ,				A ):
								lowerCamelCase_, lowerCamelCase_   : str       =						self.remove_language_code(A )
								lowerCamelCase_   : List[str]       =						self.current_spm.encode(A     ,				out_type=A )
								return code + pieces

			def     UpperCAmelCase__	(self     ,				A ):
								return self.decoder.get(A     ,				self.unk_token )

			def     UpperCAmelCase__	(self     ,				A     ,				**A ):
								return super().batch_decode(A     ,				**A )

			def     UpperCAmelCase__	(self     ,				A     ,				**A ):
								return super().decode(A     ,				**A )

			def     UpperCAmelCase__	(self     ,				A ):
								lowerCamelCase_   : Tuple       =						self.spm_source if self._decode_use_source_tokenizer else self.spm_target
								lowerCamelCase_   : Any       =						[]
								lowerCamelCase_   : 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 + " "
																		lowerCamelCase_   : List[str]       =						[]
													else:
																		current_sub_tokens.append(A )
								out_string += sp_model.decode_pieces(A )
								return out_string.strip()

			def     UpperCAmelCase__	(self     ,				A     ,				A=None ):
								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     UpperCAmelCase__	(self ):
								lowerCamelCase_   : Any       =						self.spm_source
								lowerCamelCase_   : Any       =						self.encoder

			def     UpperCAmelCase__	(self ):
								lowerCamelCase_   : List[str]       =						self.spm_target
								if self.separate_vocabs:
													lowerCamelCase_   : Optional[int]       =						self.target_encoder

			@property
			def     UpperCAmelCase__	(self ):
								return len(self.encoder )

			def     UpperCAmelCase__	(self     ,				A     ,				A = None ):
								if not os.path.isdir(A ):
													logger.error(F"""Vocabulary path ({save_directory}) should be a directory""" )
													return
								lowerCamelCase_   : Optional[Any]       =						[]

								if self.separate_vocabs:
													lowerCamelCase_   : Any       =						os.path.join(
													    A     ,				(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab''']     ,				)
													lowerCamelCase_   : List[str]       =						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:
													lowerCamelCase_   : Optional[int]       =						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]     ,				):
													lowerCamelCase_   : Dict       =						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:
																							lowerCamelCase_   : List[Any]       =						spm_model.serialized_model_proto()
																							fi.write(A )
																		saved_files.append(A )

								return tuple(A )

			def     UpperCAmelCase__	(self ):
								return self.get_src_vocab()

			def     UpperCAmelCase__	(self ):
								return dict(self.encoder     ,				**self.added_tokens_encoder )

			def     UpperCAmelCase__	(self ):
								return dict(self.target_encoder     ,				**self.added_tokens_decoder )

			def __getstate__(self ):
								lowerCamelCase_   : List[str]       =						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 ):
								lowerCamelCase_   : List[str]       =						d

								# for backward compatibility
								if not hasattr(self     ,				'''sp_model_kwargs''' ):
													lowerCamelCase_   : Union[str, Any]       =						{}

								lowerCamelCase_, lowerCamelCase_   : Tuple       =						(load_spm(A     ,				self.sp_model_kwargs ) for f in self.spm_files)
								lowerCamelCase_   : Any       =						self.spm_source
								self._setup_normalizer()

			def     UpperCAmelCase__	(self     ,				*A     ,				**A ):
								return 1

			def     UpperCAmelCase__	(self     ,				A ):
								lowerCamelCase_   : 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     UpperCAmelCase__	(self     ,				A     ,				A = None     ,				A = False ):
								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_		(				_lowercase     ,    _lowercase			)       ->							sentencepiece.SentencePieceProcessor:
					'''simple docstring'''

					lowerCamelCase_   : Any       =						sentencepiece.SentencePieceProcessor(**_lowercase			)
					spm.Load(_lowercase			)
					return spm




def lowercase_		(				_lowercase     ,    _lowercase			)       ->							None:
					'''simple docstring'''

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






def lowercase_		(				_lowercase			)       ->							Union[Dict, List]:
					'''simple docstring'''

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




'''simple docstring'''


import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_with_pabee

from transformers.testing_utils import TestCasePlus


logging.basicConfig(level=logging.DEBUG)

__lowercase							:				Optional[Any]					=       logging.getLogger()




def lowercase_		(				)       ->							Union[str, Any]:
					'''simple docstring'''

					lowerCamelCase_   : Any       =						argparse.ArgumentParser()
					parser.add_argument('''-f'''			)
					lowerCamelCase_   : Optional[int]       =						parser.parse_args()
					return args.f






class 		__lowercase			(					_lowercase      ):

			def     UpperCAmelCase__	(self ):
								lowerCamelCase_   : Dict       =						logging.StreamHandler(sys.stdout )
								logger.addHandler(A )

								lowerCamelCase_   : int       =						self.get_auto_remove_tmp_dir()
								lowerCamelCase_   : Dict       =						F"""
            run_glue_with_pabee.py
            --model_type albert
            --model_name_or_path albert-base-v2
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --task_name mrpc
            --do_train
            --do_eval
            --per_gpu_train_batch_size=2
            --per_gpu_eval_batch_size=1
            --learning_rate=2e-5
            --max_steps=50
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            """.split()

								with patch.object(A     ,				'''argv'''     ,				A ):
													lowerCamelCase_   : Optional[Any]       =						run_glue_with_pabee.main()
													for value in result.values():
																		self.assertGreaterEqual(A     ,				0.75 )


