



"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


__SCREAMING_SNAKE_CASE  :						Union[str, Any]    							=      logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE  :						int    							=      '''▁'''

__SCREAMING_SNAKE_CASE  :						Union[str, Any]    							=      {'''vocab_file''': '''sentencepiece.bpe.model'''}

__SCREAMING_SNAKE_CASE  :						Union[str, Any]    							=      {
    '''vocab_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model''',
    }
}

__SCREAMING_SNAKE_CASE  :						str    							=      {
    '''facebook/xglm-564M''': 2_0_4_8,
}


class 							lowerCamelCase_(   A__    ):





					'''simple docstring'''



					lowercase__   :       Union[str, Any]										= VOCAB_FILES_NAMES
					lowercase__   :       List[str]										= PRETRAINED_VOCAB_FILES_MAP
					lowercase__   :       int										= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowercase__   :       Any										= ['input_ids', 'attention_mask']

					def __init__(    self				,       lowerCamelCase__				,       lowerCamelCase__="<s>"				,       lowerCamelCase__="</s>"				,       lowerCamelCase__="</s>"				,       lowerCamelCase__="<s>"				,       lowerCamelCase__="<unk>"				,       lowerCamelCase__="<pad>"				,       lowerCamelCase__ = None				,       **lowerCamelCase__				,       ):
									_lowerCamelCase        =				{} if sp_model_kwargs is None else sp_model_kwargs

									# Compatibility with the original tokenizer
									_lowerCamelCase        =				7
									_lowerCamelCase        =				[F"""<madeupword{i}>""" for i in range(self.num_madeup_words   )]

									_lowerCamelCase        =				kwargs.get('''additional_special_tokens'''				,       []   )
									kwargs["additional_special_tokens"] += [
									    word for word in madeup_words if word not in kwargs["additional_special_tokens"]
									]

									super().__init__(
									    bos_token=lowerCamelCase__				,       eos_token=lowerCamelCase__				,       unk_token=lowerCamelCase__				,       sep_token=lowerCamelCase__				,       cls_token=lowerCamelCase__				,       pad_token=lowerCamelCase__				,       sp_model_kwargs=self.sp_model_kwargs				,       **lowerCamelCase__				,       )

									_lowerCamelCase        =				spm.SentencePieceProcessor(**self.sp_model_kwargs   )
									self.sp_model.Load(str(lowerCamelCase__   )   )
									_lowerCamelCase        =				vocab_file

									# Original fairseq vocab and spm vocab must be "aligned":
									# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
									# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
									# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
									# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

									# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
									_lowerCamelCase        =				1

									# Mimic fairseq token-to-id alignment for the first 4 token
									_lowerCamelCase        =				{'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

									_lowerCamelCase        =				len(self.sp_model   )
									_lowerCamelCase        =				{F"""<madeupword{i}>""": sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words   )}
									self.fairseq_tokens_to_ids.update(lowerCamelCase__   )

									_lowerCamelCase        =				{v: k for k, v in self.fairseq_tokens_to_ids.items()}

					def __getstate__(    self   ):
									_lowerCamelCase        =				self.__dict__.copy()
									_lowerCamelCase        =				None
									_lowerCamelCase        =				self.sp_model.serialized_model_proto()
									return state

					def __setstate__(    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				d

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

									_lowerCamelCase        =				spm.SentencePieceProcessor(**self.sp_model_kwargs   )
									self.sp_model.LoadFromSerializedProto(self.sp_model_proto   )

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):

									if token_ids_a is None:
													return [self.sep_token_id] + token_ids_a
									_lowerCamelCase        =				[self.sep_token_id]
									return sep + token_ids_a + sep + sep + token_ids_a

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None				,       lowerCamelCase__ = False   ):

									if already_has_special_tokens:
													return super().get_special_tokens_mask(
													    token_ids_a=lowerCamelCase__				,       token_ids_a=lowerCamelCase__				,       already_has_special_tokens=lowerCamelCase__   )

									if token_ids_a is None:
													return [1] + ([0] * len(lowerCamelCase__   ))
									return [1] + ([0] * len(lowerCamelCase__   )) + [1, 1] + ([0] * len(lowerCamelCase__   ))

					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):
									_lowerCamelCase        =				[self.sep_token_id]

									if token_ids_a is None:
													return len(sep + token_ids_a   ) * [0]
									return len(sep + token_ids_a + sep + sep + token_ids_a   ) * [0]

					@property
					def 			snake_case__      (    self   ):
									return len(self.sp_model   ) + self.fairseq_offset + self.num_madeup_words

					def 			snake_case__      (    self   ):
									_lowerCamelCase        =				{self.convert_ids_to_tokens(lowerCamelCase__   ): i for i in range(self.vocab_size   )}
									vocab.update(self.added_tokens_encoder   )
									return vocab

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									return self.sp_model.encode(lowerCamelCase__				,       out_type=lowerCamelCase__   )

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									if token in self.fairseq_tokens_to_ids:
													return self.fairseq_tokens_to_ids[token]
									_lowerCamelCase        =				self.sp_model.PieceToId(lowerCamelCase__   )

									# Need to return unknown token if the SP model returned 0
									return spm_id + self.fairseq_offset if spm_id else self.unk_token_id

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									if index in self.fairseq_ids_to_tokens:
													return self.fairseq_ids_to_tokens[index]
									return self.sp_model.IdToPiece(index - self.fairseq_offset   )

					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				''''''.join(lowerCamelCase__   ).replace(lowerCamelCase__				,       ''' '''   ).strip()
									return out_string





					def 			snake_case__      (    self				,       lowerCamelCase__				,       lowerCamelCase__ = None   ):
									if not os.path.isdir(lowerCamelCase__   ):
													logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""   )
													return
									_lowerCamelCase        =				os.path.join(
									    lowerCamelCase__				,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']   )

									if os.path.abspath(self.vocab_file   ) != os.path.abspath(lowerCamelCase__   ) and os.path.isfile(self.vocab_file   ):
													copyfile(self.vocab_file				,       lowerCamelCase__   )
									elif not os.path.isfile(self.vocab_file   ):
													with open(lowerCamelCase__				,       '''wb'''   ) as fi:
																	_lowerCamelCase        =				self.sp_model.serialized_model_proto()
																	fi.write(lowerCamelCase__   )

									return (out_vocab_file,)





"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import sys
import warnings
from os.path import abspath, dirname, join


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
__SCREAMING_SNAKE_CASE  :						Optional[Any]    							=      abspath(join(dirname(dirname(__file__)), '''src'''))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action='''ignore''', category=FutureWarning)



def        lowerCAmelCase_(   lowercase_     :							List[Any]							)	->       Optional[Any]:
				from diffusers.utils.testing_utils import pytest_addoption_shared

				pytest_addoption_shared(lowercase_							)




def        lowerCAmelCase_(   lowercase_     :							List[str]							)	->       List[str]:
				from diffusers.utils.testing_utils import pytest_terminal_summary_main

				_lowerCamelCase        =				terminalreporter.config.getoption('''--make-reports'''							)
				if make_reports:
								pytest_terminal_summary_main(lowercase_						,   id=lowercase_							)
