



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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE_:Any					=						logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_:Optional[int]					=						"""▁"""

SCREAMING_SNAKE_CASE_:Tuple					=						{"""vocab_file""": """sentencepiece.bpe.model"""}

SCREAMING_SNAKE_CASE_:Optional[Any]					=						{
    """vocab_file""": {
        """facebook/mbart-large-en-ro""": (
            """https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model"""
        ),
        """facebook/mbart-large-cc25""": (
            """https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model"""
        ),
    }
}

SCREAMING_SNAKE_CASE_:Optional[Any]					=						{
    """facebook/mbart-large-en-ro""": 1_024,
    """facebook/mbart-large-cc25""": 1_024,
}

# fmt: off
SCREAMING_SNAKE_CASE_:Any					=						["""ar_AR""", """cs_CZ""", """de_DE""", """en_XX""", """es_XX""", """et_EE""", """fi_FI""", """fr_XX""", """gu_IN""", """hi_IN""", """it_IT""", """ja_XX""", """kk_KZ""", """ko_KR""", """lt_LT""", """lv_LV""", """my_MM""", """ne_NP""", """nl_XX""", """ro_RO""", """ru_RU""", """si_LK""", """tr_TR""", """vi_VN""", """zh_CN"""]






class SCREAMING_SNAKE_CASE__					(		SCREAMING_SNAKE_CASE__   ):




    '''simple docstring'''






    __lowerCamelCase      :			int =				VOCAB_FILES_NAMES
    __lowerCamelCase      :			Any =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __lowerCamelCase      :			Optional[int] =				PRETRAINED_VOCAB_FILES_MAP
    __lowerCamelCase      :			Union[str, Any] =				["input_ids", "attention_mask"]

    __lowerCamelCase      :			List[int] =				[]
    __lowerCamelCase      :			List[int] =				[]






    def __init__(	self,		lowerCamelCase__,		lowerCamelCase__="<s>",		lowerCamelCase__="</s>",		lowerCamelCase__="</s>",		lowerCamelCase__="<s>",		lowerCamelCase__="<unk>",		lowerCamelCase__="<pad>",		lowerCamelCase__="<mask>",		lowerCamelCase__=None,		lowerCamelCase__=None,		lowerCamelCase__=None,		lowerCamelCase__ = None,		lowerCamelCase__=None,		**lowerCamelCase__,		):
        # Mask token behave like a normal word, i.e. include the space before it
        A			:	List[str]										=       AddedToken(lowerCamelCase__,		lstrip=lowerCamelCase__,		rstrip=lowerCamelCase__		) if isinstance(lowerCamelCase__,		lowerCamelCase__		) else mask_token

        A			:	int										=       {} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            bos_token=lowerCamelCase__,		eos_token=lowerCamelCase__,		unk_token=lowerCamelCase__,		sep_token=lowerCamelCase__,		cls_token=lowerCamelCase__,		pad_token=lowerCamelCase__,		mask_token=lowerCamelCase__,		tokenizer_file=lowerCamelCase__,		src_lang=lowerCamelCase__,		tgt_lang=lowerCamelCase__,		additional_special_tokens=lowerCamelCase__,		sp_model_kwargs=self.sp_model_kwargs,		**lowerCamelCase__,		)

        A			:	List[str]										=       spm.SentencePieceProcessor(**self.sp_model_kwargs		)
        self.sp_model.Load(str(lowerCamelCase__		)		)
        A			:	Dict										=       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'

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

        # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
        A			:	List[Any]										=       1

        A			:	Optional[Any]										=       len(self.sp_model		)
        A			:	int										=       {
            code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(lowerCamelCase__		)
        }
        A			:	int										=       {v: k for k, v in self.lang_code_to_id.items()}
        A			:	List[Any]										=       len(self.sp_model		) + len(self.lang_code_to_id		) + self.fairseq_offset

        self.fairseq_tokens_to_ids.update(self.lang_code_to_id		)
        A			:	Union[str, Any]										=       {v: k for k, v in self.fairseq_tokens_to_ids.items()}
        A			:	Union[str, Any]										=       list(self.lang_code_to_id.keys()		)

        if additional_special_tokens is not None:
            # Only add those special tokens if they are not already there.
            self._additional_special_tokens.extend(
                [t for t in additional_special_tokens if t not in self._additional_special_tokens]		)

        A			:	List[Any]										=       src_lang if src_lang is not None else """en_XX"""
        A			:	Tuple										=       self.lang_code_to_id[self._src_lang]
        A			:	List[str]										=       tgt_lang
        self.set_src_lang_special_tokens(self._src_lang		)






    def __getstate__(	self		):
        A			:	Dict										=       self.__dict__.copy()
        A			:	Any										=       None
        A			:	Tuple										=       self.sp_model.serialized_model_proto()
        return state






    def __setstate__(	self,		lowerCamelCase__		):
        A			:	Any										=       d

        # for backward compatibility
        if not hasattr(self,		"""sp_model_kwargs"""		):
            A			:	int										=       {}

        A			:	Dict										=       spm.SentencePieceProcessor(**self.sp_model_kwargs		)
        self.sp_model.LoadFromSerializedProto(self.sp_model_proto		)






    @property
    def       _lowerCAmelCase (	self		):
        return len(self.sp_model		) + len(self.lang_code_to_id		) + self.fairseq_offset + 1  # Plus 1 for the mask token






    @property
    def       _lowerCAmelCase (	self		):
        return self._src_lang






    @src_lang.setter
    def       _lowerCAmelCase (	self,		lowerCamelCase__		):
        A			:	Any										=       new_src_lang
        self.set_src_lang_special_tokens(self._src_lang		)






    def       _lowerCAmelCase (	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__		)

        A			:	int										=       [1] * len(self.prefix_tokens		)
        A			:	Tuple										=       [1] * len(self.suffix_tokens		)
        if token_ids_a is None:
            return prefix_ones + ([0] * len(lowerCamelCase__		)) + suffix_ones
        return prefix_ones + ([0] * len(lowerCamelCase__		)) + ([0] * len(lowerCamelCase__		)) + suffix_ones






    def       _lowerCAmelCase (	self,		lowerCamelCase__,		lowerCamelCase__ = None		):
        if token_ids_a is None:
            return self.prefix_tokens + token_ids_a + self.suffix_tokens
        # We don't expect to process pairs, but leave the pair logic for API consistency
        return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens






    def       _lowerCAmelCase (	self,		lowerCamelCase__,		lowerCamelCase__ = None		):
        A			:	Optional[Any]										=       [self.sep_token_id]
        A			:	Optional[Any]										=       [self.cls_token_id]

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






    def       _lowerCAmelCase (	self,		lowerCamelCase__,		lowerCamelCase__,		lowerCamelCase__,		lowerCamelCase__,		**lowerCamelCase__		):
        if src_lang is None or tgt_lang is None:
            raise ValueError("""Translation requires a `src_lang` and a `tgt_lang` for this model"""		)
        A			:	List[str]										=       src_lang
        A			:	Optional[Any]										=       self(lowerCamelCase__,		add_special_tokens=lowerCamelCase__,		return_tensors=lowerCamelCase__,		**lowerCamelCase__		)
        A			:	Tuple										=       self.convert_tokens_to_ids(lowerCamelCase__		)
        A			:	int										=       tgt_lang_id
        return inputs






    def       _lowerCAmelCase (	self		):
        A			:	Optional[Any]										=       {self.convert_ids_to_tokens(lowerCamelCase__		): i for i in range(self.vocab_size		)}
        vocab.update(self.added_tokens_encoder		)
        return vocab






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






    def       _lowerCAmelCase (	self,		lowerCamelCase__		):
        if token in self.fairseq_tokens_to_ids:
            return self.fairseq_tokens_to_ids[token]
        A			:	Optional[int]										=       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       _lowerCAmelCase (	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       _lowerCAmelCase (	self,		lowerCamelCase__		):
        A			:	int										=       """""".join(lowerCamelCase__		).replace(lowerCamelCase__,		""" """		).strip()
        return out_string






    def       _lowerCAmelCase (	self,		lowerCamelCase__,		lowerCamelCase__ = None		):
        if not os.path.isdir(lowerCamelCase__		):
            logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''		)
            return
        A			:	Union[str, Any]										=       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:
                A			:	Tuple										=       self.sp_model.serialized_model_proto()
                fi.write(lowerCamelCase__		)

        return (out_vocab_file,)






    def       _lowerCAmelCase (	self,		lowerCamelCase__,		lowerCamelCase__ = "en_XX",		lowerCamelCase__ = None,		lowerCamelCase__ = "ro_RO",		**lowerCamelCase__,		):
        A			:	int										=       src_lang
        A			:	Optional[int]										=       tgt_lang
        return super().prepare_seqaseq_batch(lowerCamelCase__,		lowerCamelCase__,		**lowerCamelCase__		)






    def       _lowerCAmelCase (	self		):
        return self.set_src_lang_special_tokens(self.src_lang		)






    def       _lowerCAmelCase (	self		):
        return self.set_tgt_lang_special_tokens(self.tgt_lang		)






    def       _lowerCAmelCase (	self,		lowerCamelCase__		):
        A			:	Any										=       self.lang_code_to_id[src_lang]
        A			:	str										=       []
        A			:	Optional[Any]										=       [self.eos_token_id, self.cur_lang_code]






    def       _lowerCAmelCase (	self,		lowerCamelCase__		):
        A			:	int										=       self.lang_code_to_id[lang]
        A			:	Tuple										=       []
        A			:	List[Any]										=       [self.eos_token_id, self.cur_lang_code]







import argparse
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
SCREAMING_SNAKE_CASE_:Any					=						"""src/diffusers"""

# Matches is_xxx_available()
SCREAMING_SNAKE_CASE_:Optional[Any]					=						re.compile(R"""is\_([a-z_]*)_available\(\)""")
# Matches from xxx import bla
SCREAMING_SNAKE_CASE_:Union[str, Any]					=						re.compile(R"""\s+from\s+\S*\s+import\s+([^\(\s].*)\n""")


SCREAMING_SNAKE_CASE_:List[Any]					=						"""
{0} = None
"""

SCREAMING_SNAKE_CASE_:Optional[Any]					=						"""
class {0}(metaclass=DummyObject):
    _backends = {1}

    def __init__(self, *args, **kwargs):
        requires_backends(self, {1})

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, {1})

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, {1})
"""


SCREAMING_SNAKE_CASE_:int					=						"""
def {0}(*args, **kwargs):
    requires_backends({0}, {1})
"""




def      __UpperCamelCase     (  _lowerCAmelCase		)	->  Tuple:



    """simple docstring"""






    A			:	Union[str, Any]										=       _re_backend.findall(_lowerCAmelCase		)
    if len(_lowerCAmelCase		) == 0:
        return None

    return "_and_".join(_lowerCAmelCase		)




def      __UpperCamelCase     (  )	->  str:



    """simple docstring"""






    with open(os.path.join(_lowerCAmelCase				,					"""__init__.py"""		)				,					"""r"""				,					encoding="""utf-8"""				,					newline="""\n"""		) as f:
        A			:	Dict										=       f.readlines()

    # Get to the point we do the actual imports for type checking
    A			:	Dict										=       0
    A			:	List[Any]										=       {}
    # Go through the end of the file
    while line_index < len(_lowerCAmelCase		):
        # If the line contains is_backend_available, we grab all objects associated with the `else` block
        A			:	Optional[int]										=       find_backend(lines[line_index]		)
        if backend is not None:
            while not lines[line_index].startswith("""else:"""		):
                line_index += 1
            line_index += 1
            A			:	str										=       []
            # Until we unindent, add backend objects to the list
            while line_index < len(_lowerCAmelCase		) and len(lines[line_index]		) > 1:
                A			:	Tuple										=       lines[line_index]
                A			:	List[str]										=       _re_single_line_import.search(_lowerCAmelCase		)
                if single_line_import_search is not None:
                    objects.extend(single_line_import_search.groups()[0].split(""", """		)		)
                elif line.startswith(""" """ * 8		):
                    objects.append(line[8:-2]		)
                line_index += 1

            if len(_lowerCAmelCase		) > 0:
                A			:	List[str]										=       objects
        else:
            line_index += 1

    return backend_specific_objects




def      __UpperCamelCase     (  _lowerCAmelCase				,					_lowerCAmelCase		)	->  str:



    """simple docstring"""






    if name.isupper():
        return DUMMY_CONSTANT.format(_lowerCAmelCase		)
    elif name.islower():
        return DUMMY_FUNCTION.format(_lowerCAmelCase				,					_lowerCAmelCase		)
    else:
        return DUMMY_CLASS.format(_lowerCAmelCase				,					_lowerCAmelCase		)




def      __UpperCamelCase     (  _lowerCAmelCase=None		)	->  Tuple:



    """simple docstring"""






    if backend_specific_objects is None:
        A			:	Union[str, Any]										=       read_init()
    # For special correspondence backend to module name as used in the function requires_modulename
    A			:	Any										=       {}

    for backend, objects in backend_specific_objects.items():
        A			:	str										=       """[""" + """, """.join(f'''"{b}"''' for b in backend.split("""_and_"""		)		) + """]"""
        A			:	Any										=       """# This file is autogenerated by the command `make fix-copies`, do not edit.\n"""
        dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
        dummy_file += "\n".join([create_dummy_object(_lowerCAmelCase				,					_lowerCAmelCase		) for o in objects]		)
        A			:	Optional[Any]										=       dummy_file

    return dummy_files




def      __UpperCamelCase     (  _lowerCAmelCase=False		)	->  str:



    """simple docstring"""






    A			:	str										=       create_dummy_files()
    # For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
    A			:	List[str]										=       {"""torch""": """pt"""}

    # Locate actual dummy modules and read their content.
    A			:	Union[str, Any]										=       os.path.join(_lowerCAmelCase				,					"""utils"""		)
    A			:	Any										=       {
        backend: os.path.join(_lowerCAmelCase				,					f'''dummy_{short_names.get(_lowerCAmelCase				,					_lowerCAmelCase		)}_objects.py'''		)
        for backend in dummy_files.keys()
    }

    A			:	List[Any]										=       {}
    for backend, file_path in dummy_file_paths.items():
        if os.path.isfile(_lowerCAmelCase		):
            with open(_lowerCAmelCase				,					"""r"""				,					encoding="""utf-8"""				,					newline="""\n"""		) as f:
                A			:	Dict										=       f.read()
        else:
            A			:	str										=       """"""

    for backend in dummy_files.keys():
        if dummy_files[backend] != actual_dummies[backend]:
            if overwrite:
                print(
                    f'''Updating diffusers.utils.dummy_{short_names.get(_lowerCAmelCase				,					_lowerCAmelCase		)}_objects.py as the main '''
                    """__init__ has new objects."""		)
                with open(dummy_file_paths[backend]				,					"""w"""				,					encoding="""utf-8"""				,					newline="""\n"""		) as f:
                    f.write(dummy_files[backend]		)
            else:
                raise ValueError(
                    """The main __init__ has objects that are not present in """
                    f'''diffusers.utils.dummy_{short_names.get(_lowerCAmelCase				,					_lowerCAmelCase		)}_objects.py. Run `make fix-copies` '''
                    """to fix this."""		)


if __name__ == "__main__":
     SCREAMING_SNAKE_CASE_:List[Any]					=						argparse.ArgumentParser()
     parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
     SCREAMING_SNAKE_CASE_:Any					=						parser.parse_args()

     check_dummies(args.fix_and_overwrite)


