



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
_snake_case		=  "src/diffusers"

# Matches is_xxx_available()
_snake_case		=  re.compile(R"is\_([a-z_]*)_available\(\)")
# Matches from xxx import bla
_snake_case		=  re.compile(R"\s+from\s+\S*\s+import\s+([^\(\s].*)\n")


_snake_case		=  "\n{0} = None\n"

_snake_case		=  "\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n"


_snake_case		=  "\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n"






def 				A				(					_lowerCamelCase  ):





							'''simple docstring'''




							_lowerCAmelCase     :							Tuple    =    _re_backend.findall(_lowerCamelCase  )
							if len(_lowerCamelCase  ) == 0:
														return None

							return "_and_".join(_lowerCamelCase  )






def 				A				(					):





							'''simple docstring'''




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

							# Get to the point we do the actual imports for type checking
							_lowerCAmelCase     :							Dict    =    0
							_lowerCAmelCase     :							Optional[int]    =    {}
							# 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
														_lowerCAmelCase     :							str    =    find_backend(lines[line_index]  )
														if backend is not None:
																					while not lines[line_index].startswith("else:"  ):
																												line_index += 1
																					line_index += 1
																					_lowerCAmelCase     :							Tuple    =    []
																					# Until we unindent, add backend objects to the list
																					while line_index < len(_lowerCamelCase  ) and len(lines[line_index]  ) > 1:
																												_lowerCAmelCase     :							List[Any]    =    lines[line_index]
																												_lowerCAmelCase     :							Optional[Any]    =    _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:
																												_lowerCAmelCase     :							List[Any]    =    objects
														else:
																					line_index += 1

							return backend_specific_objects






def 				A				(					_lowerCamelCase				, _lowerCamelCase  ):





							'''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 				A				(					_lowerCamelCase=None  ):





							'''simple docstring'''




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

							for backend, objects in backend_specific_objects.items():
														_lowerCAmelCase     :							int    =    "[" + ", ".join(F"\"{b}\"" for b in backend.split("_and_"  )  ) + "]"
														_lowerCAmelCase     :							int    =    "# 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]  )
														_lowerCAmelCase     :							Dict    =    dummy_file

							return dummy_files






def 				A				(					_lowerCamelCase=False  ):





							'''simple docstring'''




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

							# Locate actual dummy modules and read their content.
							_lowerCAmelCase     :							Optional[int]    =    os.path.join(_lowerCamelCase				, "utils"  )
							_lowerCAmelCase     :							Tuple    =    {
							    backend: os.path.join(_lowerCamelCase				, F"dummy_{short_names.get(_lowerCamelCase				, _lowerCamelCase  )}_objects.py"  )
							    for backend in dummy_files.keys()
							}

							_lowerCAmelCase     :							Tuple    =    {}
							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:
																												_lowerCAmelCase     :							Dict    =    f.read()
														else:
																					_lowerCAmelCase     :							Any    =    ""

							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__":
						_snake_case		=  argparse.ArgumentParser()
						parser.add_argument("--fix_and_overwrite", action="store_true", help="Whether to fix inconsistencies.")
						_snake_case		=  parser.parse_args()

						check_dummies(args.fix_and_overwrite)



"""simple docstring"""


import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer


__A						   =			logging.get_logger(__name__)

__A						   =			{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

__A						   =			{
    "vocab_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/vocab.json",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/vocab.json",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/vocab.json",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/merges.txt",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/merges.txt",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/merges.txt",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt"
        ),
    },
    "tokenizer_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/tokenizer.json",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/tokenizer.json",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json",
        "roberta-base-openai-detector": (
            "https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json"
        ),
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json"
        ),
    },
}

__A						   =			{
    "roberta-base": 512,
    "roberta-large": 512,
    "roberta-large-mnli": 512,
    "distilroberta-base": 512,
    "roberta-base-openai-detector": 512,
    "roberta-large-openai-detector": 512,
}





class     snake_case	(				__snake_case  ):
				SCREAMING_SNAKE_CASE_   :      str         =  VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_   :      Optional[Any]         =  PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_   :      Optional[int]         =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_   :      Optional[int]         =  ["""input_ids""", """attention_mask"""]
				SCREAMING_SNAKE_CASE_   :      Any         =  RobertaTokenizer

				def __init__(	self							:				Optional[int]     ,  UpperCamelCase__							:				int=None     ,  UpperCamelCase__							:				Union[str, Any]=None     ,  UpperCamelCase__							:				Optional[Any]=None     ,  UpperCamelCase__							:				int="replace"     ,  UpperCamelCase__							:				Union[str, Any]="<s>"     ,  UpperCamelCase__							:				List[Any]="</s>"     ,  UpperCamelCase__							:				Any="</s>"     ,  UpperCamelCase__							:				Union[str, Any]="<s>"     ,  UpperCamelCase__							:				str="<unk>"     ,  UpperCamelCase__							:				Optional[int]="<pad>"     ,  UpperCamelCase__							:				int="<mask>"     ,  UpperCamelCase__							:				Optional[int]=False     ,  UpperCamelCase__							:				Optional[Any]=True     ,  **UpperCamelCase__							:				Tuple     ,  )->   Optional[int]:



						'''simple docstring'''


						super().__init__(
						    UpperCamelCase__     ,  UpperCamelCase__     ,  tokenizer_file=UpperCamelCase__     ,  errors=UpperCamelCase__     ,  bos_token=UpperCamelCase__     ,  eos_token=UpperCamelCase__     ,  sep_token=UpperCamelCase__     ,  cls_token=UpperCamelCase__     ,  unk_token=UpperCamelCase__     ,  pad_token=UpperCamelCase__     ,  mask_token=UpperCamelCase__     ,  add_prefix_space=UpperCamelCase__     ,  trim_offsets=UpperCamelCase__     ,  **UpperCamelCase__     ,  )

						__lowerCAmelCase:       Tuple          =			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
						if pre_tok_state.get("add_prefix_space"     ,  UpperCamelCase__) != add_prefix_space:
								__lowerCAmelCase:       str          =			getattr(UpperCamelCase__     ,  pre_tok_state.pop("type"))
								__lowerCAmelCase:       Optional[int]          =			add_prefix_space
								__lowerCAmelCase:       Dict          =			pre_tok_class(**UpperCamelCase__)

						__lowerCAmelCase:       Any          =			add_prefix_space

						__lowerCAmelCase:       int          =			"post_processor"
						__lowerCAmelCase:       Optional[Any]          =			getattr(self.backend_tokenizer     ,  UpperCamelCase__     ,  UpperCamelCase__)
						if tokenizer_component_instance:
								__lowerCAmelCase:       Dict          =			json.loads(tokenizer_component_instance.__getstate__())

								# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
								if "sep" in state:
										__lowerCAmelCase:       List[Any]          =			tuple(state["sep"])
								if "cls" in state:
										__lowerCAmelCase:       str          =			tuple(state["cls"])

								__lowerCAmelCase:       str          =			False

								if state.get("add_prefix_space"     ,  UpperCamelCase__) != add_prefix_space:
										__lowerCAmelCase:       Optional[Any]          =			add_prefix_space
										__lowerCAmelCase:       List[str]          =			True

								if state.get("trim_offsets"     ,  UpperCamelCase__) != trim_offsets:
										__lowerCAmelCase:       Any          =			trim_offsets
										__lowerCAmelCase:       List[str]          =			True

								if changes_to_apply:
										__lowerCAmelCase:       str          =			getattr(UpperCamelCase__     ,  state.pop("type"))
										__lowerCAmelCase:       List[str]          =			component_class(**UpperCamelCase__)
										setattr(self.backend_tokenizer     ,  UpperCamelCase__     ,  UpperCamelCase__)

				@property
				def 							lowercase_     (	self							:				List[str])->   str:



						'''simple docstring'''


						if self._mask_token is None:
								if self.verbose:
										logger.error("Using mask_token, but it is not set yet.")
								return None
						return str(self._mask_token)

				@mask_token.setter
				def 							lowercase_     (	self							:				Tuple     ,  UpperCamelCase__							:				Optional[int])->   Optional[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       List[Any]          =			AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__     ,  UpperCamelCase__) else value
						__lowerCAmelCase:       int          =			value

				def 							lowercase_     (	self							:				Any     ,  *UpperCamelCase__							:				str     ,  **UpperCamelCase__							:				List[Any])->   BatchEncoding:



						'''simple docstring'''


						__lowerCAmelCase:       List[Any]          =			kwargs.get("is_split_into_words"     ,  UpperCamelCase__)
						assert self.add_prefix_space or not is_split_into_words, (
						    f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
						    "to use it with pretokenized inputs."
						)

						return super()._batch_encode_plus(*UpperCamelCase__     ,  **UpperCamelCase__)

				def 							lowercase_     (	self							:				int     ,  *UpperCamelCase__							:				Dict     ,  **UpperCamelCase__							:				List[str])->   BatchEncoding:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[Any]          =			kwargs.get("is_split_into_words"     ,  UpperCamelCase__)

						assert self.add_prefix_space or not is_split_into_words, (
						    f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
						    "to use it with pretokenized inputs."
						)

						return super()._encode_plus(*UpperCamelCase__     ,  **UpperCamelCase__)

				def 							lowercase_     (	self							:				Any     ,  UpperCamelCase__							:				str     ,  UpperCamelCase__							:				Optional[str] = None)->   Tuple[str]:



						'''simple docstring'''


						__lowerCAmelCase:       str          =			self._tokenizer.model.save(UpperCamelCase__     ,  name=UpperCamelCase__)
						return tuple(UpperCamelCase__)

				def 							lowercase_     (	self							:				Dict     ,  UpperCamelCase__							:				Any     ,  UpperCamelCase__							:				Union[str, Any]=None)->   Optional[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       str          =			[self.bos_token_id] + token_ids_a + [self.eos_token_id]
						if token_ids_a is None:
								return output

						return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]




				def 							lowercase_     (	self							:				int     ,  UpperCamelCase__							:				List[int]     ,  UpperCamelCase__							:				Optional[List[int]] = None)->   List[int]:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[Any]          =			[self.sep_token_id]
						__lowerCAmelCase:       str          =			[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]


