



import copy
import random

from transformers import CLIPTokenizer
class 			_lowerCAmelCase   ( _UpperCAmelCase			):






			"""simple docstring"""





			def __init__(				self	:       str			,     *lowercase	:       Tuple			,     **lowercase	:       Dict   )						->					Union[str, Any]:
									"""simple docstring"""







									super().__init__(*lowercase			,     **lowercase   )
									__lowercase					=				{}





			def 		snake_case__			(				self	:       str			,     lowercase	:       Optional[Any]			,     *lowercase	:       Union[str, Any]			,     **lowercase	:       List[str]   )						->					Tuple:
									"""simple docstring"""







									__lowercase					=				super().add_tokens(lowercase			,     *lowercase			,     **lowercase   )
									if num_added_tokens == 0:
															raise ValueError(
															    F"The tokenizer already contains the token {placeholder_token}. Please pass a different"
															    """ `placeholder_token` that is not already in the tokenizer."""   )





			def 		snake_case__			(				self	:       Optional[Any]			,     lowercase	:       int			,     *lowercase	:       Tuple			,     lowercase	:       Tuple=1			,     **lowercase	:       Optional[int]   )						->					int:
									"""simple docstring"""







									__lowercase					=				[]
									if num_vec_per_token == 1:
															self.try_adding_tokens(lowercase			,     *lowercase			,     **lowercase   )
															output.append(lowercase   )
									else:
															__lowercase					=				[]
															for i in range(lowercase   ):
																					__lowercase					=				placeholder_token + F"_{i}"
																					self.try_adding_tokens(lowercase			,     *lowercase			,     **lowercase   )
																					output.append(lowercase   )
        # handle cases where there is a new placeholder token that contains the current placeholder token but is larger
									for token in self.token_map:
															if token in placeholder_token:
																					raise ValueError(
																					    F"The tokenizer already has placeholder token {token} that can get confused with"
																					    F" {placeholder_token}keep placeholder tokens independent"   )
									__lowercase					=				output





			def 		snake_case__			(				self	:       str			,     lowercase	:       Optional[Any]			,     lowercase	:       List[Any]=False			,     lowercase	:       str=1.0   )						->					Optional[Any]:
									"""simple docstring"""







									if isinstance(lowercase			,     lowercase   ):
															__lowercase					=				[]
															for i in range(len(lowercase   )   ):
																					output.append(self.replace_placeholder_tokens_in_text(text[i]			,     vector_shuffle=lowercase   )   )
															return output
									for placeholder_token in self.token_map:
															if placeholder_token in text:
																					__lowercase					=				self.token_map[placeholder_token]
																					__lowercase					=				tokens[: 1 + int(len(lowercase   ) * prop_tokens_to_load   )]
																					if vector_shuffle:
																											__lowercase					=				copy.copy(lowercase   )
																											random.shuffle(lowercase   )
																					__lowercase					=				text.replace(lowercase			,     """ """.join(lowercase   )   )
									return text





			def __call__(				self	:       Tuple			,     lowercase	:       Optional[int]			,     *lowercase	:       Optional[int]			,     lowercase	:       Optional[int]=False			,     lowercase	:       List[str]=1.0			,     **lowercase	:       List[str]   )						->					Union[str, Any]:
									"""simple docstring"""







									return super().__call__(
									    self.replace_placeholder_tokens_in_text(
									        lowercase			,     vector_shuffle=lowercase			,     prop_tokens_to_load=lowercase   )			,     *lowercase			,     **lowercase			,     )







			def 		snake_case__			(				self	:       Union[str, Any]			,     lowercase	:       Dict			,     *lowercase	:       Tuple			,     lowercase	:       List[str]=False			,     lowercase	:       List[str]=1.0			,     **lowercase	:       Dict   )						->					Optional[Any]:
									"""simple docstring"""







									return super().encode(
									    self.replace_placeholder_tokens_in_text(
									        lowercase			,     vector_shuffle=lowercase			,     prop_tokens_to_load=lowercase   )			,     *lowercase			,     **lowercase			,     )










import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union

import torch

from ..utils import BaseOutput


UpperCamelCase__ =						"scheduler_config.json"
class 			_lowerCAmelCase   ( _UpperCAmelCase			):






			"""simple docstring"""





			lowercase__      :  List[Any]      =			1
			lowercase__      :  Tuple      =			2
			lowercase__      :  Union[str, Any]      =			3
			lowercase__      :  Union[str, Any]      =			4
			lowercase__      :  str      =			5
			lowercase__      :  Any      =			6
			lowercase__      :  Any      =			7
			lowercase__      :  List[str]      =			8
			lowercase__      :  Union[str, Any]      =			9
			lowercase__      :  int      =			10
			lowercase__      :  List[str]      =			11
			lowercase__      :  List[Any]      =			12
			lowercase__      :  str      =			13
			lowercase__      :  Optional[int]      =			14





@dataclass
class 			_lowerCAmelCase   ( _UpperCAmelCase			):






			"""simple docstring"""





			lowercase__      :  torch.FloatTensor





class 			_lowerCAmelCase   :






			"""simple docstring"""





			lowercase__      :  Optional[int]      =			SCHEDULER_CONFIG_NAME
			lowercase__      :  int      =			[]
			lowercase__      :  Dict      =			True





			@classmethod
			def 		snake_case__			(				cls	:       str			,     lowercase	:       Dict[str, Any] = None			,     lowercase	:       Optional[str] = None			,     lowercase	:       Any=False			,     **lowercase	:       List[str]			,     )						->					Union[str, Any]:
									"""simple docstring"""







									__lowercase	,			__lowercase	,			__lowercase					=				cls.load_config(
									    pretrained_model_name_or_path=lowercase			,     subfolder=lowercase			,     return_unused_kwargs=lowercase			,     return_commit_hash=lowercase			,     **lowercase			,     )
									return cls.from_config(lowercase			,     return_unused_kwargs=lowercase			,     **lowercase   )





			def 		snake_case__			(				self	:       Dict			,     lowercase	:       Union[str, os.PathLike]			,     lowercase	:       bool = False			,     **lowercase	:       List[str]   )						->					Optional[Any]:
									"""simple docstring"""







									self.save_config(save_directory=lowercase			,     push_to_hub=lowercase			,     **lowercase   )





			@property
			def 		snake_case__			(				self	:       Optional[Any]   )						->					Dict:
									"""simple docstring"""







									return self._get_compatibles()







			@classmethod
			def 		snake_case__			(				cls	:       List[str]   )						->					Union[str, Any]:
									"""simple docstring"""







									__lowercase					=				list(set([cls.__name__] + cls._compatibles   )   )
									__lowercase					=				importlib.import_module(__name__.split("""."""   )[0]   )
									__lowercase					=				[
									    getattr(lowercase			,     lowercase   ) for c in compatible_classes_str if hasattr(lowercase			,     lowercase   )
									]
									return compatible_classes





