





from typing import Dict, List, Optional

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


SCREAMING_SNAKE_CASE__							:      Tuple         =    logging.get_logger(__name__)


SCREAMING_SNAKE_CASE__							:      Any         =    {
    """nielsr/canine-s""": 2_0_4_8,
}

# Unicode defines 1,114,112 total “codepoints”
SCREAMING_SNAKE_CASE__							:      Any         =    1_1_1_4_1_1_2

# Below: Constants defining canonical codepoints for special, pseudo-characters.
# Copied from https://github.com/google-research/language/blob/master/language/canine/special_codepoints.py
SCREAMING_SNAKE_CASE__							:      Optional[Any]         =    0

SCREAMING_SNAKE_CASE__							:      int         =    0XE_0_0_0
SCREAMING_SNAKE_CASE__							:      Tuple         =    0XE_0_0_1
SCREAMING_SNAKE_CASE__							:      str         =    0XE_0_0_2
SCREAMING_SNAKE_CASE__							:      Dict         =    0XE_0_0_3
SCREAMING_SNAKE_CASE__							:      Any         =    0XE_0_0_4

# Maps special codepoints to human-readable names.
SCREAMING_SNAKE_CASE__							:      Dict[int, str]         =    {
    # Special symbols are represented using codepoints values that are valid,
    # but designated as "Private Use", meaning that they will never be assigned
    # characters by the Unicode Consortium, and are thus safe for use here.
    #
    # NOTE: Do *NOT* add any sort of [UNK_CHAR] here. They are explicitly
    # excluded and should fail with a hard error.
    CLS: "[CLS]",
    SEP: "[SEP]",
    BOS: "[BOS]",
    MASK: "[MASK]",
    PAD: "[PAD]",
    RESERVED: "[RESERVED]",
}

# Maps special codepoint human-readable names to their codepoint values.
SCREAMING_SNAKE_CASE__							:      Dict[str, int]         =    {name: codepoint for codepoint, name in SPECIAL_CODEPOINTS.items()}







class 	__lowerCAmelCase      (       _UpperCamelCase	):
   _UpperCamelCase			:    Dict  		=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES





   def __init__(			self       ,      snake_case=chr(snake_case   )       ,      snake_case=chr(snake_case   )       ,      snake_case=chr(snake_case   )       ,      snake_case=chr(snake_case   )       ,      snake_case=chr(snake_case   )       ,      snake_case=chr(snake_case   )       ,      snake_case=False       ,      snake_case=2_048       ,      **snake_case       ,      )					->	Any:
      """simple docstring"""





      a__						:    List[str]   		=	AddedToken(snake_case       ,      lstrip=snake_case       ,      rstrip=snake_case   ) if isinstance(snake_case       ,      snake_case   ) else bos_token
      a__						:    Dict   		=	AddedToken(snake_case       ,      lstrip=snake_case       ,      rstrip=snake_case   ) if isinstance(snake_case       ,      snake_case   ) else eos_token
      a__						:    Union[str, Any]   		=	AddedToken(snake_case       ,      lstrip=snake_case       ,      rstrip=snake_case   ) if isinstance(snake_case       ,      snake_case   ) else sep_token
      a__						:    List[Any]   		=	AddedToken(snake_case       ,      lstrip=snake_case       ,      rstrip=snake_case   ) if isinstance(snake_case       ,      snake_case   ) else cls_token
      a__						:    Optional[Any]   		=	AddedToken(snake_case       ,      lstrip=snake_case       ,      rstrip=snake_case   ) if isinstance(snake_case       ,      snake_case   ) else pad_token

      # Mask token behave like a normal word, i.e. include the space before it
      a__						:    int   		=	AddedToken(snake_case       ,      lstrip=snake_case       ,      rstrip=snake_case   ) if isinstance(snake_case       ,      snake_case   ) else mask_token

      super().__init__(
          bos_token=snake_case       ,      eos_token=snake_case       ,      sep_token=snake_case       ,      cls_token=snake_case       ,      pad_token=snake_case       ,      mask_token=snake_case       ,      add_prefix_space=snake_case       ,      model_max_length=snake_case       ,      **snake_case       ,      )

      # Creates a mapping for looking up the IDs of special symbols.
      a__						:    Dict[str, int]   		=	{}
      for codepoint, name in SPECIAL_CODEPOINTS.items():
         a__						:    List[str]   		=	codepoint

      # Creates a mapping for looking up the string forms of special symbol IDs.
      a__						:    Dict[int, str]   		=	{
          codepoint: name for name, codepoint in self._special_codepoints.items()
      }

      a__						:    Tuple   		=	UNICODE_VOCAB_SIZE
      a__						:    Tuple   		=	len(self._special_codepoints   )





   @property
   def 						_snake_case			(			self   )					->	int:
      """simple docstring"""





      return self._unicode_vocab_size





   def 						_snake_case			(			self       ,      snake_case   )					->	List[str]:
      """simple docstring"""





      return list(snake_case   )





   def 						_snake_case			(			self       ,      snake_case   )					->	int:
      """simple docstring"""





      try:
         return ord(snake_case   )
      except TypeError:
         raise ValueError(F"""invalid token: '{token}'"""   )





   def 						_snake_case			(			self       ,      snake_case   )					->	str:
      """simple docstring"""





      try:
         if index in SPECIAL_CODEPOINTS:
            return SPECIAL_CODEPOINTS[index]
         return chr(snake_case   )
      except TypeError:
         raise ValueError(F"""invalid id: {index}"""   )





   def 						_snake_case			(			self       ,      snake_case   )					->	Optional[Any]:
      """simple docstring"""





      return "".join(snake_case   )





   def 						_snake_case			(			self       ,      snake_case       ,      snake_case = None   )					->	List[int]:
      """simple docstring"""





      a__						:    Any   		=	[self.sep_token_id]
      a__						:    Dict   		=	[self.cls_token_id]

      a__						:    Optional[int]   		=	cls + token_ids_a + sep
      if token_ids_a is not None:
         result += token_ids_a + sep
      return result





   def 						_snake_case			(			self       ,      snake_case       ,      snake_case = None       ,      snake_case = False   )					->	List[int]:
      """simple docstring"""





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

      a__						:    str   		=	[1] + ([0] * len(snake_case   )) + [1]
      if token_ids_a is not None:
         result += ([0] * len(snake_case   )) + [1]
      return result





   def 						_snake_case			(			self       ,      snake_case       ,      snake_case = None   )					->	List[int]:
      """simple docstring"""





      a__						:    str   		=	[self.sep_token_id]
      a__						:    Union[str, Any]   		=	[self.cls_token_id]

      a__						:    Tuple   		=	len(cls + token_ids_a + sep   ) * [0]
      if token_ids_a is not None:
         result += len(token_ids_a + sep   ) * [1]
      return result





   def 						_snake_case			(			self       ,      snake_case       ,      snake_case = None   )					->	Optional[Any]:
      """simple docstring"""





      return ()








from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
  if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ...utils.dummy_torch_and_transformers_objects import (
      VersatileDiffusionDualGuidedPipeline,
      VersatileDiffusionImageVariationPipeline,
      VersatileDiffusionPipeline,
      VersatileDiffusionTextToImagePipeline,
  )
else:
  from .modeling_text_unet import UNetFlatConditionModel
  from .pipeline_versatile_diffusion import VersatileDiffusionPipeline
  from .pipeline_versatile_diffusion_dual_guided import VersatileDiffusionDualGuidedPipeline
  from .pipeline_versatile_diffusion_image_variation import VersatileDiffusionImageVariationPipeline
  from .pipeline_versatile_diffusion_text_to_image import VersatileDiffusionTextToImagePipeline

