





'''simple docstring'''






from typing import Dict, List, Optional

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


lowerCAmelCase       		=      logging.get_logger(__name__)


lowerCAmelCase       		=      {
    """nielsr/canine-s""": 20_48,
}

# Unicode defines 1,114,112 total “codepoints”
lowerCAmelCase       		=      1_11_41_12

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

lowerCAmelCase       		=      0XE_0_0_0
lowerCAmelCase       		=      0XE_0_0_1
lowerCAmelCase       		=      0XE_0_0_2
lowerCAmelCase       		=      0XE_0_0_3
lowerCAmelCase       		=      0XE_0_0_4

# Maps special codepoints to human-readable names.
lowerCAmelCase       		=      {
    # 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.
lowerCAmelCase       		=      {name: codepoint for codepoint, name in SPECIAL_CODEPOINTS.items()}
class 		lowerCamelCase  (      _A       ):
	snake_case_      =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES



	def __init__(   self		,      a_=chr(a_	)		,      a_=chr(a_	)		,      a_=chr(a_	)		,      a_=chr(a_	)		,      a_=chr(a_	)		,      a_=chr(a_	)		,      a_=False		,      a_=2_048		,      **a_		,      ):
			lowerCAmelCase     :    Union[str, Any]						=   AddedToken(a_		,      lstrip=a_		,      rstrip=a_	) if isinstance(a_		,      a_	) else bos_token
			lowerCAmelCase     :    Tuple						=   AddedToken(a_		,      lstrip=a_		,      rstrip=a_	) if isinstance(a_		,      a_	) else eos_token
			lowerCAmelCase     :    Optional[Any]						=   AddedToken(a_		,      lstrip=a_		,      rstrip=a_	) if isinstance(a_		,      a_	) else sep_token
			lowerCAmelCase     :    Dict						=   AddedToken(a_		,      lstrip=a_		,      rstrip=a_	) if isinstance(a_		,      a_	) else cls_token
			lowerCAmelCase     :    List[str]						=   AddedToken(a_		,      lstrip=a_		,      rstrip=a_	) if isinstance(a_		,      a_	) else pad_token

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

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

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

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

			lowerCAmelCase     :    List[Any]						=   UNICODE_VOCAB_SIZE
			lowerCAmelCase     :    Any						=   len(self._special_codepoints	)



	@property
	def   _lowerCamelCase    (   self	):
			return self._unicode_vocab_size



	def   _lowerCamelCase    (   self		,      a_	):
			return list(a_	)



	def   _lowerCamelCase    (   self		,      a_	):
			try:
					return ord(a_	)
			except TypeError:
					raise ValueError(F'''invalid token: \'{token}\''''	)



	def   _lowerCamelCase    (   self		,      a_	):
			try:
					if index in SPECIAL_CODEPOINTS:
							return SPECIAL_CODEPOINTS[index]
					return chr(a_	)
			except TypeError:
					raise ValueError(F'''invalid id: {index}'''	)



	def   _lowerCamelCase    (   self		,      a_	):
			return "".join(a_	)



	def   _lowerCamelCase    (   self		,      a_		,      a_ = None	):
			lowerCAmelCase     :    Union[str, Any]						=   [self.sep_token_id]
			lowerCAmelCase     :    Any						=   [self.cls_token_id]

			lowerCAmelCase     :    str						=   cls + token_ids_a + sep
			if token_ids_a is not None:
					result += token_ids_a + sep
			return result



	def   _lowerCamelCase    (   self		,      a_		,      a_ = None		,      a_ = False	):
			if already_has_special_tokens:
					return super().get_special_tokens_mask(
					    token_ids_a=a_		,      token_ids_a=a_		,      already_has_special_tokens=a_	)

			lowerCAmelCase     :    Union[str, Any]						=   [1] + ([0] * len(a_	)) + [1]
			if token_ids_a is not None:
					result += ([0] * len(a_	)) + [1]
			return result



	def   _lowerCamelCase    (   self		,      a_		,      a_ = None	):
			lowerCAmelCase     :    Any						=   [self.sep_token_id]
			lowerCAmelCase     :    int						=   [self.cls_token_id]

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





	def   _lowerCamelCase    (   self		,      a_		,      a_ = None	):
			return ()










'''simple docstring'''






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


try:
					if not (is_transformers_available() and is_torch_available()):
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					from ...utils.dummy_torch_and_transformers_objects import KandinskyPipeline, KandinskyPriorPipeline
else:
					from .pipeline_kandinsky import KandinskyPipeline
					from .pipeline_kandinsky_imgaimg import KandinskyImgaImgPipeline
					from .pipeline_kandinsky_inpaint import KandinskyInpaintPipeline
					from .pipeline_kandinsky_prior import KandinskyPriorPipeline, KandinskyPriorPipelineOutput
					from .text_encoder import MultilingualCLIP



