



from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_clip import CLIPTokenizer


_lowercase:					List[str]      =						logging.get_logger(__name__)

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

_lowercase:					List[str]      =						{
    "vocab_file": {
        "openai/clip-vit-base-patch32": "https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/vocab.json",
    },
    "merges_file": {
        "openai/clip-vit-base-patch32": "https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "openai/clip-vit-base-patch32": (
            "https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/tokenizer.json"
        ),
    },
}

_lowercase:					Optional[int]      =						{
    "openai/clip-vit-base-patch32": 77,
}



class       _lowercase				(  lowerCAmelCase      ):





	"""simple docstring"""
	__A		      =				VOCAB_FILES_NAMES
	__A		      =				PRETRAINED_VOCAB_FILES_MAP
	__A		      =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	__A		      =				["input_ids", "attention_mask"]
	__A		      =				CLIPTokenizer




	def __init__(self						,			lowerCamelCase_=None						,			lowerCamelCase_=None						,			lowerCamelCase_=None						,			lowerCamelCase_="<|endoftext|>"						,			lowerCamelCase_="<|startoftext|>"						,			lowerCamelCase_="<|endoftext|>"						,			lowerCamelCase_="<|endoftext|>"						,			**lowerCamelCase_						,			):
						"""simple docstring"""

						super().__init__(
						    lowerCamelCase_						,			lowerCamelCase_						,			tokenizer_file=lowerCamelCase_						,			unk_token=lowerCamelCase_						,			bos_token=lowerCamelCase_						,			eos_token=lowerCamelCase_						,			pad_token=lowerCamelCase_						,			**lowerCamelCase_						,			)

						if not isinstance(self.backend_tokenizer.pre_tokenizer						,			pre_tokenizers.Sequence						):
											raise ValueError(
											    "The `backend_tokenizer` provided does not match the expected format. The CLIP tokenizer has been"
											    " heavily modified from transformers version 4.17.0. You need to convert the tokenizer you are using"
											    " to be compatible with this version.The easiest way to do so is"
											    " `CLIPTokenizerFast.from_pretrained(\"path_to_local_folder_or_hub_repo, from_slow=True)`. If you want"
											    " to use your existing tokenizer, you will have to revert to a version prior to 4.17.0 of"
											    " transformers."						)

						self._wrap_decode_method_backend_tokenizer()




	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

						a   	=  self.backend_tokenizer.decode

						def new_decode_method(*lowerCamelCase_						,			**lowerCamelCase_						):
											a   	=  orig_decode_method(*lowerCamelCase_						,			**lowerCamelCase_						)
											a   	=  text.replace(self.backend_tokenizer.model.end_of_word_suffix						,			" "						).strip()
											return text

						a   	=  new_decode_method




	def 	UpperCamelCase_			(self						,			lowerCamelCase_						,			lowerCamelCase_ = None						):
						"""simple docstring"""

						a   	=  [self.bos_token_id]
						a   	=  [self.eos_token_id]

						if token_ids_a is None:
											return bos_token + token_ids_a + eos_token
						return bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token




	def 	UpperCamelCase_			(self						,			lowerCamelCase_						,			lowerCamelCase_ = None						):
						"""simple docstring"""

						a   	=  [self.bos_token_id]
						a   	=  [self.eos_token_id]

						if token_ids_a is None:
											return len(bos_token + token_ids_a + eos_token						) * [0]
						return len(bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token						) * [0]




	def 	UpperCamelCase_			(self						,			lowerCamelCase_						,			lowerCamelCase_ = None						):
						"""simple docstring"""

						a   	=  self._tokenizer.model.save(lowerCamelCase_						,			name=lowerCamelCase_						)
						return tuple(lowerCamelCase_						)





from .pipeline_kandinskya_a import KandinskyVaaPipeline
from .pipeline_kandinsky2_2_controlnet import KandinskyVaaControlnetPipeline
from .pipeline_kandinsky2_2_controlnet_img2img import KandinskyVaaControlnetImgaImgPipeline
from .pipeline_kandinsky2_2_img2img import KandinskyVaaImgaImgPipeline
from .pipeline_kandinsky2_2_inpainting import KandinskyVaaInpaintPipeline
from .pipeline_kandinsky2_2_prior import KandinskyVaaPriorPipeline
from .pipeline_kandinsky2_2_prior_emb2emb import KandinskyVaaPriorEmbaEmbPipeline
