
'''simple docstring'''
import argparse

from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection

from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline


if __name__ == "__main__":
		lowercase__											=argparse.ArgumentParser()

		parser.add_argument('--dump_path', default=None, type=str, required=True, help='Path to the output model.')

		parser.add_argument(
		    '--txt2img_unclip',
		    default='kakaobrain/karlo-v1-alpha',
		    type=str,
		    required=False,
		    help='The pretrained txt2img unclip.',
		)

		lowercase__											=parser.parse_args()

		lowercase__											=UnCLIPPipeline.from_pretrained(args.txtaimg_unclip)

		lowercase__											=CLIPImageProcessor()
		lowercase__											=CLIPVisionModelWithProjection.from_pretrained('openai/clip-vit-large-patch14')

		lowercase__											=UnCLIPImageVariationPipeline(
		    decoder=txtaimg.decoder,
		    text_encoder=txtaimg.text_encoder,
		    tokenizer=txtaimg.tokenizer,
		    text_proj=txtaimg.text_proj,
		    feature_extractor=feature_extractor,
		    image_encoder=image_encoder,
		    super_res_first=txtaimg.super_res_first,
		    super_res_last=txtaimg.super_res_last,
		    decoder_scheduler=txtaimg.decoder_scheduler,
		    super_res_scheduler=txtaimg.super_res_scheduler,
		)

		imgaimg.save_pretrained(args.dump_path)


'''simple docstring'''
import json
import os
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowercase__											=logging.get_logger(__name__)


lowercase__											={
    'vocab_file': 'vocab.json',
    'tokenizer_config_file': 'tokenizer_config.json',
    'merges_file': 'merges.txt',
}

lowercase__											={
    'vocab_file': {
        'facebook/s2t-wav2vec2-large-en-de': (
            'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json'
        ),
    },
    'tokenizer_config_file': {
        'facebook/s2t-wav2vec2-large-en-de': (
            'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json'
        ),
    },
    'merges_file': {
        'facebook/s2t-wav2vec2-large-en-de': (
            'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt'
        ),
    },
}

lowercase__											='</w>'
lowercase__											='@@ '






def      UpperCamelCase_				(      A__						):
	a_      				=						set()
	a_      				=						word[0]
	for char in word[1:]:
		pairs.add((prev_char, char)						)
		a_      				=						char
	return pairs


# Speech2Text2 has no max input length
lowercase__											={'facebook/s2t-wav2vec2-large-en-de': 10_24}







class   a_ (      UpperCamelCase__					):
			lowerCamelCase__	:			List[str]       =    VOCAB_FILES_NAMES
			lowerCamelCase__	:			Optional[Any]       =    PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase__	:			List[Any]       =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase__	:			int       =    ['input_ids', 'attention_mask']




			def __init__(       self					,   UpperCAmelCase					,   UpperCAmelCase="<s>"					,   UpperCAmelCase="<pad>"					,   UpperCAmelCase="</s>"					,   UpperCAmelCase="<unk>"					,   UpperCAmelCase=False					,   UpperCAmelCase=None					,   **UpperCAmelCase					,   ):
				super().__init__(
				    unk_token=UpperCAmelCase					,   bos_token=UpperCAmelCase					,   eos_token=UpperCAmelCase					,   pad_token=UpperCAmelCase					,   do_lower_case=UpperCAmelCase					,   **UpperCAmelCase					,   )

				a_      				=						do_lower_case

				with open(UpperCAmelCase					,   encoding="""utf-8"""	) as vocab_handle:
					a_      				=						json.load(UpperCAmelCase	)
				a_      				=						{v: k for k, v in self.encoder.items()}

				if merges_file is None:
					logger.info(f'''No merges files provided. {self.__class__.__name__} can only be used for decoding.'''	)

					a_      				=						None
					a_      				=						None
				else:
					with open(UpperCAmelCase					,   encoding="""utf-8"""	) as merges_handle:
						a_      				=						merges_handle.read().split("""\n"""	)[:-1]

					a_      				=						[tuple(merge.split()[:2]	) for merge in merges]
					a_      				=						dict(zip(UpperCAmelCase					,   range(len(UpperCAmelCase	)	)	)	)
					a_      				=						{}




			@property
			def 					lowerCAmelCase__					(       self	):
				return len(self.decoder	)




			def 					lowerCAmelCase__					(       self	):
				return dict(self.encoder					,   **self.added_tokens_encoder	)




			def 					lowerCAmelCase__					(       self					,   UpperCAmelCase	):
				a_      				=						tuple(token[:-1]	) + (token[-1] + BPE_TOKEN_MERGES,)
				if token in self.cache:
					return self.cache[token]
				a_      				=						get_pairs(UpperCAmelCase	)

				if not pairs:
					return token

				while True:
					a_      				=						min(UpperCAmelCase					,   key=lambda UpperCAmelCase	: self.bpe_ranks.get(UpperCAmelCase					,   float("""inf"""	)	)	)
					if bigram not in self.bpe_ranks:
						break
					a_				,  a_      				=						bigram
					a_      				=						[]
					a_      				=						0
					while i < len(UpperCAmelCase	):
						try:
							a_      				=						word.index(UpperCAmelCase					,   UpperCAmelCase	)
						except ValueError:
							new_word.extend(word[i:]	)
							break
						else:
							new_word.extend(word[i:j]	)
							a_      				=						j

						if word[i] == first and i < len(UpperCAmelCase	) - 1 and word[i + 1] == second:
							new_word.append(first + second	)
							i += 2
						else:
							new_word.append(word[i]	)
							i += 1
					a_      				=						tuple(UpperCAmelCase	)
					a_      				=						new_word
					if len(UpperCAmelCase	) == 1:
						break
					else:
						a_      				=						get_pairs(UpperCAmelCase	)
				a_      				=						""" """.join(UpperCAmelCase	)
				if word == "\n  " + BPE_TOKEN_MERGES:
					a_      				=						"""\n""" + BPE_TOKEN_MERGES

				if word.endswith(UpperCAmelCase	):
					a_      				=						word.replace(UpperCAmelCase					,   """"""	)

				a_      				=						word.replace(""" """					,   UpperCAmelCase	)
				a_      				=						word
				return word




			def 					lowerCAmelCase__					(       self					,   UpperCAmelCase	):

				if self.bpe_ranks is None:
					raise ValueError(
					    """This tokenizer was instantiated without a `merges.txt` file, so"""
					    """ that it can only be used for decoding, not for encoding."""
					    """Make sure to provide `merges.txt` file at instantiation to enable """
					    """encoding."""	)

				if self.do_lower_case:
					a_      				=						text.lower()

				a_      				=						text.split()

				a_      				=						[]
				for token in text:
					if token:
						split_tokens.extend(list(self.bpe(UpperCAmelCase	).split(""" """	)	)	)

				return split_tokens




			def 					lowerCAmelCase__					(       self					,   UpperCAmelCase	):
				return self.encoder.get(UpperCAmelCase					,   self.encoder.get(self.unk_token	)	)




			def 					lowerCAmelCase__					(       self					,   UpperCAmelCase	):
				a_      				=						self.decoder.get(UpperCAmelCase					,   self.unk_token	)
				return result




			def 					lowerCAmelCase__					(       self					,   UpperCAmelCase	):
				a_      				=						""" """.join(UpperCAmelCase	)

				# make sure @@ tokens are concatenated
				a_      				=						"""""".join(string.split(UpperCAmelCase	)	)

				return string






			def 					lowerCAmelCase__					(       self					,   UpperCAmelCase					,   UpperCAmelCase = None	):
				if not os.path.isdir(UpperCAmelCase	):
					logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''	)
					return
				a_      				=						os.path.join(
				    UpperCAmelCase					,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]	)
				a_      				=						os.path.join(
				    UpperCAmelCase					,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]	)

				with open(UpperCAmelCase					,   """w"""					,   encoding="""utf-8"""	) as f:
					f.write(json.dumps(self.encoder					,   indent=2					,   sort_keys=UpperCAmelCase					,   ensure_ascii=UpperCAmelCase	) + """\n"""	)

				a_      				=						0
				if self.bpe_ranks is None:
					return (vocab_file,)

				with open(UpperCAmelCase					,   """w"""					,   encoding="""utf-8"""	) as writer:
					for bpe_tokens, token_index in sorted(self.bpe_ranks.items()					,   key=lambda UpperCAmelCase	: kv[1]	):
						if index != token_index:
							logger.warning(
							    f'''Saving vocabulary to {merges_file}: BPE merge indices are not consecutive.'''
							    """ Please check that the tokenizer is not corrupted!"""	)
							a_      				=						token_index
						writer.write(""" """.join(UpperCAmelCase	) + """\n"""	)
						index += 1

				return (vocab_file, merges_file)
