






'''simple docstring'''







import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

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


UpperCamelCase    :      List[Any]  			=		logging.get_logger(__name__)


UpperCamelCase    :      List[Any]  			=		{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

# See all BART models at https://huggingface.co/models?filter=bart
UpperCamelCase    :      int  			=		{
    'vocab_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/vocab.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/vocab.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json',
    },
    'merges_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/merges.txt',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/merges.txt',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt',
    },
}

UpperCamelCase    :      Optional[Any]  			=		{
    'facebook/bart-base': 10_24,
    'facebook/bart-large': 10_24,
    'facebook/bart-large-mnli': 10_24,
    'facebook/bart-large-cnn': 10_24,
    'facebook/bart-large-xsum': 10_24,
    'yjernite/bart_eli5': 10_24,
}
@lru_cache()
def 						A__			(				):
						lowerCamelCase__         =  (
						    list(range(ord("""!"""						)   ,    ord("""~"""						) + 1						)						) + list(range(ord("""¡"""						)   ,    ord("""¬"""						) + 1						)						) + list(range(ord("""®"""						)   ,    ord("""ÿ"""						) + 1						)						)
						)
						lowerCamelCase__         =  bs[:]
						lowerCamelCase__         =  0
						for b in range(2**8						):
												if b not in bs:
																		bs.append(__lowerCAmelCase						)
																		cs.append(2**8 + n						)
																		n += 1
						lowerCamelCase__         =  [chr(__lowerCAmelCase						) for n in cs]
						return dict(zip(__lowerCAmelCase   ,    __lowerCAmelCase						)						)
def 						A__			(				__lowerCAmelCase		:			str						):
						lowerCamelCase__         =  set()
						lowerCamelCase__         =  word[0]
						for char in word[1:]:
												pairs.add((prev_char, char)						)
												lowerCamelCase__         =  char
						return pairs





class 		UpperCamelCase__    (a			):




		'''simple docstring'''





		_UpperCamelCase				  =					VOCAB_FILES_NAMES
		_UpperCamelCase				  =					PRETRAINED_VOCAB_FILES_MAP
		_UpperCamelCase				  =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		_UpperCamelCase				  =					['input_ids', 'attention_mask']






		def __init__(      self   ,_lowerCAmelCase   ,_lowerCAmelCase   ,_lowerCAmelCase="replace"   ,_lowerCAmelCase="<s>"   ,_lowerCAmelCase="</s>"   ,_lowerCAmelCase="</s>"   ,_lowerCAmelCase="<s>"   ,_lowerCAmelCase="<unk>"   ,_lowerCAmelCase="<pad>"   ,_lowerCAmelCase="<mask>"   ,_lowerCAmelCase=False   ,**_lowerCAmelCase   ,):
								lowerCamelCase__         =  AddedToken(_lowerCAmelCase   ,lstrip=_lowerCAmelCase   ,rstrip=_lowerCAmelCase       ) if isinstance(_lowerCAmelCase   ,_lowerCAmelCase       ) else bos_token
								lowerCamelCase__         =  AddedToken(_lowerCAmelCase   ,lstrip=_lowerCAmelCase   ,rstrip=_lowerCAmelCase       ) if isinstance(_lowerCAmelCase   ,_lowerCAmelCase       ) else eos_token
								lowerCamelCase__         =  AddedToken(_lowerCAmelCase   ,lstrip=_lowerCAmelCase   ,rstrip=_lowerCAmelCase       ) if isinstance(_lowerCAmelCase   ,_lowerCAmelCase       ) else sep_token
								lowerCamelCase__         =  AddedToken(_lowerCAmelCase   ,lstrip=_lowerCAmelCase   ,rstrip=_lowerCAmelCase       ) if isinstance(_lowerCAmelCase   ,_lowerCAmelCase       ) else cls_token
								lowerCamelCase__         =  AddedToken(_lowerCAmelCase   ,lstrip=_lowerCAmelCase   ,rstrip=_lowerCAmelCase       ) if isinstance(_lowerCAmelCase   ,_lowerCAmelCase       ) else unk_token
								lowerCamelCase__         =  AddedToken(_lowerCAmelCase   ,lstrip=_lowerCAmelCase   ,rstrip=_lowerCAmelCase       ) if isinstance(_lowerCAmelCase   ,_lowerCAmelCase       ) else pad_token

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

								super().__init__(
								    errors=_lowerCAmelCase   ,bos_token=_lowerCAmelCase   ,eos_token=_lowerCAmelCase   ,unk_token=_lowerCAmelCase   ,sep_token=_lowerCAmelCase   ,cls_token=_lowerCAmelCase   ,pad_token=_lowerCAmelCase   ,mask_token=_lowerCAmelCase   ,add_prefix_space=_lowerCAmelCase   ,**_lowerCAmelCase   ,)

								with open(_lowerCAmelCase   ,encoding="""utf-8"""       ) as vocab_handle:
														lowerCamelCase__         =  json.load(_lowerCAmelCase       )
								lowerCamelCase__         =  {v: k for k, v in self.encoder.items()}
								lowerCamelCase__         =  errors  # how to handle errors in decoding
								lowerCamelCase__         =  bytes_to_unicode()
								lowerCamelCase__         =  {v: k for k, v in self.byte_encoder.items()}
								with open(_lowerCAmelCase   ,encoding="""utf-8"""       ) as merges_handle:
														lowerCamelCase__         =  merges_handle.read().split("""\n"""       )[1:-1]
								lowerCamelCase__         =  [tuple(merge.split()       ) for merge in bpe_merges]
								lowerCamelCase__         =  dict(zip(_lowerCAmelCase   ,range(len(_lowerCAmelCase       )       )       )       )
								lowerCamelCase__         =  {}
								lowerCamelCase__         =  add_prefix_space

								# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
								lowerCamelCase__         =  re.compile(R"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""       )






		@property
		def 			UpperCamelCase_					(      self       ):
								return len(self.encoder       )






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






		def 			UpperCamelCase_					(      self   ,_lowerCAmelCase       ):
								if token in self.cache:
														return self.cache[token]
								lowerCamelCase__         =  tuple(_lowerCAmelCase       )
								lowerCamelCase__         =  get_pairs(_lowerCAmelCase       )

								if not pairs:
														return token

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

																				if word[i] == first and i < len(_lowerCAmelCase       ) - 1 and word[i + 1] == second:
																										new_word.append(first + second       )
																										i += 2
																				else:
																										new_word.append(word[i]       )
																										i += 1
														lowerCamelCase__         =  tuple(_lowerCAmelCase       )
														lowerCamelCase__         =  new_word
														if len(_lowerCAmelCase       ) == 1:
																				break
														else:
																				lowerCamelCase__         =  get_pairs(_lowerCAmelCase       )
								lowerCamelCase__         =  """ """.join(_lowerCAmelCase       )
								lowerCamelCase__         =  word
								return word






		def 			UpperCamelCase_					(      self   ,_lowerCAmelCase       ):
								lowerCamelCase__         =  []
								for token in re.findall(self.pat   ,_lowerCAmelCase       ):
														lowerCamelCase__         =  """""".join(
														    self.byte_encoder[b] for b in token.encode("""utf-8"""       )       )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
														bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_lowerCAmelCase       ).split(""" """       )       )
								return bpe_tokens






		def 			UpperCamelCase_					(      self   ,_lowerCAmelCase       ):
								return self.encoder.get(_lowerCAmelCase   ,self.encoder.get(self.unk_token       )       )






		def 			UpperCamelCase_					(      self   ,_lowerCAmelCase       ):
								return self.decoder.get(_lowerCAmelCase       )






		def 			UpperCamelCase_					(      self   ,_lowerCAmelCase       ):
								lowerCamelCase__         =  """""".join(_lowerCAmelCase       )
								lowerCamelCase__         =  bytearray([self.byte_decoder[c] for c in text]       ).decode("""utf-8"""   ,errors=self.errors       )
								return text






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

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

								lowerCamelCase__         =  0
								with open(_lowerCAmelCase   ,"""w"""   ,encoding="""utf-8"""       ) as writer:
														writer.write("""#version: 0.2\n"""       )
														for bpe_tokens, token_index in sorted(self.bpe_ranks.items()   ,key=lambda _lowerCAmelCase       : kv[1]       ):
																				if index != token_index:
																										logger.warning(
																										    F'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
																										    """ Please check that the tokenizer is not corrupted!"""       )
																										lowerCamelCase__         =  token_index
																				writer.write(""" """.join(_lowerCAmelCase       ) + """\n"""       )
																				index += 1

								return vocab_file, merge_file






		def 			UpperCamelCase_					(      self   ,_lowerCAmelCase   ,_lowerCAmelCase = None       ):
								if token_ids_a is None:
														return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								lowerCamelCase__         =  [self.cls_token_id]
								lowerCamelCase__         =  [self.sep_token_id]
								return cls + token_ids_a + sep + sep + token_ids_a + sep






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

								if token_ids_a is None:
														return [1] + ([0] * len(_lowerCAmelCase       )) + [1]
								return [1] + ([0] * len(_lowerCAmelCase       )) + [1, 1] + ([0] * len(_lowerCAmelCase       )) + [1]






		def 			UpperCamelCase_					(      self   ,_lowerCAmelCase   ,_lowerCAmelCase = None       ):
								lowerCamelCase__         =  [self.sep_token_id]
								lowerCamelCase__         =  [self.cls_token_id]

								if token_ids_a is None:
														return len(cls + token_ids_a + sep       ) * [0]
								return len(cls + token_ids_a + sep + sep + token_ids_a + sep       ) * [0]






		def 			UpperCamelCase_					(      self   ,_lowerCAmelCase   ,_lowerCAmelCase=False   ,**_lowerCAmelCase       ):
								lowerCamelCase__         =  kwargs.pop("""add_prefix_space"""   ,self.add_prefix_space       )
								if (is_split_into_words or add_prefix_space) and (len(_lowerCAmelCase       ) > 0 and not text[0].isspace()):
														lowerCamelCase__         =  """ """ + text
								return (text, kwargs)









'''simple docstring'''







import argparse

import OmegaConf
import torch

from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def 						A__			(				__lowerCAmelCase		:			str   ,    __lowerCAmelCase		:			Tuple   ,    __lowerCAmelCase		:			List[str]						):
						lowerCamelCase__         =  OmegaConf.load(__lowerCAmelCase						)
						lowerCamelCase__         =  torch.load(__lowerCAmelCase   ,    map_location="""cpu"""						)["""model"""]
						lowerCamelCase__         =  list(state_dict.keys()						)

						# extract state_dict for VQVAE
						lowerCamelCase__         =  {}
						lowerCamelCase__         =  """first_stage_model."""
						for key in keys:
												if key.startswith(__lowerCAmelCase						):
																		lowerCamelCase__         =  state_dict[key]

    # extract state_dict for UNetLDM
						lowerCamelCase__         =  {}
						lowerCamelCase__         =  """model.diffusion_model."""
						for key in keys:
												if key.startswith(__lowerCAmelCase						):
																		lowerCamelCase__         =  state_dict[key]

						lowerCamelCase__         =  config.model.params.first_stage_config.params
						lowerCamelCase__         =  config.model.params.unet_config.params

						lowerCamelCase__         =  VQModel(**__lowerCAmelCase						).eval()
						vqvae.load_state_dict(__lowerCAmelCase						)

						lowerCamelCase__         =  UNetLDMModel(**__lowerCAmelCase						).eval()
						unet.load_state_dict(__lowerCAmelCase						)

						lowerCamelCase__         =  DDIMScheduler(
						    timesteps=config.model.params.timesteps   ,    beta_schedule="""scaled_linear"""   ,    beta_start=config.model.params.linear_start   ,    beta_end=config.model.params.linear_end   ,    clip_sample=__lowerCAmelCase   ,    )

						lowerCamelCase__         =  LDMPipeline(__lowerCAmelCase   ,    __lowerCAmelCase   ,    __lowerCAmelCase						)
						pipeline.save_pretrained(__lowerCAmelCase						)


if __name__ == "__main__":
							UpperCamelCase    :      Optional[int]  			=		argparse.ArgumentParser()
							parser.add_argument('--checkpoint_path', type=str, required=True)
							parser.add_argument('--config_path', type=str, required=True)
							parser.add_argument('--output_path', type=str, required=True)
							UpperCamelCase    :      List[Any]  			=		parser.parse_args()

							convert_ldm_original(args.checkpoint_path, args.config_path, args.output_path)

