



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


lowerCAmelCase__					  =  logging.get_logger(__name__)


lowerCAmelCase__					  =  {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt'''}

# See all BART models at https://huggingface.co/models?filter=bart
lowerCAmelCase__					  =  {
    '''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''',
    },
}

lowerCAmelCase__					  =  {
    '''facebook/bart-base''': 1_0_2_4,
    '''facebook/bart-large''': 1_0_2_4,
    '''facebook/bart-large-mnli''': 1_0_2_4,
    '''facebook/bart-large-cnn''': 1_0_2_4,
    '''facebook/bart-large-xsum''': 1_0_2_4,
    '''yjernite/bart_eli5''': 1_0_2_4,
}


@lru_cache()
def  __lowerCamelCase (       ):

						"""simple docstring"""


						lowercase__					:   List[Any]													=					(
						    list(range(ord("!"						)					,			ord("~"						) + 1						)						) + list(range(ord("¡"						)					,			ord("¬"						) + 1						)						) + list(range(ord("®"						)					,			ord("ÿ"						) + 1						)						)
						)
						lowercase__					:   Any													=					bs[:]
						lowercase__					:   int													=					0
						for b in range(2**8						):
												if b not in bs:
																		bs.append(lowerCAmelCase_						)
																		cs.append(2**8 + n						)
																		n += 1
						lowercase__					:   Optional[Any]													=					[chr(lowerCAmelCase_						) for n in cs]
						return dict(zip(lowerCAmelCase_					,			lowerCAmelCase_						)						)


def  __lowerCamelCase (       lowerCamelCase__						):

						"""simple docstring"""


						lowercase__					:   int													=					set()
						lowercase__					:   Any													=					word[0]
						for char in word[1:]:
												pairs.add((prev_char, char)						)
												lowercase__					:   Tuple													=					char
						return pairs

class 				snake_case__(_UpperCamelCase      ):

					"""simple docstring"""






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







					def __init__(							self :     Union[str, Any]				,       SCREAMING_SNAKE_CASE :     Union[str, Any]				,       SCREAMING_SNAKE_CASE :     str				,       SCREAMING_SNAKE_CASE :     List[Any]="replace"				,       SCREAMING_SNAKE_CASE :     List[str]="<s>"				,       SCREAMING_SNAKE_CASE :     List[str]="</s>"				,       SCREAMING_SNAKE_CASE :     List[Any]="</s>"				,       SCREAMING_SNAKE_CASE :     Optional[Any]="<s>"				,       SCREAMING_SNAKE_CASE :     Dict="<unk>"				,       SCREAMING_SNAKE_CASE :     List[str]="<pad>"				,       SCREAMING_SNAKE_CASE :     Optional[int]="<mask>"				,       SCREAMING_SNAKE_CASE :     Any=False				,       **SCREAMING_SNAKE_CASE :     List[str]				,       ):
											lowercase__					:   List[str]													=					AddedToken(_UpperCAmelCase				,       lstrip=_UpperCAmelCase				,       rstrip=_UpperCAmelCase					) if isinstance(_UpperCAmelCase				,       _UpperCAmelCase					) else bos_token
											lowercase__					:   Dict													=					AddedToken(_UpperCAmelCase				,       lstrip=_UpperCAmelCase				,       rstrip=_UpperCAmelCase					) if isinstance(_UpperCAmelCase				,       _UpperCAmelCase					) else eos_token
											lowercase__					:   Optional[int]													=					AddedToken(_UpperCAmelCase				,       lstrip=_UpperCAmelCase				,       rstrip=_UpperCAmelCase					) if isinstance(_UpperCAmelCase				,       _UpperCAmelCase					) else sep_token
											lowercase__					:   Optional[int]													=					AddedToken(_UpperCAmelCase				,       lstrip=_UpperCAmelCase				,       rstrip=_UpperCAmelCase					) if isinstance(_UpperCAmelCase				,       _UpperCAmelCase					) else cls_token
											lowercase__					:   Any													=					AddedToken(_UpperCAmelCase				,       lstrip=_UpperCAmelCase				,       rstrip=_UpperCAmelCase					) if isinstance(_UpperCAmelCase				,       _UpperCAmelCase					) else unk_token
											lowercase__					:   Dict													=					AddedToken(_UpperCAmelCase				,       lstrip=_UpperCAmelCase				,       rstrip=_UpperCAmelCase					) if isinstance(_UpperCAmelCase				,       _UpperCAmelCase					) else pad_token

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

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

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

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







					@property
					def 			snake_case					(							self :     List[Any]					):
											return len(self.encoder					)







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







					def 			snake_case					(							self :     Optional[int]				,       SCREAMING_SNAKE_CASE :     Dict					):
											if token in self.cache:
																	return self.cache[token]
											lowercase__					:   Union[str, Any]													=					tuple(_UpperCAmelCase					)
											lowercase__					:   Union[str, Any]													=					get_pairs(_UpperCAmelCase					)

											if not pairs:
																	return token

											while True:
																	lowercase__					:   Tuple													=					min(_UpperCAmelCase				,       key=lambda SCREAMING_SNAKE_CASE					: self.bpe_ranks.get(_UpperCAmelCase				,       float("inf"					)					)					)
																	if bigram not in self.bpe_ranks:
																							break
																	lowercase__					:   Tuple													=					bigram
																	lowercase__					:   Optional[int]													=					[]
																	lowercase__					:   Tuple													=					0
																	while i < len(_UpperCAmelCase					):
																							try:
																													lowercase__					:   Dict													=					word.index(_UpperCAmelCase				,       _UpperCAmelCase					)
																							except ValueError:
																													new_word.extend(word[i:]					)
																													break
																							else:
																													new_word.extend(word[i:j]					)
																													lowercase__					:   Tuple													=					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
																	lowercase__					:   List[str]													=					tuple(_UpperCAmelCase					)
																	lowercase__					:   Dict													=					new_word
																	if len(_UpperCAmelCase					) == 1:
																							break
																	else:
																							lowercase__					:   Optional[Any]													=					get_pairs(_UpperCAmelCase					)
											lowercase__					:   List[str]													=					' '.join(_UpperCAmelCase					)
											lowercase__					:   Tuple													=					word
											return word







					def 			snake_case					(							self :     Optional[int]				,       SCREAMING_SNAKE_CASE :     int					):
											lowercase__					:   int													=					[]
											for token in re.findall(self.pat				,       _UpperCAmelCase					):
																	lowercase__					:   Union[str, Any]													=					''.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(_UpperCAmelCase					).split(" "					)					)
											return bpe_tokens







					def 			snake_case					(							self :     Optional[Any]				,       SCREAMING_SNAKE_CASE :     Optional[int]					):
											return self.encoder.get(_UpperCAmelCase				,       self.encoder.get(self.unk_token					)					)







					def 			snake_case					(							self :     str				,       SCREAMING_SNAKE_CASE :     int					):
											return self.decoder.get(_UpperCAmelCase					)







					def 			snake_case					(							self :     Optional[int]				,       SCREAMING_SNAKE_CASE :     Optional[int]					):
											lowercase__					:   List[str]													=					''.join(_UpperCAmelCase					)
											lowercase__					:   Any													=					bytearray([self.byte_decoder[c] for c in text]					).decode("utf-8"				,       errors=self.errors					)
											return text







					def 			snake_case					(							self :     Tuple				,       SCREAMING_SNAKE_CASE :     str				,       SCREAMING_SNAKE_CASE :     Optional[str] = None					):
											if not os.path.isdir(_UpperCAmelCase					):
																	logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""					)
																	return
											lowercase__					:   Any													=					os.path.join(
											    _UpperCAmelCase				,       (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]					)
											lowercase__					:   Optional[int]													=					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"					)

											lowercase__					:   Union[str, Any]													=					0
											with open(_UpperCAmelCase				,       "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 SCREAMING_SNAKE_CASE					: 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!"					)
																													lowercase__					:   Optional[Any]													=					token_index
																							writer.write(" ".join(_UpperCAmelCase					) + "\n"					)
																							index += 1

											return vocab_file, merge_file







					def 			snake_case					(							self :     Optional[int]				,       SCREAMING_SNAKE_CASE :     List[int]				,       SCREAMING_SNAKE_CASE :     Optional[List[int]] = None					):
											if token_ids_a is None:
																	return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
											lowercase__					:   str													=					[self.cls_token_id]
											lowercase__					:   int													=					[self.sep_token_id]
											return cls + token_ids_a + sep + sep + token_ids_a + sep







					def 			snake_case					(							self :     Any				,       SCREAMING_SNAKE_CASE :     List[int]				,       SCREAMING_SNAKE_CASE :     Optional[List[int]] = None				,       SCREAMING_SNAKE_CASE :     bool = False					):
											if already_has_special_tokens:
																	return super().get_special_tokens_mask(
																	    token_ids_a=_UpperCAmelCase				,       token_ids_a=_UpperCAmelCase				,       already_has_special_tokens=_UpperCAmelCase					)

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







					def 			snake_case					(							self :     str				,       SCREAMING_SNAKE_CASE :     List[int]				,       SCREAMING_SNAKE_CASE :     Optional[List[int]] = None					):
											lowercase__					:   Tuple													=					[self.sep_token_id]
											lowercase__					:   Any													=					[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 			snake_case					(							self :     str				,       SCREAMING_SNAKE_CASE :     Dict				,       SCREAMING_SNAKE_CASE :     int=False				,       **SCREAMING_SNAKE_CASE :     int					):
											lowercase__					:   Union[str, Any]													=					kwargs.pop("add_prefix_space"				,       self.add_prefix_space					)
											if (is_split_into_words or add_prefix_space) and (len(_UpperCAmelCase					) > 0 and not text[0].isspace()):
																	lowercase__					:   str													=					' ' + text
											return (text, kwargs)









import unittest

import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel

from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()

class 				snake_case__(unittest.TestCase      ):

					"""simple docstring"""






					@property
					def 			snake_case					(							self :     Any					):
									torch.manual_seed(0					)
									lowercase__					:   Tuple													=					UNetaDModel(
									    block_out_channels=(32, 64)				,       layers_per_block=2				,       sample_size=32				,       in_channels=3				,       out_channels=3				,       down_block_types=("DownBlock2D", "AttnDownBlock2D")				,       up_block_types=("AttnUpBlock2D", "UpBlock2D")				,       )
									return model







					@property
					def 			snake_case					(							self :     List[str]					):
									torch.manual_seed(0					)
									lowercase__					:   Optional[int]													=					VQModel(
									    block_out_channels=[32, 64]				,       in_channels=3				,       out_channels=3				,       down_block_types=["DownEncoderBlock2D", "DownEncoderBlock2D"]				,       up_block_types=["UpDecoderBlock2D", "UpDecoderBlock2D"]				,       latent_channels=3				,       )
									return model







					@property
					def 			snake_case					(							self :     Dict					):
									torch.manual_seed(0					)
									lowercase__					:   str													=					CLIPTextConfig(
									    bos_token_id=0				,       eos_token_id=2				,       hidden_size=32				,       intermediate_size=37				,       layer_norm_eps=1E-0_5				,       num_attention_heads=4				,       num_hidden_layers=5				,       pad_token_id=1				,       vocab_size=1_000				,       )
									return CLIPTextModel(SCREAMING_SNAKE_CASE					)







					def 			snake_case					(							self :     str					):
									lowercase__					:   Any													=					self.dummy_uncond_unet
									lowercase__					:   Dict													=					DDIMScheduler()
									lowercase__					:   Optional[Any]													=					self.dummy_vq_model

									lowercase__					:   Union[str, Any]													=					LDMPipeline(unet=SCREAMING_SNAKE_CASE				,       vqvae=SCREAMING_SNAKE_CASE				,       scheduler=SCREAMING_SNAKE_CASE					)
									ldm.to(SCREAMING_SNAKE_CASE					)
									ldm.set_progress_bar_config(disable=SCREAMING_SNAKE_CASE					)

									lowercase__					:   int													=					torch.manual_seed(0					)
									lowercase__					:   Optional[int]													=					ldm(generator=SCREAMING_SNAKE_CASE				,       num_inference_steps=2				,       output_type="numpy"					).images

									lowercase__					:   str													=					torch.manual_seed(0					)
									lowercase__					:   List[Any]													=					ldm(generator=SCREAMING_SNAKE_CASE				,       num_inference_steps=2				,       output_type="numpy"				,       return_dict=SCREAMING_SNAKE_CASE					)[0]

									lowercase__					:   Any													=					image[0, -3:, -3:, -1]
									lowercase__					:   Optional[Any]													=					image_from_tuple[0, -3:, -3:, -1]

									assert image.shape == (1, 64, 64, 3)
									lowercase__					:   List[Any]													=					np.array([0.8_512, 0.818, 0.6_411, 0.6_808, 0.4_465, 0.5_618, 0.46, 0.6_231, 0.5_172]					)
									lowercase__					:   Optional[Any]													=					1E-2 if torch_device != "mps" else 3E-2

									assert np.abs(image_slice.flatten() - expected_slice					).max() < tolerance
									assert np.abs(image_from_tuple_slice.flatten() - expected_slice					).max() < tolerance






@slow
@require_torch
class 				snake_case__(unittest.TestCase      ):

					"""simple docstring"""






					def 			snake_case					(							self :     Optional[Any]					):
									lowercase__					:   int													=					LDMPipeline.from_pretrained("CompVis/ldm-celebahq-256"					)
									ldm.to(SCREAMING_SNAKE_CASE					)
									ldm.set_progress_bar_config(disable=SCREAMING_SNAKE_CASE					)

									lowercase__					:   Dict													=					torch.manual_seed(0					)
									lowercase__					:   Tuple													=					ldm(generator=SCREAMING_SNAKE_CASE				,       num_inference_steps=5				,       output_type="numpy"					).images

									lowercase__					:   Tuple													=					image[0, -3:, -3:, -1]

									assert image.shape == (1, 256, 256, 3)
									lowercase__					:   Optional[Any]													=					np.array([0.4_399, 0.44_975, 0.46_825, 0.474, 0.4_359, 0.4_581, 0.45_095, 0.4_341, 0.4_447]					)
									lowercase__					:   int													=					1E-2 if torch_device != "mps" else 3E-2

									assert np.abs(image_slice.flatten() - expected_slice					).max() < tolerance




