
from typing import Dict, List, Optional, Tuple

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


_A       =					logging.get_logger(__name__)





class      _lowerCAmelCase (     __a	):
				_lowercase      		=['''input_ids''', '''attention_mask''']




				def __init__( self    ,    _UpperCamelCase="[PAD]"    ,    _UpperCamelCase="[BOS]"    ,    _UpperCamelCase="[EOS]"    ,    _UpperCamelCase="[MASK]"    ,    _UpperCamelCase="[CLS]"    ,    _UpperCamelCase="[SEP]"    ,    _UpperCamelCase=2_048    ,    **_UpperCamelCase    ,    )    ->				None:
							lowerCAmelCase_      =     AddedToken(_UpperCamelCase    ,    lstrip=_UpperCamelCase    ,    rstrip=_UpperCamelCase					) if isinstance(_UpperCamelCase    ,    _UpperCamelCase					) else pad_token
							lowerCAmelCase_      =     AddedToken(_UpperCamelCase    ,    lstrip=_UpperCamelCase    ,    rstrip=_UpperCamelCase					) if isinstance(_UpperCamelCase    ,    _UpperCamelCase					) else bos_token
							lowerCAmelCase_      =     AddedToken(_UpperCamelCase    ,    lstrip=_UpperCamelCase    ,    rstrip=_UpperCamelCase					) if isinstance(_UpperCamelCase    ,    _UpperCamelCase					) else eos_token
							lowerCAmelCase_      =     AddedToken(_UpperCamelCase    ,    lstrip=_UpperCamelCase    ,    rstrip=_UpperCamelCase					) if isinstance(_UpperCamelCase    ,    _UpperCamelCase					) else mask_token
							lowerCAmelCase_      =     AddedToken(_UpperCamelCase    ,    lstrip=_UpperCamelCase    ,    rstrip=_UpperCamelCase					) if isinstance(_UpperCamelCase    ,    _UpperCamelCase					) else cls_token
							lowerCAmelCase_      =     AddedToken(_UpperCamelCase    ,    lstrip=_UpperCamelCase    ,    rstrip=_UpperCamelCase					) if isinstance(_UpperCamelCase    ,    _UpperCamelCase					) else sep_token

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

							lowerCAmelCase_      =     2**8  # utf is 8 bits

							# define special tokens dict
							lowerCAmelCase_      =     {
							    self.pad_token: 0,
							    self.bos_token: 1,
							    self.eos_token: 2,
							    self.mask_token: 3,
							    self.cls_token: 4,
							    self.sep_token: 5,
							}
							lowerCAmelCase_      =     len(self.special_tokens_encoder					)
							lowerCAmelCase_      =     {v: k for k, v in self.special_tokens_encoder.items()}




				def 					__a						( self					)    ->				Dict[str, int]:
							lowerCAmelCase_      =     self.special_tokens_encoder.copy()
							vocab.update(self.added_tokens_encoder					)
							for i in range(self._utf_vocab_size					):
										lowerCAmelCase_      =     chr(_UpperCamelCase					)
										lowerCAmelCase_      =     i + len(self.special_tokens_encoder					)
							return vocab




				@property
				def 					__a						( self					)    ->				List[Any]:
							return self._utf_vocab_size + self._num_special_tokens




				def 					__a						( self    ,    _UpperCamelCase    ,    _UpperCamelCase = None    ,    _UpperCamelCase = False					)    ->				List[int]:
							if already_has_special_tokens:
										return super().get_special_tokens_mask(
										    token_ids_a=_UpperCamelCase    ,    token_ids_a=_UpperCamelCase    ,    already_has_special_tokens=_UpperCamelCase					)

							# normal case: some special tokens
							if token_ids_a is None:
										return [1] + [0] * len(_UpperCamelCase					) + [1]
							return [1] + ([0] * len(_UpperCamelCase					)) + [1] + ([0] * len(_UpperCamelCase					)) + [1]




				def 					__a						( self    ,    _UpperCamelCase    ,    _UpperCamelCase = None					)    ->				List[int]:
							if token_ids_a is None:
										return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							else:
										return [self.cls_token_id] + token_ids_a + [self.sep_token_id] + token_ids_a + [self.sep_token_id]




				def 					__a						( self    ,    _UpperCamelCase					)    ->				List[str]:
							lowerCAmelCase_      =     [chr(_UpperCamelCase					) for i in text.encode("utf-8"					)]
							return tokens




				def 					__a						( self    ,    _UpperCamelCase					)    ->				Optional[Any]:
							if token in self.special_tokens_encoder:
										lowerCAmelCase_      =     self.special_tokens_encoder[token]
							elif token in self.added_tokens_encoder:
										lowerCAmelCase_      =     self.added_tokens_encoder[token]
							elif len(_UpperCamelCase					) != 1:
										lowerCAmelCase_      =     self.unk_token_id
							else:
										lowerCAmelCase_      =     ord(_UpperCamelCase					) + self._num_special_tokens
							return token_id




				def 					__a						( self    ,    _UpperCamelCase					)    ->				Dict:
							if index in self.special_tokens_decoder:
										lowerCAmelCase_      =     self.special_tokens_decoder[index]
							elif index in self.added_tokens_decoder:
										lowerCAmelCase_      =     self.added_tokens_decoder[index]
							else:
										lowerCAmelCase_      =     chr(index - self._num_special_tokens					)
							return token




				def 					__a						( self    ,    _UpperCamelCase					)    ->				Optional[int]:
							lowerCAmelCase_      =     B""
							for token in tokens:
										if token in self.special_tokens_decoder:
													lowerCAmelCase_      =     self.special_tokens_decoder[token].encode("utf-8"					)
										elif token in self.added_tokens_decoder:
													lowerCAmelCase_      =     self.special_tokens_decoder[token].encode("utf-8"					)
										elif token in self.special_tokens_encoder:
													lowerCAmelCase_      =     token.encode("utf-8"					)
										elif token in self.added_tokens_encoder:
													lowerCAmelCase_      =     token.encode("utf-8"					)
										else:
													lowerCAmelCase_      =     bytes([ord(_UpperCamelCase					)]					)
										bstring += tok_string
							lowerCAmelCase_      =     bstring.decode("utf-8"    ,    errors="replace"					)
							return string




				def 					__a						( self    ,    _UpperCamelCase    ,    _UpperCamelCase = None					)    ->				Tuple[str]:
							return ()





import torch
import torch.nn.functional as F

from diffusers import VQDiffusionScheduler

from .test_schedulers import SchedulerCommonTest





class      _lowerCAmelCase (     __a	):
				_lowercase      		=(VQDiffusionScheduler,)




				def 					__a						( self    ,    **_UpperCamelCase					)    ->				List[str]:
							lowerCAmelCase_      =     {
							    "num_vec_classes": 4_097,
							    "num_train_timesteps": 100,
							}

							config.update(**_UpperCamelCase					)
							return config




				def 					__a						( self    ,    _UpperCamelCase					)    ->				str:
							lowerCAmelCase_      =     4
							lowerCAmelCase_      =     8
							lowerCAmelCase_      =     8

							lowerCAmelCase_      =     torch.randint(0    ,    _UpperCamelCase    ,    (batch_size, height * width)					)

							return sample




				@property
				def 					__a						( self					)    ->				List[str]:
							assert False




				def 					__a						( self    ,    _UpperCamelCase					)    ->				Tuple:
							def model(_UpperCamelCase    ,    _UpperCamelCase    ,    *_UpperCamelCase					):
										lowerCAmelCase_     ,  lowerCAmelCase_      =     sample.shape
										lowerCAmelCase_      =     torch.rand((batch_size, num_vec_classes - 1, num_latent_pixels)					)
										lowerCAmelCase_      =     F.log_softmax(logits.double()    ,    dim=1					).float()
										return return_value

							return model




				def 					__a						( self					)    ->				str:
							for timesteps in [2, 5, 100, 1_000]:
										self.check_over_configs(num_train_timesteps=_UpperCamelCase					)




				def 					__a						( self					)    ->				Dict:
							for num_vec_classes in [5, 100, 1_000, 4_000]:
										self.check_over_configs(num_vec_classes=_UpperCamelCase					)




				def 					__a						( self					)    ->				Tuple:
							for t in [0, 50, 99]:
										self.check_over_forward(time_step=_UpperCamelCase					)




				def 					__a						( self					)    ->				List[str]:
							pass



