

import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer


if TYPE_CHECKING:
						from ...tokenization_utils_base import TextInput
from ...utils import logging


A__						=							logging.get_logger(__name__)

A__						=							{"vocab_file": "spiece.model"}

A__						=							{
    "vocab_file": {
        "t5-small": "https://huggingface.co/t5-small/resolve/main/spiece.model",
        "t5-base": "https://huggingface.co/t5-base/resolve/main/spiece.model",
        "t5-large": "https://huggingface.co/t5-large/resolve/main/spiece.model",
        "t5-3b": "https://huggingface.co/t5-3b/resolve/main/spiece.model",
        "t5-11b": "https://huggingface.co/t5-11b/resolve/main/spiece.model",
    }
}


# TODO(PVP) - this should be removed in Transformers v5
A__						=							{
    "t5-small": 512,
    "t5-base": 512,
    "t5-large": 512,
    "t5-3b": 512,
    "t5-11b": 512,
}

A__						=							"▁"

class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE			):
	_lowercase  :   List[str]       				=  VOCAB_FILES_NAMES
	_lowercase  :   str       				=  PRETRAINED_VOCAB_FILES_MAP
	_lowercase  :   List[str]       				=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_lowercase  :   List[Any]       				=  ["input_ids", "attention_mask"]







	def __init__(   self: List[str]  , __UpperCamelCase: Any  , __UpperCamelCase: Any="</s>"  , __UpperCamelCase: Tuple="<unk>"  , __UpperCamelCase: Any="<pad>"  , __UpperCamelCase: Tuple=1_00  , __UpperCamelCase: str=None  , __UpperCamelCase: Optional[Dict[str, Any]] = None  , __UpperCamelCase: str=True  , **__UpperCamelCase: List[Any]  , ):

						'''simple docstring'''





						if extra_ids > 0 and additional_special_tokens is None:
											__magic_name__							=    [F'<extra_id_{i}>' for i in range(__UpperCamelCase      )]
						elif extra_ids > 0 and additional_special_tokens is not None:
											# Check that we have the right number of extra_id special tokens
											__magic_name__							=    len(set(filter(lambda __UpperCamelCase      : bool('extra_id' in str(__UpperCamelCase      )      )  , __UpperCamelCase      )      )      )
											if extra_tokens != extra_ids:
																raise ValueError(
																    F'Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are'
																    ' provided to T5Tokenizer. In this case the additional_special_tokens must include the extra_ids'
																    ' tokens'      )
						if legacy:
											logger.warning_once(
											    F'You are using the legacy behaviour of the {self.__class__}. This means that tokens that come after special tokens will not be properly handled. We recommend you to'
											    ' read the related pull request available at https://github.com/huggingface/transformers/pull/24565'      )

						__magic_name__							=    legacy
						__magic_name__							=    {} if sp_model_kwargs is None else sp_model_kwargs

						super().__init__(
						    eos_token=__UpperCamelCase  , unk_token=__UpperCamelCase  , pad_token=__UpperCamelCase  , extra_ids=__UpperCamelCase  , additional_special_tokens=__UpperCamelCase  , sp_model_kwargs=self.sp_model_kwargs  , legacy=__UpperCamelCase  , **__UpperCamelCase  , )

						__magic_name__							=    vocab_file
						__magic_name__							=    extra_ids

						__magic_name__							=    spm.SentencePieceProcessor(**self.sp_model_kwargs      )
						self.sp_model.Load(__UpperCamelCase      )







	@staticmethod
	def 	_SCREAMING_SNAKE_CASE							(   __UpperCamelCase: int  , __UpperCamelCase: Any  , __UpperCamelCase: Dict      ):

						'''simple docstring'''





						if pretrained_model_name_or_path in TaTokenizer.max_model_input_sizes:
											__magic_name__							=    TaTokenizer.max_model_input_sizes[pretrained_model_name_or_path]
											if init_max_model_length is not None and init_max_model_length != max_model_length:
																return init_max_model_length
											elif init_max_model_length is None:
																warnings.warn(
																    'This tokenizer was incorrectly instantiated with a model max length of'
																    F' {deprecated_max_model_length} which will be corrected in Transformers v5.\nFor now, this'
																    ' behavior is kept to avoid breaking backwards compatibility when padding/encoding with'
																    ' `truncation is True`.\n- Be aware that you SHOULD NOT rely on'
																    F' {pretrained_model_name_or_path} automatically truncating your input to'
																    F' {deprecated_max_model_length} when padding/encoding.\n- If you want to encode/pad to sequences'
																    F' longer than {deprecated_max_model_length} you can either instantiate this tokenizer with'
																    ' `model_max_length` or pass `max_length` when encoding/padding.\n- To avoid this warning, please'
																    ' instantiate this tokenizer with `model_max_length` set to your preferred value.'  , __UpperCamelCase  , )

						return max_model_length







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: Any      ):

						'''simple docstring'''





						return self.sp_model.get_piece_size() + self._extra_ids







	def 	_SCREAMING_SNAKE_CASE							(   self: Any      ):

						'''simple docstring'''





						__magic_name__							=    {self.convert_ids_to_tokens(__UpperCamelCase      ): i for i in range(self.vocab_size      )}
						vocab.update(self.added_tokens_encoder      )
						return vocab







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]  , __UpperCamelCase: List[int]  , __UpperCamelCase: Optional[List[int]] = None  , __UpperCamelCase: bool = False      ):

						'''simple docstring'''





						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 ([0] * len(__UpperCamelCase      )) + [1]
						return ([0] * len(__UpperCamelCase      )) + [1] + ([0] * len(__UpperCamelCase      )) + [1]







	def 	_SCREAMING_SNAKE_CASE							(   self: Dict      ):

						'''simple docstring'''





						return list(
						    set(filter(lambda __UpperCamelCase      : bool(re.search(r'<extra_id_\d+>'  , __UpperCamelCase      )      ) is not None  , self.additional_special_tokens      )      )      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Dict      ):

						'''simple docstring'''





						return [self._convert_token_to_id(__UpperCamelCase      ) for token in self.get_sentinel_tokens()]







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]  , __UpperCamelCase: List[int]      ):

						'''simple docstring'''





						if len(__UpperCamelCase      ) > 0 and token_ids[-1] == self.eos_token_id:
											warnings.warn(
											    F'This sequence already has {self.eos_token}. In future versions this behavior may lead to duplicated'
											    ' eos tokens being added.'      )
											return token_ids
						else:
											return token_ids + [self.eos_token_id]







	def 	_SCREAMING_SNAKE_CASE							(   self: Union[str, Any]  , __UpperCamelCase: List[int]  , __UpperCamelCase: Optional[List[int]] = None      ):

						'''simple docstring'''





						__magic_name__							=    [self.eos_token_id]

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







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[int]  , __UpperCamelCase: List[int]  , __UpperCamelCase: Optional[List[int]] = None      ):

						'''simple docstring'''





						__magic_name__							=    self._add_eos_if_not_present(__UpperCamelCase      )
						if token_ids_a is None:
											return token_ids_a
						else:
											__magic_name__							=    self._add_eos_if_not_present(__UpperCamelCase      )
											return token_ids_a + token_ids_a







	def __getstate__(   self: Union[str, Any]      ):

						'''simple docstring'''





						__magic_name__							=    self.__dict__.copy()
						__magic_name__							=    None
						return state







	def __setstate__(   self: Union[str, Any]  , __UpperCamelCase: List[Any]      ):

						'''simple docstring'''





						__magic_name__							=    d

						# for backward compatibility
						if not hasattr(self  , 'sp_model_kwargs'      ):
											__magic_name__							=    {}

						__magic_name__							=    spm.SentencePieceProcessor(**self.sp_model_kwargs      )
						self.sp_model.Load(self.vocab_file      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Any  , __UpperCamelCase: "TextInput"  , **__UpperCamelCase: str      ):

						'''simple docstring'''





						if not self.legacy:
											__magic_name__							=    SPIECE_UNDERLINE + text.replace(__UpperCamelCase  , ' '      )
						return super().tokenize(__UpperCamelCase  , **__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[int]  , __UpperCamelCase: Optional[Any]  , **__UpperCamelCase: Optional[int]      ):

						'''simple docstring'''





						if not self.legacy:
											__magic_name__							=    text.startswith(__UpperCamelCase      )
											if is_first:
																__magic_name__							=    text[1:]

						__magic_name__							=    self.sp_model.encode(__UpperCamelCase  , out_type=__UpperCamelCase      )

						if not self.legacy and not is_first and not text.startswith(' '      ) and tokens[0].startswith(__UpperCamelCase      ):
											__magic_name__							=    ([tokens[0][1:]] if len(tokens[0]      ) > 1 else []) + tokens[1:]
						return tokens







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]  , __UpperCamelCase: Optional[int]      ):

						'''simple docstring'''





						if token.startswith('<extra_id_'      ):
											__magic_name__							=    re.match(r'<extra_id_(\d+)>'  , __UpperCamelCase      )
											__magic_name__							=    int(match.group(1      )      )
											return self.vocab_size - num - 1
						return self.sp_model.piece_to_id(__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Tuple  , __UpperCamelCase: Any      ):

						'''simple docstring'''





						if index < self.sp_model.get_piece_size():
											__magic_name__							=    self.sp_model.IdToPiece(__UpperCamelCase      )
						else:
											__magic_name__							=    F'<extra_id_{self.vocab_size - 1 - index}>'
						return token







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]  , __UpperCamelCase: Union[str, Any]      ):

						'''simple docstring'''





						__magic_name__							=    []
						__magic_name__							=    ''
						__magic_name__							=    False
						for token in tokens:
											# make sure that special tokens are not decoded using sentencepiece model
											if token in self.all_special_tokens:
																if not prev_is_special:
																					out_string += " "
																out_string += self.sp_model.decode(__UpperCamelCase      ) + token
																__magic_name__							=    True
																__magic_name__							=    []
											else:
																current_sub_tokens.append(__UpperCamelCase      )
																__magic_name__							=    False
						out_string += self.sp_model.decode(__UpperCamelCase      )
						return out_string.strip()







	def 	_SCREAMING_SNAKE_CASE							(   self: int  , __UpperCamelCase: str  , __UpperCamelCase: Optional[str] = None      ):

						'''simple docstring'''





						if not os.path.isdir(__UpperCamelCase      ):
											logger.error(F'Vocabulary path ({save_directory}) should be a directory'      )
											return
						__magic_name__							=    os.path.join(
						    __UpperCamelCase  , (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']      )

						if os.path.abspath(self.vocab_file      ) != os.path.abspath(__UpperCamelCase      ) and os.path.isfile(self.vocab_file      ):
											copyfile(self.vocab_file  , __UpperCamelCase      )
						elif not os.path.isfile(self.vocab_file      ):
											with open(__UpperCamelCase  , 'wb'      ) as fi:
																__magic_name__							=    self.sp_model.serialized_model_proto()
																fi.write(__UpperCamelCase      )

						return (out_vocab_file,)







import unittest

from diffusers.models.unet_ad_blocks import *  # noqa F403
from diffusers.utils import torch_device

from .test_unet_blocks_common import UNetBlockTesterMixin

class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   str       				=  DownBlockaD  # noqa F405
	_lowercase  :   Union[str, Any]       				=  "down"







	def 	_SCREAMING_SNAKE_CASE							(   self: List[str]      ):

						'''simple docstring'''





						__magic_name__							=    [-0.0232, -0.9869, 0.8054, -0.0637, -0.1688, -1.4264, 0.4470, -1.3394, 0.0904]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   List[str]       				=  ResnetDownsampleBlockaD  # noqa F405
	_lowercase  :   Union[str, Any]       				=  "down"







	def 	_SCREAMING_SNAKE_CASE							(   self: int      ):

						'''simple docstring'''





						__magic_name__							=    [0.0710, 0.2410, -0.7320, -1.0757, -1.1343, 0.3540, -0.0133, -0.2576, 0.0948]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   Dict       				=  AttnDownBlockaD  # noqa F405
	_lowercase  :   List[Any]       				=  "down"







	def 	_SCREAMING_SNAKE_CASE							(   self: Any      ):

						'''simple docstring'''





						__magic_name__							=    [0.0636, 0.8964, -0.6234, -1.0131, 0.0844, 0.4935, 0.3437, 0.0911, -0.2957]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   int       				=  CrossAttnDownBlockaD  # noqa F405
	_lowercase  :   Any       				=  "down"







	def 	_SCREAMING_SNAKE_CASE							(   self: int      ):

						'''simple docstring'''





						__magic_name__,	__magic_name__							=    super().prepare_init_args_and_inputs_for_common()
						__magic_name__							=    32
						return init_dict, inputs_dict







	def 	_SCREAMING_SNAKE_CASE							(   self: str      ):

						'''simple docstring'''





						__magic_name__							=    [0.2238, -0.7396, -0.2255, -0.3829, 0.1925, 1.1665, 0.0603, -0.7295, 0.1983]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   Union[str, Any]       				=  SimpleCrossAttnDownBlockaD  # noqa F405
	_lowercase  :   List[str]       				=  "down"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: Any      ):

						'''simple docstring'''





						return super().get_dummy_input(include_encoder_hidden_states=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						__magic_name__,	__magic_name__							=    super().prepare_init_args_and_inputs_for_common()
						__magic_name__							=    32
						return init_dict, inputs_dict







	@unittest.skipIf(torch_device == 'mps'  , 'MPS result is not consistent'      )
	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						__magic_name__							=    [0.7921, -0.0992, -0.1962, -0.7695, -0.4242, 0.7804, 0.4737, 0.2765, 0.3338]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   str       				=  SkipDownBlockaD  # noqa F405
	_lowercase  :   Union[str, Any]       				=  "down"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[int]      ):

						'''simple docstring'''





						return super().get_dummy_input(include_skip_sample=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: List[str]      ):

						'''simple docstring'''





						__magic_name__							=    [-0.0845, -0.2087, -0.2465, 0.0971, 0.1900, -0.0484, 0.2664, 0.4179, 0.5069]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   Tuple       				=  AttnSkipDownBlockaD  # noqa F405
	_lowercase  :   str       				=  "down"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						return super().get_dummy_input(include_skip_sample=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Dict      ):

						'''simple docstring'''





						__magic_name__							=    [0.5539, 0.1609, 0.4924, 0.0537, -0.1995, 0.4050, 0.0979, -0.2721, -0.0642]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   Optional[int]       				=  DownEncoderBlockaD  # noqa F405
	_lowercase  :   List[str]       				=  "down"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: Union[str, Any]      ):

						'''simple docstring'''





						return super().get_dummy_input(include_temb=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Dict      ):

						'''simple docstring'''





						__magic_name__							=    {
						    'in_channels': 32,
						    'out_channels': 32,
						}
						__magic_name__							=    self.dummy_input
						return init_dict, inputs_dict







	def 	_SCREAMING_SNAKE_CASE							(   self: List[str]      ):

						'''simple docstring'''





						__magic_name__							=    [1.1102, 0.5302, 0.4872, -0.0023, -0.8042, 0.0483, -0.3489, -0.5632, 0.7626]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   List[Any]       				=  AttnDownEncoderBlockaD  # noqa F405
	_lowercase  :   Optional[Any]       				=  "down"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						return super().get_dummy_input(include_temb=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]      ):

						'''simple docstring'''





						__magic_name__							=    {
						    'in_channels': 32,
						    'out_channels': 32,
						}
						__magic_name__							=    self.dummy_input
						return init_dict, inputs_dict







	def 	_SCREAMING_SNAKE_CASE							(   self: Dict      ):

						'''simple docstring'''





						__magic_name__							=    [0.8966, -0.1486, 0.8568, 0.8141, -0.9046, -0.1342, -0.0972, -0.7417, 0.1538]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   List[Any]       				=  UNetMidBlockaD  # noqa F405
	_lowercase  :   Any       				=  "mid"







	def 	_SCREAMING_SNAKE_CASE							(   self: List[str]      ):

						'''simple docstring'''





						__magic_name__							=    {
						    'in_channels': 32,
						    'temb_channels': 1_28,
						}
						__magic_name__							=    self.dummy_input
						return init_dict, inputs_dict







	def 	_SCREAMING_SNAKE_CASE							(   self: str      ):

						'''simple docstring'''





						__magic_name__							=    [-0.1062, 1.7248, 0.3494, 1.4569, -0.0910, -1.2421, -0.9984, 0.6736, 1.0028]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   str       				=  UNetMidBlockaDCrossAttn  # noqa F405
	_lowercase  :   int       				=  "mid"







	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						__magic_name__,	__magic_name__							=    super().prepare_init_args_and_inputs_for_common()
						__magic_name__							=    32
						return init_dict, inputs_dict







	def 	_SCREAMING_SNAKE_CASE							(   self: Tuple      ):

						'''simple docstring'''





						__magic_name__							=    [0.0187, 2.4220, 0.4484, 1.1203, -0.6121, -1.5122, -0.8270, 0.7851, 1.8335]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   Tuple       				=  UNetMidBlockaDSimpleCrossAttn  # noqa F405
	_lowercase  :   str       				=  "mid"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: Any      ):

						'''simple docstring'''





						return super().get_dummy_input(include_encoder_hidden_states=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Tuple      ):

						'''simple docstring'''





						__magic_name__,	__magic_name__							=    super().prepare_init_args_and_inputs_for_common()
						__magic_name__							=    32
						return init_dict, inputs_dict







	def 	_SCREAMING_SNAKE_CASE							(   self: Any      ):

						'''simple docstring'''





						__magic_name__							=    [0.7143, 1.9974, 0.5448, 1.3977, 0.1282, -1.1237, -1.4238, 0.5530, 0.8880]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   List[Any]       				=  UpBlockaD  # noqa F405
	_lowercase  :   List[Any]       				=  "up"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: Tuple      ):

						'''simple docstring'''





						return super().get_dummy_input(include_res_hidden_states_tuple=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Any      ):

						'''simple docstring'''





						__magic_name__							=    [-0.2041, -0.4165, -0.3022, 0.0041, -0.6628, -0.7053, 0.1928, -0.0325, 0.0523]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   List[Any]       				=  ResnetUpsampleBlockaD  # noqa F405
	_lowercase  :   Dict       				=  "up"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[int]      ):

						'''simple docstring'''





						return super().get_dummy_input(include_res_hidden_states_tuple=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Dict      ):

						'''simple docstring'''





						__magic_name__							=    [0.2287, 0.3549, -0.1346, 0.4797, -0.1715, -0.9649, 0.7305, -0.5864, -0.6244]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   Any       				=  CrossAttnUpBlockaD  # noqa F405
	_lowercase  :   Union[str, Any]       				=  "up"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[int]      ):

						'''simple docstring'''





						return super().get_dummy_input(include_res_hidden_states_tuple=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: str      ):

						'''simple docstring'''





						__magic_name__,	__magic_name__							=    super().prepare_init_args_and_inputs_for_common()
						__magic_name__							=    32
						return init_dict, inputs_dict







	def 	_SCREAMING_SNAKE_CASE							(   self: Any      ):

						'''simple docstring'''





						__magic_name__							=    [-0.1403, -0.3515, -0.0420, -0.1425, 0.3167, 0.5094, -0.2181, 0.5931, 0.5582]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   str       				=  SimpleCrossAttnUpBlockaD  # noqa F405
	_lowercase  :   Tuple       				=  "up"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: List[str]      ):

						'''simple docstring'''





						return super().get_dummy_input(include_res_hidden_states_tuple=__UpperCamelCase  , include_encoder_hidden_states=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Union[str, Any]      ):

						'''simple docstring'''





						__magic_name__,	__magic_name__							=    super().prepare_init_args_and_inputs_for_common()
						__magic_name__							=    32
						return init_dict, inputs_dict







	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						__magic_name__							=    [0.2645, 0.1480, 0.0909, 0.8044, -0.9758, -0.9083, 0.0994, -1.1453, -0.7402]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   Optional[Any]       				=  AttnUpBlockaD  # noqa F405
	_lowercase  :   Optional[int]       				=  "up"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: str      ):

						'''simple docstring'''





						return super().get_dummy_input(include_res_hidden_states_tuple=__UpperCamelCase      )







	@unittest.skipIf(torch_device == 'mps'  , 'MPS result is not consistent'      )
	def 	_SCREAMING_SNAKE_CASE							(   self: Union[str, Any]      ):

						'''simple docstring'''





						__magic_name__							=    [0.0979, 0.1326, 0.0021, 0.0659, 0.2249, 0.0059, 0.1132, 0.5952, 0.1033]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   Union[str, Any]       				=  SkipUpBlockaD  # noqa F405
	_lowercase  :   int       				=  "up"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: Union[str, Any]      ):

						'''simple docstring'''





						return super().get_dummy_input(include_res_hidden_states_tuple=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Union[str, Any]      ):

						'''simple docstring'''





						__magic_name__							=    [-0.0893, -0.1234, -0.1506, -0.0332, 0.0123, -0.0211, 0.0566, 0.0143, 0.0362]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   Union[str, Any]       				=  AttnSkipUpBlockaD  # noqa F405
	_lowercase  :   Optional[Any]       				=  "up"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]      ):

						'''simple docstring'''





						return super().get_dummy_input(include_res_hidden_states_tuple=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Tuple      ):

						'''simple docstring'''





						__magic_name__							=    [0.0361, 0.0617, 0.2787, -0.0350, 0.0342, 0.3421, -0.0843, 0.0913, 0.3015]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   List[str]       				=  UpDecoderBlockaD  # noqa F405
	_lowercase  :   List[str]       				=  "up"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						return super().get_dummy_input(include_temb=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						__magic_name__							=    {'in_channels': 32, 'out_channels': 32}

						__magic_name__							=    self.dummy_input
						return init_dict, inputs_dict







	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]      ):

						'''simple docstring'''





						__magic_name__							=    [0.4404, 0.1998, -0.9886, -0.3320, -0.3128, -0.7034, -0.6955, -0.2338, -0.3137]
						super().test_output(__UpperCamelCase      )




class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   Optional[Any]       				=  AttnUpDecoderBlockaD  # noqa F405
	_lowercase  :   Any       				=  "up"







	@property
	def 	_SCREAMING_SNAKE_CASE							(   self: Dict      ):

						'''simple docstring'''





						return super().get_dummy_input(include_temb=__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: str      ):

						'''simple docstring'''





						__magic_name__							=    {'in_channels': 32, 'out_channels': 32}

						__magic_name__							=    self.dummy_input
						return init_dict, inputs_dict







	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						__magic_name__							=    [0.6738, 0.4491, 0.1055, 1.0710, 0.7316, 0.3339, 0.3352, 0.1023, 0.3568]
						super().test_output(__UpperCamelCase      )




