


import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin




class       lowercase_					(lowercase__      ,					lowercase__      ,					lowercase__   ):





				@register_to_config
				def __init__(				self       ,  lowercase_       ,  lowercase_       ,  lowercase_       ,  lowercase_       ,  lowercase_       ,  lowercase_       ,  lowercase_       ,  lowercase_       ,  lowercase_       ,  lowercase_ = False       ,  )  -> str:
											super().__init__()

											a__      =nn.Embedding(lowercase_       ,  lowercase_)

											a__      =nn.Embedding(lowercase_       ,  lowercase_)
											a__      =False

											a__      =nn.Dropout(p=lowercase_)

											a__      =TaConfig(
											    vocab_size=lowercase_       ,  d_model=lowercase_       ,  num_heads=lowercase_       ,  d_kv=lowercase_       ,  d_ff=lowercase_       ,  dropout_rate=lowercase_       ,  feed_forward_proj=lowercase_       ,  is_decoder=lowercase_       ,  is_encoder_decoder=lowercase_       ,  )

											a__      =nn.ModuleList()
											for lyr_num in range(lowercase_):
																		a__      =TaBlock(lowercase_)
																		self.encoders.append(lowercase_)

											a__      =TaLayerNorm(lowercase_)
											a__      =nn.Dropout(p=lowercase_)





				def 						__UpperCamelCase    (				self       ,  lowercase_       ,  lowercase_)  -> Tuple:
											a__      =self.token_embedder(lowercase_)

											a__      =encoder_input_tokens.shape[1]
											a__      =torch.arange(lowercase_       ,  device=encoder_input_tokens.device)
											x += self.position_encoding(lowercase_)

											a__      =self.dropout_pre(lowercase_)

											# inverted the attention mask
											a__      =encoder_input_tokens.size()
											a__      =self.get_extended_attention_mask(lowercase_       ,  lowercase_)

											for lyr in self.encoders:
																		a__      =lyr(lowercase_       ,  lowercase_)[0]
											a__      =self.layer_norm(lowercase_)

											return self.dropout_post(lowercase_), encoder_inputs_mask





import inspect
import unittest






class      UpperCamelCase(	unittest.TestCase ):


					def 				SCREAMING_SNAKE_CASE_	(    self						:		Dict    )      ->						List[Any]:




											'''simple docstring'''

											try:
																	import diffusers  # noqa: F401
											except ImportError:
																	assert False






					def 				SCREAMING_SNAKE_CASE_	(    self						:		Optional[int]    )      ->						Any:




											'''simple docstring'''

											import diffusers
											from diffusers.dependency_versions_table import deps

											__snake_case				=		inspect.getmembers(SCREAMING_SNAKE_CASE  ,     inspect.isclass    )

											for cls_name, cls_module in all_classes:
																	if "dummy_" in cls_module.__module__:
																							for backend in cls_module._backends:
																													if backend == "k_diffusion":
																																			__snake_case				=		"k-diffusion"
																													elif backend == "invisible_watermark":
																																			__snake_case				=		"invisible-watermark"
																													assert backend in deps, f'''{backend} is not in the deps table!'''





