






import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel




class  UpperCamelCase_      (			snake_case_				):



	'''simple docstring'''




	lowerCAmelCase													= '''M-CLIP'''




	def __init__(       self       ,			a=10_24       ,			a=7_68       ,			**a					)       ->    Optional[int]:
								snake_case_				=							transformerDimSize
								snake_case_				=							imageDimSize
								super().__init__(**a					)






class  UpperCamelCase_      (			snake_case_				):



	'''simple docstring'''




	lowerCAmelCase													= MCLIPConfig




	def __init__(       self       ,			a       ,			*a       ,			**a					)       ->    List[str]:
								super().__init__(a       ,			*a       ,			**a					)
								snake_case_				=							XLMRobertaModel(a					)
								snake_case_				=							torch.nn.Linear(
								    in_features=config.transformerDimensions       ,			out_features=config.numDims					)






	def 							_UpperCamelCase			(       self       ,			a       ,			a					)       ->    Optional[Any]:
								snake_case_				=							self.transformer(input_ids=a       ,			attention_mask=a					)[0]
								snake_case_				=							(embs * attention_mask.unsqueeze(2					)).sum(dim=1					) / attention_mask.sum(dim=1					)[:, None]
								return self.LinearTransformation(a					), embs













from __future__ import annotations





def 						__UpperCAmelCase			(     a_							,     a_							,     a_							,     a_):  # noqa: E741
							while r - l > 1:
														snake_case_				=							(l + r) // 2
														if v[m] >= key:
																					snake_case_				=							m
														else:
																					snake_case_				=							m  # noqa: E741
							return r





def 						__UpperCAmelCase			(     a_):
							if len(a_) == 0:
														return 0

							snake_case_				=							[0] * len(a_)
							snake_case_				=							1

							snake_case_				=							v[0]

							for i in range(1							,     len(a_)):
														if v[i] < tail[0]:
																					snake_case_				=							v[i]
														elif v[i] > tail[length - 1]:
																					snake_case_				=							v[i]
																					length += 1
														else:
																					snake_case_				=							v[i]

							return length


if __name__ == "__main__":
	import doctest

	doctest.testmod()





