
"""simple docstring"""





import copy
import os
from typing import TYPE_CHECKING, List, Union


if TYPE_CHECKING:
    pass

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_a		       =							logging.get_logger(__name__)

_a		       =							{
    'kakaobrain/align-base': 'https://huggingface.co/kakaobrain/align-base/resolve/main/config.json',
}


class A_	(lowercase__      ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						Dict       =		"""align_text_model"""







  def __init__(		self				,   lowercase_=3_0522				,   lowercase_=768				,   lowercase_=12				,   lowercase_=12				,   lowercase_=3072				,   lowercase_="gelu"				,   lowercase_=0.1				,   lowercase_=0.1				,   lowercase_=512				,   lowercase_=2				,   lowercase_=0.02				,   lowercase_=1E-1_2				,   lowercase_=0				,   lowercase_="absolute"				,   lowercase_=True				,   **lowercase_				,   ):

     """simple docstring"""
     super().__init__(**lowercase_  )

     UpperCAmelCase_					:					int			     =    vocab_size
     UpperCAmelCase_					:					Tuple			     =    hidden_size
     UpperCAmelCase_					:					Optional[int]			     =    num_hidden_layers
     UpperCAmelCase_					:					List[str]			     =    num_attention_heads
     UpperCAmelCase_					:					str			     =    hidden_act
     UpperCAmelCase_					:					Tuple			     =    intermediate_size
     UpperCAmelCase_					:					Any			     =    hidden_dropout_prob
     UpperCAmelCase_					:					int			     =    attention_probs_dropout_prob
     UpperCAmelCase_					:					Union[str, Any]			     =    max_position_embeddings
     UpperCAmelCase_					:					str			     =    type_vocab_size
     UpperCAmelCase_					:					Dict			     =    initializer_range
     UpperCAmelCase_					:					int			     =    layer_norm_eps
     UpperCAmelCase_					:					Tuple			     =    position_embedding_type
     UpperCAmelCase_					:					Dict			     =    use_cache
     UpperCAmelCase_					:					Optional[int]			     =    pad_token_id







  @classmethod
  def        UpperCamelCase__					(		cls				,   lowercase_				,   **lowercase_  ):

     """simple docstring"""
     cls._set_token_in_kwargs(lowercase_  )

     UpperCAmelCase_     ,   UpperCAmelCase_					:					int			     =    cls.get_config_dict(lowercase_				,   **lowercase_  )

     # get the text config dict if we are loading from AlignConfig
     if config_dict.get("model_type"  ) == "align":
        UpperCAmelCase_					:					Union[str, Any]			     =    config_dict["text_config"]

     if "model_type" in config_dict and hasattr(cls				,   "model_type"  ) and config_dict["model_type"] != cls.model_type:
        logger.warning(
            F"""You are using a model of type {config_dict["model_type"]} to instantiate a model of type """
            F"""{cls.model_type}. This is not supported for all configurations of models and can yield errors."""  )

     return cls.from_dict(lowercase_				,   **lowercase_  )




class A_	(lowercase__      ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						int       =		"""align_vision_model"""







  def __init__(		self				,   lowercase_ = 3				,   lowercase_ = 600				,   lowercase_ = 2.0				,   lowercase_ = 3.1				,   lowercase_ = 8				,   lowercase_ = [3, 3, 5, 3, 5, 5, 3]				,   lowercase_ = [32, 16, 24, 40, 80, 112, 192]				,   lowercase_ = [16, 24, 40, 80, 112, 192, 320]				,   lowercase_ = []				,   lowercase_ = [1, 2, 2, 2, 1, 2, 1]				,   lowercase_ = [1, 2, 2, 3, 3, 4, 1]				,   lowercase_ = [1, 6, 6, 6, 6, 6, 6]				,   lowercase_ = 0.25				,   lowercase_ = "swish"				,   lowercase_ = 2560				,   lowercase_ = "mean"				,   lowercase_ = 0.02				,   lowercase_ = 0.0_01				,   lowercase_ = 0.99				,   lowercase_ = 0.2				,   **lowercase_				,   ):

     """simple docstring"""
     super().__init__(**lowercase_  )

     UpperCAmelCase_					:					List[str]			     =    num_channels
     UpperCAmelCase_					:					Optional[Any]			     =    image_size
     UpperCAmelCase_					:					Any			     =    width_coefficient
     UpperCAmelCase_					:					Dict			     =    depth_coefficient
     UpperCAmelCase_					:					Union[str, Any]			     =    depth_divisor
     UpperCAmelCase_					:					int			     =    kernel_sizes
     UpperCAmelCase_					:					Dict			     =    in_channels
     UpperCAmelCase_					:					Tuple			     =    out_channels
     UpperCAmelCase_					:					Optional[int]			     =    depthwise_padding
     UpperCAmelCase_					:					Dict			     =    strides
     UpperCAmelCase_					:					Tuple			     =    num_block_repeats
     UpperCAmelCase_					:					Tuple			     =    expand_ratios
     UpperCAmelCase_					:					Dict			     =    squeeze_expansion_ratio
     UpperCAmelCase_					:					Union[str, Any]			     =    hidden_act
     UpperCAmelCase_					:					Optional[Any]			     =    hidden_dim
     UpperCAmelCase_					:					List[Any]			     =    pooling_type
     UpperCAmelCase_					:					Union[str, Any]			     =    initializer_range
     UpperCAmelCase_					:					str			     =    batch_norm_eps
     UpperCAmelCase_					:					List[str]			     =    batch_norm_momentum
     UpperCAmelCase_					:					Any			     =    drop_connect_rate
     UpperCAmelCase_					:					str			     =    sum(lowercase_  ) * 4







  @classmethod
  def        UpperCamelCase__					(		cls				,   lowercase_				,   **lowercase_  ):

     """simple docstring"""
     cls._set_token_in_kwargs(lowercase_  )

     UpperCAmelCase_     ,   UpperCAmelCase_					:					List[str]			     =    cls.get_config_dict(lowercase_				,   **lowercase_  )

     # get the vision config dict if we are loading from AlignConfig
     if config_dict.get("model_type"  ) == "align":
        UpperCAmelCase_					:					Any			     =    config_dict["vision_config"]

     if "model_type" in config_dict and hasattr(cls				,   "model_type"  ) and config_dict["model_type"] != cls.model_type:
        logger.warning(
            F"""You are using a model of type {config_dict["model_type"]} to instantiate a model of type """
            F"""{cls.model_type}. This is not supported for all configurations of models and can yield errors."""  )

     return cls.from_dict(lowercase_				,   **lowercase_  )




class A_	(lowercase__      ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						int       =		"""align"""
  SCREAMING_SNAKE_CASE__			:						str       =		True







  def __init__(		self				,   lowercase_=None				,   lowercase_=None				,   lowercase_=640				,   lowercase_=1.0				,   lowercase_=0.02				,   **lowercase_				,   ):

     """simple docstring"""
     super().__init__(**lowercase_  )

     if text_config is None:
        UpperCAmelCase_					:					Union[str, Any]			     =    {}
        logger.info("text_config is None. Initializing the AlignTextConfig with default values."  )

     if vision_config is None:
        UpperCAmelCase_					:					Tuple			     =    {}
        logger.info("vision_config is None. Initializing the AlignVisionConfig with default values."  )

     UpperCAmelCase_					:					Tuple			     =    AlignTextConfig(**lowercase_  )
     UpperCAmelCase_					:					str			     =    AlignVisionConfig(**lowercase_  )

     UpperCAmelCase_					:					List[Any]			     =    projection_dim
     UpperCAmelCase_					:					Union[str, Any]			     =    temperature_init_value
     UpperCAmelCase_					:					Union[str, Any]			     =    initializer_range







  @classmethod
  def        UpperCamelCase__					(		cls				,   lowercase_				,   lowercase_				,   **lowercase_  ):

     """simple docstring"""
     return cls(text_config=text_config.to_dict()				,   vision_config=vision_config.to_dict()				,   **lowercase_  )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					int			     =    copy.deepcopy(self.__dict__  )
     UpperCAmelCase_					:					Dict			     =    self.text_config.to_dict()
     UpperCAmelCase_					:					str			     =    self.vision_config.to_dict()
     UpperCAmelCase_					:					Optional[Any]			     =    self.__class__.model_type
     return output



from multiprocessing import Lock, Pipe, Process

# lock used to ensure that two processes do not access a pipe at the same time
__a  :     List[str]       =  Lock()





def 				UpperCAmelCase						(    lowercase							,			lowercase							,			lowercase							,			lowercase							,			lowercase							,			lowercase							,			lowercase							):







				"""simple docstring"""



				global process_lock

				# we perform n swaps since after n swaps we know we are sorted
				# we *could* stop early if we are sorted already, but it takes as long to
				# find out we are sorted as it does to sort the list with this algorithm
				for i in range(0							,			10							):
								if (i + position) % 2 == 0 and r_send is not None:
												# send your value to your right neighbor
												process_lock.acquire()
												r_send[1].send(lowercase							)
												process_lock.release()

												# receive your right neighbor's value
												process_lock.acquire()
												__lowercase 			=							rr_cv[0].recv()
												process_lock.release()

												# take the lower value since you are on the left
												__lowercase 			=							min(lowercase							,			lowercase							)
								elif (i + position) % 2 != 0 and l_send is not None:
												# send your value to your left neighbor
												process_lock.acquire()
												l_send[1].send(lowercase							)
												process_lock.release()

												# receive your left neighbor's value
												process_lock.acquire()
												__lowercase 			=							lr_cv[0].recv()
												process_lock.release()

												# take the higher value since you are on the right
												__lowercase 			=							max(lowercase							,			lowercase							)
    # after all swaps are performed, send the values back to main
				result_pipe[1].send(lowercase							)





def 				UpperCAmelCase						(    lowercase							):







				"""simple docstring"""



				__lowercase 			=							[]
				__lowercase 			=							[]
				# initialize the list of pipes where the values will be retrieved
				for _ in arr:
								result_pipe.append(Pipe()							)
				# creates the processes
				# the first and last process only have one neighbor so they are made outside
				# of the loop
				__lowercase 			=							Pipe()
				__lowercase 			=							Pipe()
				process_array_.append(
				    Process(
				        target=lowercase							,			args=(0, arr[0], None, temp_rs, None, temp_rr, result_pipe[0])							,			)							)
				__lowercase 			=							temp_rs
				__lowercase 			=							temp_rr

				for i in range(1							,			len(lowercase							) - 1							):
								__lowercase 			=							Pipe()
								__lowercase 			=							Pipe()
								process_array_.append(
								    Process(
								        target=lowercase							,			args=(i, arr[i], temp_ls, temp_rs, temp_lr, temp_rr, result_pipe[i])							,			)							)
								__lowercase 			=							temp_rs
								__lowercase 			=							temp_rr

				process_array_.append(
				    Process(
				        target=lowercase							,			args=(
				            len(lowercase							) - 1,
				            arr[len(lowercase							) - 1],
				            temp_ls,
				            None,
				            temp_lr,
				            None,
				            result_pipe[len(lowercase							) - 1],
				        )							,			)							)

				# start the processes
				for p in process_array_:
								p.start()

				# wait for the processes to end and write their values to the list
				for p in range(0							,			len(lowercase							)							):
								__lowercase 			=							result_pipe[p][0].recv()
								process_array_[p].join()
				return arr





def 				UpperCAmelCase						(    ):







				"""simple docstring"""



				__lowercase 			=							list(range(10							,			0							,			-1							)							)
				print('''Initial List'''							)
				print(*lowercase							)
				__lowercase 			=							odd_even_transposition(lowercase							)
				print('''Sorted List\n'''							)
				print(*lowercase							)


if __name__ == "__main__":
		main()