
"""simple docstring"""

import copy
import os
from typing import Union

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


UpperCamelCase     :    str       =			logging.get_logger(__name__)

UpperCamelCase     :    int       =			{
    "microsoft/git-base": "https://huggingface.co/microsoft/git-base/resolve/main/config.json",
}

class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):
     lowercase						       =						"git_vision_model"





     def __init__(     self     ,					__UpperCAmelCase=768     ,					__UpperCAmelCase=3072     ,					__UpperCAmelCase=12     ,					__UpperCAmelCase=12     ,					__UpperCAmelCase=3     ,					__UpperCAmelCase=224     ,					__UpperCAmelCase=16     ,					__UpperCAmelCase="quick_gelu"     ,					__UpperCAmelCase=1E-5     ,					__UpperCAmelCase=0.0     ,					__UpperCAmelCase=0.0_2     ,					**__UpperCAmelCase     ,					):

      '''simple docstring'''




      super().__init__(**__UpperCAmelCase				)

      __UpperCamelCase      =	hidden_size
      __UpperCamelCase      =	intermediate_size
      __UpperCamelCase      =	num_hidden_layers
      __UpperCamelCase      =	num_attention_heads
      __UpperCamelCase      =	num_channels
      __UpperCamelCase      =	patch_size
      __UpperCamelCase      =	image_size
      __UpperCamelCase      =	initializer_range
      __UpperCamelCase      =	attention_dropout
      __UpperCamelCase      =	layer_norm_eps
      __UpperCamelCase      =	hidden_act







     @classmethod
     def 						UpperCAmelCase (     cls     ,					__UpperCAmelCase     ,					**__UpperCAmelCase				):

      '''simple docstring'''




      cls._set_token_in_kwargs(__UpperCAmelCase				)

      __UpperCamelCase  ,     __UpperCamelCase      =	cls.get_config_dict(__UpperCAmelCase     ,					**__UpperCAmelCase				)

      # get the vision config dict if we are loading from GITConfig
      if config_dict.get('model_type'				) == "git":
       __UpperCamelCase      =	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(__UpperCAmelCase     ,					**__UpperCAmelCase				)


class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):
     lowercase						       =						"git"





     def __init__(     self     ,					__UpperCAmelCase=None     ,					__UpperCAmelCase=3_0522     ,					__UpperCAmelCase=768     ,					__UpperCAmelCase=6     ,					__UpperCAmelCase=12     ,					__UpperCAmelCase=3072     ,					__UpperCAmelCase="gelu"     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase=1024     ,					__UpperCAmelCase=0.0_2     ,					__UpperCAmelCase=1E-12     ,					__UpperCAmelCase=0     ,					__UpperCAmelCase="absolute"     ,					__UpperCAmelCase=True     ,					__UpperCAmelCase=False     ,					__UpperCAmelCase=101     ,					__UpperCAmelCase=102     ,					__UpperCAmelCase=None     ,					**__UpperCAmelCase     ,					):

      '''simple docstring'''




      super().__init__(bos_token_id=__UpperCAmelCase     ,					eos_token_id=__UpperCAmelCase     ,					pad_token_id=__UpperCAmelCase     ,					**__UpperCAmelCase				)

      if vision_config is None:
       __UpperCamelCase      =	{}
       logger.info('vision_config is None. initializing the GitVisionConfig with default values.'				)

      __UpperCamelCase      =	GitVisionConfig(**__UpperCAmelCase				)
      __UpperCamelCase      =	vocab_size
      __UpperCamelCase      =	hidden_size
      __UpperCamelCase      =	num_hidden_layers
      __UpperCamelCase      =	num_attention_heads
      __UpperCamelCase      =	hidden_act
      __UpperCamelCase      =	intermediate_size
      __UpperCamelCase      =	hidden_dropout_prob
      __UpperCamelCase      =	attention_probs_dropout_prob
      __UpperCamelCase      =	max_position_embeddings
      __UpperCamelCase      =	initializer_range
      __UpperCamelCase      =	layer_norm_eps
      __UpperCamelCase      =	position_embedding_type
      __UpperCamelCase      =	use_cache
      __UpperCamelCase      =	tie_word_embeddings
      __UpperCamelCase      =	num_image_with_embedding

      __UpperCamelCase      =	bos_token_id
      __UpperCamelCase      =	eos_token_id







     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	copy.deepcopy(self.__dict__				)
      __UpperCamelCase      =	self.vision_config.to_dict()
      __UpperCamelCase      =	self.__class__.model_type
      return output





"""simple docstring"""

UpperCamelCase     :    Union[str, Any]       =			[
    [0, 1_6, 1_3, 0, 0, 0],
    [0, 0, 1_0, 1_2, 0, 0],
    [0, 4, 0, 0, 1_4, 0],
    [0, 0, 9, 0, 0, 2_0],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]






def 							A						(    snake_case				:Dict    , snake_case				:Tuple    , snake_case				:str    , snake_case				:Optional[int]		)				->     Union[str, Any]:
 # Return True if there is node that has not iterated.
 __UpperCamelCase      =	[False] * len(snake_case		)
 __UpperCamelCase      =	[s]
 __UpperCamelCase      =	True

 while queue:
  __UpperCamelCase      =	queue.pop(0		)
  for ind in range(len(graph[u]		)		):
   if visited[ind] is False and graph[u][ind] > 0:
    queue.append(snake_case		)
    __UpperCamelCase      =	True
    __UpperCamelCase      =	u

 return visited[t]






def 							A						(    snake_case				:int    , snake_case				:Any    , snake_case				:Union[str, Any]		)				->     Optional[int]:
 __UpperCamelCase      =	[-1] * (len(snake_case		))
 __UpperCamelCase      =	0
 __UpperCamelCase      =	[]
 __UpperCamelCase      =	[i[:] for i in graph]  # Record original cut, copy.
 while bfs(snake_case    , snake_case    , snake_case    , snake_case		):
  __UpperCamelCase      =	float('Inf'		)
  __UpperCamelCase      =	sink

  while s != source:
   # Find the minimum value in select path
   __UpperCamelCase      =	min(snake_case    , graph[parent[s]][s]		)
   __UpperCamelCase      =	parent[s]

  max_flow += path_flow
  __UpperCamelCase      =	sink

  while v != source:
   __UpperCamelCase      =	parent[v]
   graph[u][v] -= path_flow
   graph[v][u] += path_flow
   __UpperCamelCase      =	parent[v]

 for i in range(len(snake_case		)		):
  for j in range(len(graph[0]		)		):
   if graph[i][j] == 0 and temp[i][j] > 0:
    res.append((i, j)		)

 return res


if __name__ == "__main__":
      print(mincut(test_graph, source=0, sink=5))



