



"""simple docstring"""







from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


UpperCamelCase     =							logging.get_logger(__name__)

UpperCamelCase     =							{
    """shi-labs/dinat-mini-in1k-224""": """https://huggingface.co/shi-labs/dinat-mini-in1k-224/resolve/main/config.json""",
    # See all Dinat models at https://huggingface.co/models?filter=dinat
}






class       UpperCamelCase__			(   _lowerCAmelCase       ,		_lowerCAmelCase      ):

			"""simple docstring"""


			A__	:					Optional[Any]							  =     "dinat"

			A__	:					Optional[Any]							  =     {
			    "num_attention_heads": "num_heads",
			    "num_hidden_layers": "num_layers",
			}


			def __init__(      self						,	SCREAMING_SNAKE_CASE__=4						,	SCREAMING_SNAKE_CASE__=3						,	SCREAMING_SNAKE_CASE__=64						,	SCREAMING_SNAKE_CASE__=[3, 4, 6, 5]						,	SCREAMING_SNAKE_CASE__=[2, 4, 8, 16]						,	SCREAMING_SNAKE_CASE__=7						,	SCREAMING_SNAKE_CASE__=[[1, 8, 1], [1, 4, 1, 4], [1, 2, 1, 2, 1, 2], [1, 1, 1, 1, 1]]						,	SCREAMING_SNAKE_CASE__=3.0						,	SCREAMING_SNAKE_CASE__=True						,	SCREAMING_SNAKE_CASE__=0.0						,	SCREAMING_SNAKE_CASE__=0.0						,	SCREAMING_SNAKE_CASE__=0.1						,	SCREAMING_SNAKE_CASE__="gelu"						,	SCREAMING_SNAKE_CASE__=0.0_2						,	SCREAMING_SNAKE_CASE__=1e-5						,	SCREAMING_SNAKE_CASE__=0.0						,	SCREAMING_SNAKE_CASE__=None						,	SCREAMING_SNAKE_CASE__=None						,	**SCREAMING_SNAKE_CASE__						,	)      ->	Union[str, Any]:
				super().__init__(**SCREAMING_SNAKE_CASE__		)

				A__											=					patch_size
				A__											=					num_channels
				A__											=					embed_dim
				A__											=					depths
				A__											=					len(SCREAMING_SNAKE_CASE__		)
				A__											=					num_heads
				A__											=					kernel_size
				A__											=					dilations
				A__											=					mlp_ratio
				A__											=					qkv_bias
				A__											=					hidden_dropout_prob
				A__											=					attention_probs_dropout_prob
				A__											=					drop_path_rate
				A__											=					hidden_act
				A__											=					layer_norm_eps
				A__											=					initializer_range
				# we set the hidden_size attribute in order to make Dinat work with VisionEncoderDecoderModel
				# this indicates the channel dimension after the last stage of the model
				A__											=					int(embed_dim * 2 ** (len(SCREAMING_SNAKE_CASE__		) - 1)		)
				A__											=					layer_scale_init_value
				A__											=					["stem"] + [f"""stage{idx}""" for idx in range(1						,	len(SCREAMING_SNAKE_CASE__		) + 1		)]
				A__							,							A__											=					get_aligned_output_features_output_indices(
				    out_features=SCREAMING_SNAKE_CASE__						,	out_indices=SCREAMING_SNAKE_CASE__						,	stage_names=self.stage_names		)








def    a__    (		snake_case__					:							Tuple     ):  # noqa: E741
  _UpperCAmelCase		:							Dict							=     len(snake_case__     )
  _UpperCAmelCase		:							Tuple							=     0
  _UpperCAmelCase		:							Union[str, Any]							=     [0] * n
  _UpperCAmelCase		:							Union[str, Any]							=     [False] * n
  _UpperCAmelCase		:							Tuple							=     [False] * n

  def dfs(snake_case__					:							List[str]						,   snake_case__					:							int						,   snake_case__					:							str						,   snake_case__					:							int     ):
    if parent == root:
      out_edge_count += 1
    _UpperCAmelCase		:							List[Any]							=     True
    _UpperCAmelCase		:							List[str]							=     at

    for to in l[at]:
      if to == parent:
        pass
      elif not visited[to]:
        _UpperCAmelCase		:							Optional[Any]							=     dfs(snake_case__						,   snake_case__						,   snake_case__						,   snake_case__     )
        _UpperCAmelCase		:							Optional[Any]							=     min(low[at]						,   low[to]     )

        # AP found via bridge
        if at < low[to]:
          _UpperCAmelCase		:							List[str]							=     True
        # AP found via cycle
        if at == low[to]:
          _UpperCAmelCase		:							Optional[Any]							=     True
      else:
        _UpperCAmelCase		:							str							=     min(low[at]						,   snake_case__     )
    return out_edge_count

  for i in range(snake_case__     ):
    if not visited[i]:
      _UpperCAmelCase		:							List[Any]							=     0
      _UpperCAmelCase		:							List[str]							=     dfs(snake_case__						,   snake_case__						,   -1						,   snake_case__     )
      _UpperCAmelCase		:							Optional[Any]							=     out_edge_count > 1

  for x in range(len(snake_case__     )     ):
    if is_art[x] is True:
      print(snake_case__     )


# Adjacency list of graph
SCREAMING_SNAKE_CASE__					:     Optional[Any]       =     {
    0: [1, 2],
    1: [0, 2],
    2: [0, 1, 3, 5],
    3: [2, 4],
    4: [3],
    5: [2, 6, 8],
    6: [5, 7],
    7: [6, 8],
    8: [5, 7],
}





compute_ap(data)





