




class 		__A      :  # Public class to implement a graph

						def __init__(		self   :Union[str, Any]    , __snake_case   :int    , __snake_case   :int    , __snake_case   :list[list[bool]] ):
										'''simple docstring'''

										__magic_name__	:	Union[str, Any]								=row
										__magic_name__	:	Any								=col
										__magic_name__	:	int								=graph

						def     A__						(		self   :Tuple    , __snake_case   :int    , __snake_case   :int    , __snake_case   :list[list[bool]] ):
										'''simple docstring'''

										return (
										    0 <= i < self.ROW
										    and 0 <= j < self.COL
										    and not visited[i][j]
										    and self.graph[i][j]
										)

						def     A__						(		self   :Dict    , __snake_case   :int    , __snake_case   :int    , __snake_case   :list[list[bool]] ):
										'''simple docstring'''

										__magic_name__	:	List[str]								=[-1, -1, -1, 0, 0, 1, 1, 1]  # Coordinate order
										__magic_name__	:	List[Any]								=[-1, 0, 1, -1, 1, -1, 0, 1]
										__magic_name__	:	Union[str, Any]								=True  # Make those cells visited
										for k in range(8 ):
														if self.is_safe(i + row_nbr[k]    , j + col_nbr[k]    , __snake_case ):
																		self.diffs(i + row_nbr[k]    , j + col_nbr[k]    , __snake_case )


						def     A__						(		self   :Dict ):  # And finally, count all islands.
										'''simple docstring'''

										__magic_name__	:	int								=[[False for j in range(self.COL )] for i in range(self.ROW )]
										__magic_name__	:	Union[str, Any]								=0
										for i in range(self.ROW ):
														for j in range(self.COL ):
																		if visited[i][j] is False and self.graph[i][j] == 1:
																						self.diffs(__snake_case    , __snake_case    , __snake_case )
																						count += 1
										return count










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase_		:				Dict									=     {"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase_		:				Optional[int]									=     [
							    "WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "WavLMForAudioFrameClassification",
							    "WavLMForCTC",
							    "WavLMForSequenceClassification",
							    "WavLMForXVector",
							    "WavLMModel",
							    "WavLMPreTrainedModel",
							]

if TYPE_CHECKING:
							from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_wavlm import (
														    WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
														    WavLMForAudioFrameClassification,
														    WavLMForCTC,
														    WavLMForSequenceClassification,
														    WavLMForXVector,
														    WavLMModel,
														    WavLMPreTrainedModel,
														)

else:
							import sys

							UpperCAmelCase_		:				Union[str, Any]									=     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




