





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__lowerCamelCase	:					List[Any]			  =					{"""configuration_mbart""": ["""MBART_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MBartConfig""", """MBartOnnxConfig"""]}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase	:					List[Any]			  =					["""MBartTokenizer"""]

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase	:					Optional[Any]			  =					["""MBartTokenizerFast"""]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase	:					Optional[int]			  =					[
        """MBART_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """MBartForCausalLM""",
        """MBartForConditionalGeneration""",
        """MBartForQuestionAnswering""",
        """MBartForSequenceClassification""",
        """MBartModel""",
        """MBartPreTrainedModel""",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase	:					Any			  =					[
        """TFMBartForConditionalGeneration""",
        """TFMBartModel""",
        """TFMBartPreTrainedModel""",
    ]

try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase	:					List[Any]			  =					[
        """FlaxMBartForConditionalGeneration""",
        """FlaxMBartForQuestionAnswering""",
        """FlaxMBartForSequenceClassification""",
        """FlaxMBartModel""",
        """FlaxMBartPreTrainedModel""",
    ]


if TYPE_CHECKING:
    from .configuration_mbart import MBART_PRETRAINED_CONFIG_ARCHIVE_MAP, MBartConfig, MBartOnnxConfig

    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_mbart import MBartTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_mbart_fast import MBartTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mbart import (
            MBART_PRETRAINED_MODEL_ARCHIVE_LIST,
            MBartForCausalLM,
            MBartForConditionalGeneration,
            MBartForQuestionAnswering,
            MBartForSequenceClassification,
            MBartModel,
            MBartPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_mbart import TFMBartForConditionalGeneration, TFMBartModel, TFMBartPreTrainedModel

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_mbart import (
            FlaxMBartForConditionalGeneration,
            FlaxMBartForQuestionAnswering,
            FlaxMBartForSequenceClassification,
            FlaxMBartModel,
            FlaxMBartPreTrainedModel,
        )

else:
    import sys

    __lowerCamelCase	:					Optional[Any]			  =					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)







class  A__       :  # Public class to implement a graph





      def __init__(			self	,							A_	,							A_	,							A_       ):
       '''simple docstring'''




       UpperCamelCase     : Optional[int]	     =       row
       UpperCamelCase     : Any	     =       col
       UpperCamelCase     : Optional[Any]	     =       graph





      def 	__UpperCamelCase(			self	,							A_	,							A_	,							A_       ):
       '''simple docstring'''




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





      def 	__UpperCamelCase(			self	,							A_	,							A_	,							A_       ):
       '''simple docstring'''




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





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




       UpperCamelCase     : str	     =       [[False for j in range(self.COL       )] for i in range(self.ROW       )]
       UpperCamelCase     : int	     =       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(A_	,							A_	,							A_       )
          count += 1
       return count
