






from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE								=  {
    'configuration_bart': ['BART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BartConfig', 'BartOnnxConfig'],
    'tokenization_bart': ['BartTokenizer'],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE								=  ['BartTokenizerFast']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE								=  [
      'BART_PRETRAINED_MODEL_ARCHIVE_LIST',
      'BartForCausalLM',
      'BartForConditionalGeneration',
      'BartForQuestionAnswering',
      'BartForSequenceClassification',
      'BartModel',
      'BartPretrainedModel',
      'PretrainedBartModel',
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE								=  [
      'TFBartForConditionalGeneration',
      'TFBartForSequenceClassification',
      'TFBartModel',
      'TFBartPretrainedModel',
  ]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE								=  [
      'FlaxBartDecoderPreTrainedModel',
      'FlaxBartForCausalLM',
      'FlaxBartForConditionalGeneration',
      'FlaxBartForQuestionAnswering',
      'FlaxBartForSequenceClassification',
      'FlaxBartModel',
      'FlaxBartPreTrainedModel',
  ]

if TYPE_CHECKING:
  from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
  from .tokenization_bart import BartTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_bart_fast import BartTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_bart import (
        BART_PRETRAINED_MODEL_ARCHIVE_LIST,
        BartForCausalLM,
        BartForConditionalGeneration,
        BartForQuestionAnswering,
        BartForSequenceClassification,
        BartModel,
        BartPretrainedModel,
        PretrainedBartModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_bart import (
        TFBartForConditionalGeneration,
        TFBartForSequenceClassification,
        TFBartModel,
        TFBartPretrainedModel,
    )

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_bart import (
        FlaxBartDecoderPreTrainedModel,
        FlaxBartForCausalLM,
        FlaxBartForConditionalGeneration,
        FlaxBartForQuestionAnswering,
        FlaxBartForSequenceClassification,
        FlaxBartModel,
        FlaxBartPreTrainedModel,
    )

else:
  import sys

  SCREAMING_SNAKE_CASE								=  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)












def        _lowerCamelCase		(  __A      :							dict						,						__A      :							int	) ->   str:
    if not root or root not in binary_tree_mirror_dictionary:
        return
    _UpperCAmelCase					,	_UpperCAmelCase			: int     					=			binary_tree_mirror_dictionary[root][:2]
    _UpperCAmelCase			: int     					=			[right_child, left_child]
    binary_tree_mirror_dict(__A						,						__A	)
    binary_tree_mirror_dict(__A						,						__A	)

def        _lowerCamelCase		(  __A      :							dict						,						__A      :							int = 1	) ->   dict:
    if not binary_tree:
        raise ValueError('''binary tree cannot be empty'''	)
    if root not in binary_tree:
        _UpperCAmelCase			: Dict     					=			f'''root {root} is not present in the binary_tree'''
        raise ValueError(__A	)
    _UpperCAmelCase			: int     					=			dict(__A	)
    binary_tree_mirror_dict(__A						,						__A	)
    return binary_tree_mirror_dictionary


if __name__ == "__main__":
  SCREAMING_SNAKE_CASE								=  {1: [2, 3], 2: [4, 5], 3: [6, 7], 7: [8, 9]}
  print(F'Binary tree: {binary_tree}')
  SCREAMING_SNAKE_CASE								=  binary_tree_mirror(binary_tree, 5)
  print(F'Binary tree mirror: {binary_tree_mirror_dictionary}')




