





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


_SCREAMING_SNAKE_CASE   						=		{"""configuration_hubert""": ["""HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """HubertConfig"""]}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_SCREAMING_SNAKE_CASE   						=		[
						    """HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """HubertForCTC""",
						    """HubertForSequenceClassification""",
						    """HubertModel""",
						    """HubertPreTrainedModel""",
						]


try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_SCREAMING_SNAKE_CASE   						=		[
						    """TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """TFHubertForCTC""",
						    """TFHubertModel""",
						    """TFHubertPreTrainedModel""",
						]

if TYPE_CHECKING:
						from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_hubert import (
												    HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    HubertForCTC,
												    HubertForSequenceClassification,
												    HubertModel,
												    HubertPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_hubert import (
												    TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFHubertForCTC,
												    TFHubertModel,
												    TFHubertPreTrainedModel,
												)


else:
						import sys

						_SCREAMING_SNAKE_CASE   						=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


"""simple docstring"""




def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





					if not root or root not in binary_tree_mirror_dictionary:
										return
					lowerCamelCase__				,						lowerCamelCase__		:   Tuple  				=					binary_tree_mirror_dictionary[root][:2]
					lowerCamelCase__		:   Optional[Any]  				=					[right_child, left_child]
					binary_tree_mirror_dict(_lowercase							, _lowercase						)
					binary_tree_mirror_dict(_lowercase							, _lowercase						)



def 				__a       (			_lowercase							, _lowercase = 1						):







					"""simple docstring"""





					if not binary_tree:
										raise ValueError('''binary tree cannot be empty'''						)
					if root not in binary_tree:
										lowerCamelCase__		:   Dict  				=					f"""root {root} is not present in the binary_tree"""
										raise ValueError(_lowercase						)
					lowerCamelCase__		:   Optional[Any]  				=					dict(_lowercase						)
					binary_tree_mirror_dict(_lowercase							, _lowercase						)
					return binary_tree_mirror_dictionary


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






