





'''simple docstring'''






from __future__ import annotations

from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any


@dataclass
class   _lowercase						:
   _UpperCamelCase       		=   42
   _UpperCamelCase       		=   None
   _UpperCamelCase       		=   None







def 							_lowerCamelCase(  )		->  Node | None:
    A       :       Union[str, Any]							=						Node(1		)
    A       :       str							=						Node(2		)
    A       :       List[str]							=						Node(3		)
    A       :       Optional[Any]							=						Node(4		)
    A       :       str							=						Node(5		)
    return tree
def 							_lowerCamelCase(  UpperCamelCase__    : Node | None		)		->  list[int]:
    return [root.data, *preorder(root.left		), *preorder(root.right		)] if root else []
def 							_lowerCamelCase(  UpperCamelCase__    : Node | None		)		->  list[int]:
    return postorder(root.left		) + postorder(root.right		) + [root.data] if root else []
def 							_lowerCamelCase(  UpperCamelCase__    : Node | None		)		->  list[int]:
    return [*inorder(root.left		), root.data, *inorder(root.right		)] if root else []
def 							_lowerCamelCase(  UpperCamelCase__    : Node | None		)		->  int:
    return (max(height(root.left		)    ,       height(root.right		)		) + 1) if root else 0
def 							_lowerCamelCase(  UpperCamelCase__    : Node | None		)		->  Sequence[Node | None]:
    A       :       list[Any]							=						[]

    if root is None:
        return output

    A       :       List[str]							=						deque([root]		)

    while process_queue:
        A       :       str							=						process_queue.popleft()
        output.append(node.data		)

        if node.left:
            process_queue.append(node.left		)
        if node.right:
            process_queue.append(node.right		)
    return output
def 							_lowerCamelCase(  UpperCamelCase__    : Node | None    ,       UpperCamelCase__    : int		)		->  Sequence[Node | None]:
    A       :       list[Any]							=						[]

    def populate_output(UpperCamelCase__    : Node | None    ,       UpperCamelCase__    : int		) -> None:
        if not root:
            return
        if level == 1:
            output.append(root.data		)
        elif level > 1:
            populate_output(root.left    ,       level - 1		)
            populate_output(root.right    ,       level - 1		)

    populate_output(UpperCamelCase__    ,       UpperCamelCase__		)
    return output
def 							_lowerCamelCase(  UpperCamelCase__    : Node | None    ,       UpperCamelCase__    : int		)		->  Sequence[Node | None]:
    A       :       list[Any]							=						[]

    def populate_output(UpperCamelCase__    : Node | None    ,       UpperCamelCase__    : int		) -> None:
        if root is None:
            return
        if level == 1:
            output.append(root.data		)
        elif level > 1:
            populate_output(root.right    ,       level - 1		)
            populate_output(root.left    ,       level - 1		)

    populate_output(UpperCamelCase__    ,       UpperCamelCase__		)
    return output
def 							_lowerCamelCase(  UpperCamelCase__    : Node | None		)		->  Sequence[Node | None] | list[Any]:
    if root is None:
        return []

    A       :       list[Sequence[Node | None]]							=						[]

    A       :       Any							=						0
    A       :       Dict							=						height(UpperCamelCase__		)

    for h in range(1    ,       height_tree + 1		):
        if not flag:
            output.append(get_nodes_from_left_to_right(UpperCamelCase__    ,       UpperCamelCase__		)		)
            A       :       Optional[Any]							=						1
        else:
            output.append(get_nodes_from_right_to_left(UpperCamelCase__    ,       UpperCamelCase__		)		)
            A       :       Optional[Any]							=						0

    return output
def 							_lowerCamelCase(  )		->  None:  # Main function for testing.
    A       :       Tuple							=						make_tree()
    print(F'''In-order Traversal: {inorder(UpperCamelCase__		)}'''		)
    print(F'''Pre-order Traversal: {preorder(UpperCamelCase__		)}'''		)
    print(F'''Post-order Traversal: {postorder(UpperCamelCase__		)}'''    ,       '''\n'''		)

    print(F'''Height of Tree: {height(UpperCamelCase__		)}'''    ,       '''\n'''		)

    print('''Complete Level Order Traversal: '''		)
    print(level_order(UpperCamelCase__		)    ,       '''\n'''		)

    print('''Level-wise order Traversal: '''		)

    for level in range(1    ,       height(UpperCamelCase__		) + 1		):
        print(F'''Level {level}:'''    ,       get_nodes_from_left_to_right(UpperCamelCase__    ,       level=UpperCamelCase__		)		)

    print('''\nZigZag order Traversal: '''		)
    print(zigzag(UpperCamelCase__		)		)


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     main()







'''simple docstring'''






from typing import TYPE_CHECKING

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


snake_case_     =	{
    """configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
    """tokenization_biogpt""": ["""BioGptTokenizer"""],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case_     =	[
         """BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """BioGptForCausalLM""",
         """BioGptForTokenClassification""",
         """BioGptForSequenceClassification""",
         """BioGptModel""",
         """BioGptPreTrainedModel""",
     ]


if TYPE_CHECKING:
     from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
     from .tokenization_biogpt import BioGptTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_biogpt import (
              BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
              BioGptForCausalLM,
              BioGptForSequenceClassification,
              BioGptForTokenClassification,
              BioGptModel,
              BioGptPreTrainedModel,
          )


else:
     import sys

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