code: 
  
  
  '''simple docstring'''
  
  
  
  from __future__ import annotations
  
  from collections import defaultdict
  from dataclasses import dataclass
  
  
  
  
  
  @dataclass
  class      UpperCAmelCase_						:
  
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
      lowerCamelCase						:      int
      lowerCamelCase						:      TreeNode | None							  =    None
      lowerCamelCase						:      TreeNode | None							  =    None
  
  
  
  
  
  
  
  def     UpperCAmelCase__      (			)  ->	TreeNode:
       return TreeNode(3   ,					TreeNode(9							)   ,					TreeNode(20   ,					TreeNode(15							)   ,					TreeNode(7							)							)							)
  
  
  
  def     UpperCAmelCase__      (			UpperCAmelCase_					:       TreeNode							)  ->	list[int]:
  
       def depth_first_search(
           UpperCAmelCase_					:       TreeNode | None   ,					UpperCAmelCase_					:       int   ,					UpperCAmelCase_					:       list[int]							) -> None:
            if not root:
                 return
  
            if depth == len(UpperCAmelCase_							):
                 right_view.append(root.val							)
  
            depth_first_search(root.right   ,					depth + 1   ,					UpperCAmelCase_							)
            depth_first_search(root.left   ,					depth + 1   ,					UpperCAmelCase_							)
  
       __lowerCamelCase     :			list              =	[]
       if not root:
            return right_view
  
       depth_first_search(UpperCAmelCase_   ,					0   ,					UpperCAmelCase_							)
       return right_view
  
  
  
  def     UpperCAmelCase__      (			UpperCAmelCase_					:       TreeNode							)  ->	list[int]:
  
       def depth_first_search(
           UpperCAmelCase_					:       TreeNode | None   ,					UpperCAmelCase_					:       int   ,					UpperCAmelCase_					:       list[int]							) -> None:
            if not root:
                 return
  
            if depth == len(UpperCAmelCase_							):
                 left_view.append(root.val							)
  
            depth_first_search(root.left   ,					depth + 1   ,					UpperCAmelCase_							)
            depth_first_search(root.right   ,					depth + 1   ,					UpperCAmelCase_							)
  
       __lowerCamelCase     :			list              =	[]
       if not root:
            return left_view
  
       depth_first_search(UpperCAmelCase_   ,					0   ,					UpperCAmelCase_							)
       return left_view
  
  
  
  def     UpperCAmelCase__      (			UpperCAmelCase_					:       TreeNode							)  ->	list[int]:
  
       def breadth_first_search(UpperCAmelCase_					:       TreeNode   ,					UpperCAmelCase_					:       list[int]							) -> None:
            __lowerCamelCase     :			List[str]              =	[(root, 0)]
            __lowerCamelCase     :			Tuple              =	defaultdict(UpperCAmelCase_							)
  
            while queue:
                 __lowerCamelCase     :			str              =	queue.pop(0							)
                 __lowerCamelCase       , __lowerCamelCase     :			int              =	first
  
                 lookup[hd].append(node.val							)
  
                 if node.left:
                      queue.append((node.left, hd - 1)							)
                 if node.right:
                      queue.append((node.right, hd + 1)							)
  
            for pair in sorted(lookup.items()   ,					key=lambda UpperCAmelCase_							: each[0]							):
                 top_view.append(pair[1][0]							)
  
       __lowerCamelCase     :			list              =	[]
       if not root:
            return top_view
  
       breadth_first_search(UpperCAmelCase_   ,					UpperCAmelCase_							)
       return top_view
  
  
  
  def     UpperCAmelCase__      (			UpperCAmelCase_					:       TreeNode							)  ->	list[int]:
       from collections import defaultdict
  
       def breadth_first_search(UpperCAmelCase_					:       TreeNode   ,					UpperCAmelCase_					:       list[int]							) -> None:
            __lowerCamelCase     :			Dict              =	[(root, 0)]
            __lowerCamelCase     :			int              =	defaultdict(UpperCAmelCase_							)
  
            while queue:
                 __lowerCamelCase     :			Optional[int]              =	queue.pop(0							)
                 __lowerCamelCase       , __lowerCamelCase     :			Union[str, Any]              =	first
                 lookup[hd].append(node.val							)
  
                 if node.left:
                      queue.append((node.left, hd - 1)							)
                 if node.right:
                      queue.append((node.right, hd + 1)							)
  
            for pair in sorted(lookup.items()   ,					key=lambda UpperCAmelCase_							: each[0]							):
                 bottom_view.append(pair[1][-1]							)
  
       __lowerCamelCase     :			list              =	[]
       if not root:
            return bottom_view
  
       breadth_first_search(UpperCAmelCase_   ,					UpperCAmelCase_							)
       return bottom_view
  
  
  if __name__ == "__main__":
        import doctest
  
        doctest.testmod()
  
  
  
  
  
  
  
style_context: 
  
  
  '''simple docstring'''
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available
  
  
  A__	:      Optional[Any]				=						{
      """configuration_xlm_prophetnet""": ["""XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMProphetNetConfig"""],
  }
  
  try:
        if not is_sentencepiece_available():
              raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
        pass
  else:
        A__	:      List[Any]				=						["""XLMProphetNetTokenizer"""]
  
  try:
        if not is_torch_available():
              raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
        pass
  else:
        A__	:      Optional[Any]				=						[
            """XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
            """XLMProphetNetDecoder""",
            """XLMProphetNetEncoder""",
            """XLMProphetNetForCausalLM""",
            """XLMProphetNetForConditionalGeneration""",
            """XLMProphetNetModel""",
            """XLMProphetNetPreTrainedModel""",
        ]
  
  
  if TYPE_CHECKING:
        from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig
  
        try:
              if not is_sentencepiece_available():
                    raise OptionalDependencyNotAvailable()
        except OptionalDependencyNotAvailable:
              pass
        else:
              from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer
  
        try:
              if not is_torch_available():
                    raise OptionalDependencyNotAvailable()
        except OptionalDependencyNotAvailable:
              pass
        else:
              from .modeling_xlm_prophetnet import (
                  XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
                  XLMProphetNetDecoder,
                  XLMProphetNetEncoder,
                  XLMProphetNetForCausalLM,
                  XLMProphetNetForConditionalGeneration,
                  XLMProphetNetModel,
                  XLMProphetNetPreTrainedModel,
              )
  
  else:
        import sys
  
        A__	:      List[str]				=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  
  
  
  
  
  
  