"""simple docstring"""






from __future__ import annotations

import math
import random
from typing import Any




class 			__lowercase     :







					'''simple docstring'''




					def __init__(  self       ):
									__a	:  list[Any]         =					[]
									__a	:  int         =					0
									__a	:  int         =					0







					def 	_lowerCamelCase						(  self       ):
									return self.head == self.tail







					def 	_lowerCamelCase						(  self		,     _UpperCAmelCase       ):
									self.data.append(_UpperCAmelCase       )
									__a	:  List[Any]         =					self.tail + 1







					def 	_lowerCamelCase						(  self       ):
									__a	:  Any         =					self.data[self.head]
									__a	:  Union[str, Any]         =					self.head + 1
									return ret







					def 	_lowerCamelCase						(  self       ):
									return self.tail - self.head







					def 	_lowerCamelCase						(  self       ):
									print(self.data       )
									print('''**************'''       )
									print(self.data[self.head : self.tail]       )






class 			__lowercase     :







					'''simple docstring'''




					def __init__(  self		,     _UpperCAmelCase       ):
									__a	:  Union[str, Any]         =					data
									__a	:  MyNode | None         =					None
									__a	:  MyNode | None         =					None
									__a	:  int         =					1







					def 	_lowerCamelCase						(  self       ):
									return self.data







					def 	_lowerCamelCase						(  self       ):
									return self.left







					def 	_lowerCamelCase						(  self       ):
									return self.right







					def 	_lowerCamelCase						(  self       ):
									return self.height







					def 	_lowerCamelCase						(  self		,     _UpperCAmelCase       ):
									__a	:  Union[str, Any]         =					data







					def 	_lowerCamelCase						(  self		,     _UpperCAmelCase       ):
									__a	:  Optional[Any]         =					node







					def 	_lowerCamelCase						(  self		,     _UpperCAmelCase       ):
									__a	:  Union[str, Any]         =					node







					def 	_lowerCamelCase						(  self		,     _UpperCAmelCase       ):
									__a	:  str         =					height






def       __A (     a_  :MyNode | None)						->						int:
				if node is None:
								return 0
				return node.get_height()

def       __A (     a_  :int				,    a_  :int)						->						int:
				if a > b:
								return a
				return b

def       __A (     a_  :MyNode)						->						MyNode:
				print('''left rotation node:'''				,    node.get_data())
				__a	:  List[str]         =					node.get_left()
				assert ret is not None
				node.set_left(ret.get_right())
				ret.set_right(a_)
				__a	:  int         =					my_max(get_height(node.get_right())				,    get_height(node.get_left())) + 1
				node.set_height(a_)
				__a	:  Optional[Any]         =					my_max(get_height(ret.get_right())				,    get_height(ret.get_left())) + 1
				ret.set_height(a_)
				return ret

def       __A (     a_  :MyNode)						->						MyNode:
				print('''right rotation node:'''				,    node.get_data())
				__a	:  Optional[Any]         =					node.get_right()
				assert ret is not None
				node.set_right(ret.get_left())
				ret.set_left(a_)
				__a	:  Any         =					my_max(get_height(node.get_right())				,    get_height(node.get_left())) + 1
				node.set_height(a_)
				__a	:  Optional[Any]         =					my_max(get_height(ret.get_right())				,    get_height(ret.get_left())) + 1
				ret.set_height(a_)
				return ret

def       __A (     a_  :MyNode)						->						MyNode:
				__a	:  Any         =					node.get_left()
				assert left_child is not None
				node.set_left(left_rotation(a_))
				return right_rotation(a_)

def       __A (     a_  :MyNode)						->						MyNode:
				__a	:  Dict         =					node.get_right()
				assert right_child is not None
				node.set_right(right_rotation(a_))
				return left_rotation(a_)

def       __A (     a_  :MyNode | None				,    a_  :Any)						->						MyNode | None:
				if node is None:
								return MyNode(a_)
				if data < node.get_data():
								node.set_left(insert_node(node.get_left()				,    a_))
								if (
								    get_height(node.get_left()) - get_height(node.get_right()) == 2
								):  # an unbalance detected
												__a	:  Optional[int]         =					node.get_left()
												assert left_child is not None
												if (
												    data < left_child.get_data()
												):  # new node is the left child of the left child
																__a	:  str         =					right_rotation(a_)
												else:
																__a	:  List[str]         =					lr_rotation(a_)
				else:
								node.set_right(insert_node(node.get_right()				,    a_))
								if get_height(node.get_right()) - get_height(node.get_left()) == 2:
												__a	:  Dict         =					node.get_right()
												assert right_child is not None
												if data < right_child.get_data():
																__a	:  Any         =					rl_rotation(a_)
												else:
																__a	:  Optional[int]         =					left_rotation(a_)
				__a	:  List[str]         =					my_max(get_height(node.get_right())				,    get_height(node.get_left())) + 1
				node.set_height(a_)
				return node

def       __A (     a_  :MyNode)						->						Any:
				while True:
								__a	:  str         =					root.get_right()
								if right_child is None:
												break
								__a	:  int         =					right_child
				return root.get_data()

def       __A (     a_  :MyNode)						->						Any:
				while True:
								__a	:  List[Any]         =					root.get_left()
								if left_child is None:
												break
								__a	:  Optional[int]         =					left_child
				return root.get_data()

def       __A (     a_  :MyNode				,    a_  :Any)						->						MyNode | None:
				__a	:  Dict         =					root.get_left()
				__a	:  Dict         =					root.get_right()
				if root.get_data() == data:
								if left_child is not None and right_child is not None:
												__a	:  Dict         =					get_left_most(a_)
												root.set_data(a_)
												root.set_right(del_node(a_				,    a_))
								elif left_child is not None:
												__a	:  List[Any]         =					left_child
								elif right_child is not None:
												__a	:  Union[str, Any]         =					right_child
								else:
												return None
				elif root.get_data() > data:
								if left_child is None:
												print('''No such data''')
												return root
								else:
												root.set_left(del_node(a_				,    a_))
				else:  # root.get_data() < data
								if right_child is None:
												return root
								else:
												root.set_right(del_node(a_				,    a_))

				if get_height(a_) - get_height(a_) == 2:
								assert right_child is not None
								if get_height(right_child.get_right()) > get_height(right_child.get_left()):
												__a	:  Tuple         =					left_rotation(a_)
								else:
												__a	:  Tuple         =					rl_rotation(a_)
				elif get_height(a_) - get_height(a_) == -2:
								assert left_child is not None
								if get_height(left_child.get_left()) > get_height(left_child.get_right()):
												__a	:  Any         =					right_rotation(a_)
								else:
												__a	:  Tuple         =					lr_rotation(a_)
				__a	:  int         =					my_max(get_height(root.get_right())				,    get_height(root.get_left())) + 1
				root.set_height(a_)
				return root




class 			__lowercase     :







					'''simple docstring'''




					def __init__(  self       ):
									__a	:  MyNode | None         =					None







					def 	_lowerCamelCase						(  self       ):
									return get_height(self.root       )







					def 	_lowerCamelCase						(  self		,     _UpperCAmelCase       ):
									print('''insert:''' + str(_UpperCAmelCase       )       )
									__a	:  List[str]         =					insert_node(self.root		,     _UpperCAmelCase       )







					def 	_lowerCamelCase						(  self		,     _UpperCAmelCase       ):
									print('''delete:''' + str(_UpperCAmelCase       )       )
									if self.root is None:
													print('''Tree is empty!'''       )
													return
									__a	:  Optional[Any]         =					del_node(self.root		,     _UpperCAmelCase       )







					def __str__(  self		,     ):  # a level traversale, gives a more intuitive look on the tree
									__a	:  Optional[int]         =					''''''
									__a	:  str         =					MyQueue()
									q.push(self.root       )
									__a	:  Union[str, Any]         =					self.get_height()
									if layer == 0:
													return output
									__a	:  Dict         =					0
									while not q.is_empty():
													__a	:  Tuple         =					q.pop()
													__a	:  Dict         =					''' ''' * int(math.pow(2		,     layer - 1       )       )
													output += space
													if node is None:
																	output += "*"
																	q.push(_UpperCAmelCase       )
																	q.push(_UpperCAmelCase       )
													else:
																	output += str(node.get_data()       )
																	q.push(node.get_left()       )
																	q.push(node.get_right()       )
													output += space
													__a	:  Optional[Any]         =					cnt + 1
													for i in range(100       ):
																	if cnt == math.pow(2		,     _UpperCAmelCase       ) - 1:
																					__a	:  Tuple         =					layer - 1
																					if layer == 0:
																									output += "\n*************************************"
																									return output
																					output += "\n"
																					break
									output += "\n*************************************"
									return output






def       __A (     )						->						None:
				import doctest

				doctest.testmod()


if __name__ == "__main__":
		_test()
		A	     =					AVLtree()
		A	     =					list(range(10))
		random.shuffle(lst)
		for i in lst:
				t.insert(i)
				print(str(t))
		random.shuffle(lst)
		for i in lst:
				t.del_node(i)
				print(str(t))






"""simple docstring"""






import argparse
import os

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
A	     =					'''src/transformers'''
A	     =					'''docs/source/en/tasks'''

def       __A (     a_  :List[Any]				,    a_  :List[Any]				,    a_  :List[str])						->						List[str]:
				with open(a_				,    '''r'''				,    encoding='''utf-8'''				,    newline='''\n''') as f:
								__a	:  List[str]         =					f.readlines()
				# Find the start prompt.
				__a	:  Optional[Any]         =					0
				while not lines[start_index].startswith(a_):
								start_index += 1
				start_index += 1

				__a	:  int         =					start_index
				while not lines[end_index].startswith(a_):
								end_index += 1
				end_index -= 1

				while len(lines[start_index]) <= 1:
								start_index += 1
				while len(lines[end_index]) <= 1:
								end_index -= 1
				end_index += 1
				return "".join(lines[start_index:end_index]), start_index, end_index, lines


# This is to make sure the transformers module imported is the one in the repo.
A	     =					direct_transformers_import(TRANSFORMERS_PATH)

A	     =					{
    '''asr.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_CTC_MAPPING_NAMES,
    '''audio_classification.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES,
    '''language_modeling.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES,
    '''image_classification.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES,
    '''masked_language_modeling.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_MASKED_LM_MAPPING_NAMES,
    '''multiple_choice.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_MULTIPLE_CHOICE_MAPPING_NAMES,
    '''object_detection.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES,
    '''question_answering.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES,
    '''semantic_segmentation.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES,
    '''sequence_classification.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES,
    '''summarization.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,
    '''token_classification.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES,
    '''translation.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,
    '''video_classification.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING_NAMES,
    '''document_question_answering.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES,
    '''monocular_depth_estimation.md''': transformers_module.models.auto.modeling_auto.MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES,
}

# This list contains model types used in some task guides that are not in `CONFIG_MAPPING_NAMES` (therefore not in any
# `MODEL_MAPPING_NAMES` or any `MODEL_FOR_XXX_MAPPING_NAMES`).
A	     =					{
    '''summarization.md''': ('''nllb''',),
    '''translation.md''': ('''nllb''',),
}

def       __A (     a_  :Optional[Any])						->						Any:
				__a	:  List[Any]         =					TASK_GUIDE_TO_MODELS[task_guide]
				__a	:  List[Any]         =					SPECIAL_TASK_GUIDE_TO_MODEL_TYPES.get(a_				,    set())
				__a	:  Any         =					{
				    code: name
				    for code, name in transformers_module.MODEL_NAMES_MAPPING.items()
				    if (code in model_maping_names or code in special_model_types)
				}
				return ", ".join([F"""[{name}](../model_doc/{code})""" for code, name in model_names.items()]) + "\n"

def       __A (     a_  :Optional[int]				,    a_  :Dict=False)						->						Any:
				__a    ,  __a    ,  __a    ,  __a	:  Any         =					_find_text_in_file(
				    filename=os.path.join(a_				,    a_)				,    start_prompt='''<!--This tip is automatically generated by `make fix-copies`, do not fill manually!-->'''				,    end_prompt='''<!--End of the generated tip-->'''				,    )

				__a	:  Optional[Any]         =					get_model_list_for_task(a_)

				if current_list != new_list:
								if overwrite:
												with open(os.path.join(a_				,    a_)				,    '''w'''				,    encoding='''utf-8'''				,    newline='''\n''') as f:
																f.writelines(lines[:start_index] + [new_list] + lines[end_index:])
								else:
												raise ValueError(
												    F"""The list of models that can be used in the {task_guide} guide needs an update. Run `make fix-copies`"""
												    ''' to fix this.''')


if __name__ == "__main__":
		A	     =					argparse.ArgumentParser()
		parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
		A	     =					parser.parse_args()

		for task_guide in TASK_GUIDE_TO_MODELS.keys():
				check_model_list_for_task(task_guide, args.fix_and_overwrite)