


'''simple docstring'''


from __future__ import annotations

lowerCamelCase__    	=     [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
lowerCamelCase__    	=     [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]






def  __lowerCAmelCase (__lowerCAmelCase   ):
		_UpperCAmelCase		:       Union[str, Any]								=      []
		_UpperCAmelCase		:       int								=      len(__lowerCAmelCase   )

		for i in range(__lowerCAmelCase   ):
				_UpperCAmelCase		:       float								=      -1
				for j in range(i + 1      , __lowerCAmelCase   ):
						if arr[i] < arr[j]:
								_UpperCAmelCase		:       List[str]								=      arr[j]
								break
				result.append(__lowerCAmelCase   )
		return result






def  __lowerCAmelCase (__lowerCAmelCase   ):
		_UpperCAmelCase		:       List[Any]								=      []
		for i, outer in enumerate(__lowerCAmelCase   ):
				_UpperCAmelCase		:       float								=      -1
				for inner in arr[i + 1 :]:
						if outer < inner:
								_UpperCAmelCase		:       Optional[Any]								=      inner
								break
				result.append(__lowerCAmelCase   )
		return result






def  __lowerCAmelCase (__lowerCAmelCase   ):
		_UpperCAmelCase		:       Dict								=      len(__lowerCAmelCase   )
		_UpperCAmelCase		:       list[float]								=      []
		_UpperCAmelCase		:       list[float]								=      [-1] * arr_size

		for index in reversed(range(__lowerCAmelCase   )   ):
				if stack:
						while stack[-1] <= arr[index]:
								stack.pop()
								if not stack:
										break
				if stack:
						_UpperCAmelCase		:       Dict								=      stack[-1]
				stack.append(arr[index]   )
		return result


if __name__ == "__main__":
						from doctest import testmod
						from timeit import timeit

						testmod()
						print(next_greatest_element_slow(arr))
						print(next_greatest_element_fast(arr))
						print(next_greatest_element(arr))

						lowerCamelCase__    	=     (
						    'from __main__ import arr, next_greatest_element_slow, '
						    'next_greatest_element_fast, next_greatest_element'
						)
						print(
						    'next_greatest_element_slow():',
						    timeit('next_greatest_element_slow(arr)', setup=setup),
						)
						print(
						    'next_greatest_element_fast():',
						    timeit('next_greatest_element_fast(arr)', setup=setup),
						)
						print(
						    '     next_greatest_element():',
						    timeit('next_greatest_element(arr)', setup=setup),
						)







'''simple docstring'''


# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCamelCase__    	=     {'configuration_mra': ['MRA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MraConfig']}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__    	=     [
						    'MRA_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'MraForMaskedLM',
						    'MraForMultipleChoice',
						    'MraForQuestionAnswering',
						    'MraForSequenceClassification',
						    'MraForTokenClassification',
						    'MraLayer',
						    'MraModel',
						    'MraPreTrainedModel',
						]


if TYPE_CHECKING:
						from .configuration_mra import MRA_PRETRAINED_CONFIG_ARCHIVE_MAP, MraConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_mra import (
												    MRA_PRETRAINED_MODEL_ARCHIVE_LIST,
												    MraForMaskedLM,
												    MraForMultipleChoice,
												    MraForQuestionAnswering,
												    MraForSequenceClassification,
												    MraForTokenClassification,
												    MraLayer,
												    MraModel,
												    MraPreTrainedModel,
												)
else:
						import sys

						lowerCamelCase__    	=     _LazyModule(__name__, globals()['__file__'], _import_structure)



