'''simple docstring'''






from math import factorial, pi






def   __UpperCAmelCase     (    a_:			str,   a_:			Dict = 30				):

   if not isinstance(UpperCAmelCase_,   (int, float)				):
      raise ValueError("maclaurin_sin() requires either an int or float for theta"				)

   if not isinstance(UpperCAmelCase_,   UpperCAmelCase_				) or accuracy <= 0:
      raise ValueError("maclaurin_sin() requires a positive int for accuracy"				)

   _UpperCAmelCase				:      int				=  float(UpperCAmelCase_				)
   _UpperCAmelCase				:      int				=  theta // (2 * pi)
   theta -= 2 * div * pi
   return sum(
       (-1) ** r * theta ** (2 * r + 1) / factorial(2 * r + 1				) for r in range(UpperCAmelCase_				)				)






def   __UpperCAmelCase     (    a_:			Tuple,   a_:			Tuple = 30				):

   if not isinstance(UpperCAmelCase_,   (int, float)				):
      raise ValueError("maclaurin_cos() requires either an int or float for theta"				)

   if not isinstance(UpperCAmelCase_,   UpperCAmelCase_				) or accuracy <= 0:
      raise ValueError("maclaurin_cos() requires a positive int for accuracy"				)

   _UpperCAmelCase				:      Union[str, Any]				=  float(UpperCAmelCase_				)
   _UpperCAmelCase				:      List[Any]				=  theta // (2 * pi)
   theta -= 2 * div * pi
   return sum((-1) ** r * theta ** (2 * r) / factorial(2 * r				) for r in range(UpperCAmelCase_				)				)


if __name__ == "__main__":
     import doctest

     doctest.testmod()

     print(maclaurin_sin(10))
     print(maclaurin_sin(-10))
     print(maclaurin_sin(10, 15))
     print(maclaurin_sin(-10, 15))

     print(maclaurin_cos(5))
     print(maclaurin_cos(-5))
     print(maclaurin_cos(10, 15))
     print(maclaurin_cos(-10, 15))




'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


snake_case_					:      Tuple    			=    {
    'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
    'processing_layoutlmv2': ['LayoutLMv2Processor'],
    'tokenization_layoutlmv2': ['LayoutLMv2Tokenizer'],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_					:      int    			=    ['LayoutLMv2TokenizerFast']

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_					:      Union[str, Any]    			=    ['LayoutLMv2FeatureExtractor']
					snake_case_					:      str    			=    ['LayoutLMv2ImageProcessor']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_					:      Optional[int]    			=    [
					    'LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'LayoutLMv2ForQuestionAnswering',
					    'LayoutLMv2ForSequenceClassification',
					    'LayoutLMv2ForTokenClassification',
					    'LayoutLMv2Layer',
					    'LayoutLMv2Model',
					    'LayoutLMv2PreTrainedModel',
					]

if TYPE_CHECKING:
					from .configuration_layoutlmva import LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMvaConfig
					from .processing_layoutlmva import LayoutLMvaProcessor
					from .tokenization_layoutlmva import LayoutLMvaTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_layoutlmva_fast import LayoutLMvaTokenizerFast

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_layoutlmva import LayoutLMvaFeatureExtractor, LayoutLMvaImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_layoutlmva import (
										    LAYOUTLMV2_PRETRAINED_MODEL_ARCHIVE_LIST,
										    LayoutLMvaForQuestionAnswering,
										    LayoutLMvaForSequenceClassification,
										    LayoutLMvaForTokenClassification,
										    LayoutLMvaLayer,
										    LayoutLMvaModel,
										    LayoutLMvaPreTrainedModel,
										)
else:
					import sys

					snake_case_					:      int    			=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


