




"""simple docstring"""




from typing import TYPE_CHECKING

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


lowerCAmelCase							:    Optional[Any]  							=							{
    """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:
					lowerCAmelCase							:    Optional[int]  							=							["""LayoutLMv2TokenizerFast"""]

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase							:    int  							=							["""LayoutLMv2FeatureExtractor"""]
					lowerCAmelCase							:    Optional[Any]  							=							["""LayoutLMv2ImageProcessor"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase							:    Dict  							=							[
					    """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

					lowerCAmelCase							:    str  							=							_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)









"""simple docstring"""




from collections.abc import Sequence



def 					a__				(       snake_case__ ,				snake_case__ = False       )		->      float:
			if not arr:
						return 0

			lowerCamelCase       =      0 if allow_empty_subarrays else float("""-inf"""       )
			lowerCamelCase       =      0.0
			for num in arr:
						lowerCamelCase       =      max(0 if allow_empty_subarrays else num ,				curr_sum + num       )
						lowerCamelCase       =      max(snake_case__ ,				snake_case__       )

			return max_sum


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

					testmod()

					lowerCAmelCase							:    Optional[int]  							=							[-2, 1, -3, 4, -1, 2, 1, -5, 4]
					print(F"""{max_subarray_sum(nums) = }""")



