'''simple docstring'''





import fire

from utils import calculate_rouge, save_json





def 	lowerCAmelCase_				(					snake_case_       : Union[str, Any]					,    snake_case_       : int					,    snake_case_       : List[Any]=None					,    **snake_case_       : List[Any]			)    ->      Union[str, Any]:


     '''simple docstring'''




     UpperCAmelCase_           =   [x.strip() for x in open(SCREAMING_SNAKE_CASE__			).readlines()]
     UpperCAmelCase_           =   [x.strip() for x in open(SCREAMING_SNAKE_CASE__			).readlines()][: len(SCREAMING_SNAKE_CASE__			)]
     UpperCAmelCase_           =   calculate_rouge(SCREAMING_SNAKE_CASE__					,    SCREAMING_SNAKE_CASE__					,    **SCREAMING_SNAKE_CASE__			)
     if save_path is not None:
          save_json(SCREAMING_SNAKE_CASE__					,    SCREAMING_SNAKE_CASE__					,    indent=SCREAMING_SNAKE_CASE__			)
     return metrics  # these print nicely


if __name__ == "__main__":
    fire.Fire(calculate_rouge_path)







from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable


lowerCAmelCase_       	=	{'''configuration_dpt''': ['''DPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DPTConfig''']}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_       	=	['''DPTFeatureExtractor''']
					lowerCAmelCase_       	=	['''DPTImageProcessor''']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_       	=	[
					    '''DPT_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''DPTForDepthEstimation''',
					    '''DPTForSemanticSegmentation''',
					    '''DPTModel''',
					    '''DPTPreTrainedModel''',
					]


if TYPE_CHECKING:
					from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_dpt import DPTFeatureExtractor
										from .image_processing_dpt import DPTImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_dpt import (
										    DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    DPTForDepthEstimation,
										    DPTForSemanticSegmentation,
										    DPTModel,
										    DPTPreTrainedModel,
										)


else:
					import sys

					lowerCAmelCase_       	=	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)