






'''simple docstring'''




import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig


__lowerCamelCase   :					Optional[int]   							=					logging.get_logger(__name__)

__lowerCamelCase   :					int   							=					{
    '''Intel/dpt-large''': '''https://huggingface.co/Intel/dpt-large/resolve/main/config.json''',
    # See all DPT models at https://huggingface.co/models?filter=dpt
}







class    A_	(_A							):
							"""simple docstring"""




							a__   		=	'''dpt'''

							def __init__(		self			:Optional[int]       ,							lowerCAmelCase__			:List[Any]=768       ,							lowerCAmelCase__			:Tuple=12       ,							lowerCAmelCase__			:List[str]=12       ,							lowerCAmelCase__			:Optional[Any]=3_072       ,							lowerCAmelCase__			:List[str]="gelu"       ,							lowerCAmelCase__			:Tuple=0.0       ,							lowerCAmelCase__			:Optional[int]=0.0       ,							lowerCAmelCase__			:Optional[int]=0.0_2       ,							lowerCAmelCase__			:Optional[int]=1E-1_2       ,							lowerCAmelCase__			:List[Any]=384       ,							lowerCAmelCase__			:Optional[int]=16       ,							lowerCAmelCase__			:Optional[int]=3       ,							lowerCAmelCase__			:Tuple=False       ,							lowerCAmelCase__			:int=True       ,							lowerCAmelCase__			:Tuple=[2, 5, 8, 11]       ,							lowerCAmelCase__			:Tuple="project"       ,							lowerCAmelCase__			:List[str]=[4, 2, 1, 0.5]       ,							lowerCAmelCase__			:Tuple=[96, 192, 384, 768]       ,							lowerCAmelCase__			:Optional[Any]=256       ,							lowerCAmelCase__			:str=-1       ,							lowerCAmelCase__			:Dict=False       ,							lowerCAmelCase__			:List[str]=True       ,							lowerCAmelCase__			:Union[str, Any]=0.4       ,							lowerCAmelCase__			:Any=255       ,							lowerCAmelCase__			:Union[str, Any]=0.1       ,							lowerCAmelCase__			:Optional[Any]=[1, 1_024, 24, 24]       ,							lowerCAmelCase__			:Optional[int]=[0, 1]       ,							lowerCAmelCase__			:List[str]=None       ,							**lowerCAmelCase__			:Dict       ,							)				->  Optional[int]:


										'''simple docstring'''




										super().__init__(**__lowerCamelCase				)

										snake_case_				:					str   =       hidden_size
										snake_case_				:					int   =       is_hybrid

										if self.is_hybrid:
													if backbone_config is None:
																logger.info("Initializing the config with a `BiT` backbone."				)
																snake_case_				:					str   =       {
																    "global_padding": "same",
																    "layer_type": "bottleneck",
																    "depths": [3, 4, 9],
																    "out_features": ["stage1", "stage2", "stage3"],
																    "embedding_dynamic_padding": True,
																}
																snake_case_				:					Optional[int]   =       BitConfig(**__lowerCamelCase				)
													elif isinstance(__lowerCamelCase       ,							__lowerCamelCase				):
																logger.info("Initializing the config with a `BiT` backbone."				)
																snake_case_				:					Union[str, Any]   =       BitConfig(**__lowerCamelCase				)
													elif isinstance(__lowerCamelCase       ,							__lowerCamelCase				):
																snake_case_				:					Union[str, Any]   =       backbone_config
													else:
																raise ValueError(
																    F'''backbone_config must be a dictionary or a `PretrainedConfig`, got {backbone_config.__class__}.'''				)

													snake_case_				:					int   =       backbone_featmap_shape
													snake_case_				:					Tuple   =       neck_ignore_stages

													if readout_type != "project":
																raise ValueError("Readout type must be 'project' when using `DPT-hybrid` mode."				)
										else:
													snake_case_				:					int   =       None
													snake_case_				:					List[str]   =       None
													snake_case_				:					Any   =       []

										snake_case_				:					int   =       num_hidden_layers
										snake_case_				:					str   =       num_attention_heads
										snake_case_				:					Union[str, Any]   =       intermediate_size
										snake_case_				:					List[Any]   =       hidden_act
										snake_case_				:					str   =       hidden_dropout_prob
										snake_case_				:					Dict   =       attention_probs_dropout_prob
										snake_case_				:					str   =       initializer_range
										snake_case_				:					List[Any]   =       layer_norm_eps
										snake_case_				:					Union[str, Any]   =       image_size
										snake_case_				:					Tuple   =       patch_size
										snake_case_				:					str   =       num_channels
										snake_case_				:					Dict   =       qkv_bias
										snake_case_				:					Union[str, Any]   =       backbone_out_indices
										if readout_type not in ["ignore", "add", "project"]:
													raise ValueError("Readout_type must be one of ['ignore', 'add', 'project']"				)
										snake_case_				:					List[Any]   =       readout_type
										snake_case_				:					List[Any]   =       reassemble_factors
										snake_case_				:					Union[str, Any]   =       neck_hidden_sizes
										snake_case_				:					Tuple   =       fusion_hidden_size
										snake_case_				:					Union[str, Any]   =       head_in_index
										snake_case_				:					Dict   =       use_batch_norm_in_fusion_residual
										# auxiliary head attributes (semantic segmentation)
										snake_case_				:					List[Any]   =       use_auxiliary_head
										snake_case_				:					Optional[Any]   =       auxiliary_loss_weight
										snake_case_				:					Optional[Any]   =       semantic_loss_ignore_index
										snake_case_				:					Any   =       semantic_classifier_dropout






							def 							_A	(		self			:List[str]				)				->  Optional[int]:


										'''simple docstring'''




										snake_case_				:					Optional[int]   =       copy.deepcopy(self.__dict__				)

										if output["backbone_config"] is not None:
													snake_case_				:					Tuple   =       self.backbone_config.to_dict()

										snake_case_				:					Tuple   =       self.__class__.model_type
										return output












'''simple docstring'''




import fire

from utils import calculate_rouge, save_json

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__     ,__magic_name__=None     ,**__magic_name__						)->    Optional[Any]:



			"""simple docstring"""



			snake_case_				:					int   =       [x.strip() for x in open(__magic_name__						).readlines()]
			snake_case_				:					Optional[int]   =       [x.strip() for x in open(__magic_name__						).readlines()][: len(__magic_name__						)]
			snake_case_				:					List[Any]   =       calculate_rouge(__magic_name__     ,__magic_name__     ,**__magic_name__						)
			if save_path is not None:
						save_json(__magic_name__     ,__magic_name__     ,indent=__magic_name__						)
			return metrics  # these print nicely


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




