

from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_        =      logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_        =      {
    'facebook/deit-base-distilled-patch16-224': (
        'https://huggingface.co/facebook/deit-base-patch16-224/resolve/main/config.json'
    ),
    # See all DeiT models at https://huggingface.co/models?filter=deit
}

class 				a  (	UpperCAmelCase				):
						_lowercase    						=			"deit"


						def __init__(       self						,					A_=768						,					A_=12						,					A_=12						,					A_=3072						,					A_="gelu"						,					A_=0.0						,					A_=0.0						,					A_=0.02						,					A_=1e-12						,					A_=224						,					A_=16						,					A_=3						,					A_=True						,					A_=16						,					**A_						,					):







										'''simple docstring'''


										super().__init__(**A_	)

										_UpperCAmelCase       :		str 		=    hidden_size
										_UpperCAmelCase       :		List[str] 		=    num_hidden_layers
										_UpperCAmelCase       :		Optional[int] 		=    num_attention_heads
										_UpperCAmelCase       :		int 		=    intermediate_size
										_UpperCAmelCase       :		Optional[int] 		=    hidden_act
										_UpperCAmelCase       :		int 		=    hidden_dropout_prob
										_UpperCAmelCase       :		Dict 		=    attention_probs_dropout_prob
										_UpperCAmelCase       :		Tuple 		=    initializer_range
										_UpperCAmelCase       :		Union[str, Any] 		=    layer_norm_eps
										_UpperCAmelCase       :		List[str] 		=    image_size
										_UpperCAmelCase       :		Optional[Any] 		=    patch_size
										_UpperCAmelCase       :		str 		=    num_channels
										_UpperCAmelCase       :		int 		=    qkv_bias
										_UpperCAmelCase       :		str 		=    encoder_stride







class 				a  (	UpperCAmelCase				):
						_lowercase    						=			version.parse("1.11"				)


						@property
						def        _UpperCAmelCase				(       self	):







										'''simple docstring'''


										return OrderedDict(
										    [
										        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
										    ]	)





						@property
						def        _UpperCAmelCase				(       self	):







										'''simple docstring'''


										return 1e-4





import fire

from utils import calculate_rouge, save_json

def 							__SCREAMING_SNAKE_CASE							(				lowerCAmelCase:  int  ,      lowerCAmelCase:  Tuple  ,      lowerCAmelCase:  Any=None  ,      **lowerCAmelCase:  Any )   ->       Dict:
				_UpperCAmelCase       :		Optional[Any] 		=    [x.strip() for x in open(lowerCAmelCase ).readlines()]
				_UpperCAmelCase       :		str 		=    [x.strip() for x in open(lowerCAmelCase ).readlines()][: len(lowerCAmelCase )]
				_UpperCAmelCase       :		str 		=    calculate_rouge(lowerCAmelCase  ,      lowerCAmelCase  ,      **lowerCAmelCase )
				if save_path is not None:
								save_json(lowerCAmelCase  ,      lowerCAmelCase  ,      indent=lowerCAmelCase )
				return metrics  # these print nicely


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


