



from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

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


if TYPE_CHECKING:
							from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


lowercase_						=       logging.get_logger(__name__)

lowercase_						=       {
    """microsoft/deberta-v2-xlarge""": """https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/config.json""",
    """microsoft/deberta-v2-xxlarge""": """https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/config.json""",
    """microsoft/deberta-v2-xlarge-mnli""": (
        """https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/config.json"""
    ),
    """microsoft/deberta-v2-xxlarge-mnli""": (
        """https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/config.json"""
    ),
}
class 			_snake_case     (   lowercase__):
				UpperCamelCase__			:   Optional[int]       						="""deberta-v2"""




				def __init__(  self   :  List[str],   __lowercase   :  str=12_8100,   __lowercase   :  Union[str, Any]=1536,   __lowercase   :  Optional[int]=24,   __lowercase   :  Optional[int]=24,   __lowercase   :  str=6144,   __lowercase   :  Any="gelu",   __lowercase   :  Tuple=0.1,   __lowercase   :  Dict=0.1,   __lowercase   :  Optional[int]=512,   __lowercase   :  Any=0,   __lowercase   :  List[Any]=0.02,   __lowercase   :  Union[str, Any]=1e-7,   __lowercase   :  Optional[int]=False,   __lowercase   :  Any=-1,   __lowercase   :  Optional[int]=0,   __lowercase   :  int=True,   __lowercase   :  Any=None,   __lowercase   :  Optional[int]=0,   __lowercase   :  int="gelu",   **__lowercase   :  Any,   ):
							super().__init__(**__lowercase  )

							lowercase__   					=			hidden_size
							lowercase__   					=			num_hidden_layers
							lowercase__   					=			num_attention_heads
							lowercase__   					=			intermediate_size
							lowercase__   					=			hidden_act
							lowercase__   					=			hidden_dropout_prob
							lowercase__   					=			attention_probs_dropout_prob
							lowercase__   					=			max_position_embeddings
							lowercase__   					=			type_vocab_size
							lowercase__   					=			initializer_range
							lowercase__   					=			relative_attention
							lowercase__   					=			max_relative_positions
							lowercase__   					=			pad_token_id
							lowercase__   					=			position_biased_input

							# Backwards compatibility
							if type(__lowercase  ) == str:
										lowercase__   					=			[x.strip() for x in pos_att_type.lower().split("|"  )]

							lowercase__   					=			pos_att_type
							lowercase__   					=			vocab_size
							lowercase__   					=			layer_norm_eps

							lowercase__   					=			kwargs.get("pooler_hidden_size",   __lowercase  )
							lowercase__   					=			pooler_dropout
							lowercase__   					=			pooler_hidden_act
class 			_snake_case     (   lowercase__):




				@property
				def 							A__ (  self   :  int  ):
							if self.task == "multiple-choice":
										lowercase__   					=			{0: "batch", 1: "choice", 2: "sequence"}
							else:
										lowercase__   					=			{0: "batch", 1: "sequence"}
							if self._config.type_vocab_size > 0:
										return OrderedDict(
										    [("input_ids", dynamic_axis), ("attention_mask", dynamic_axis), ("token_type_ids", dynamic_axis)]  )
							else:
										return OrderedDict([("input_ids", dynamic_axis), ("attention_mask", dynamic_axis)]  )




				@property
				def 							A__ (  self   :  str  ):
							return 12




				def 							A__ (  self   :  int,   __lowercase   :  Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"],   __lowercase   :  int = -1,   __lowercase   :  int = -1,   __lowercase   :  int = -1,   __lowercase   :  bool = False,   __lowercase   :  Optional["TensorType"] = None,   __lowercase   :  int = 3,   __lowercase   :  int = 40,   __lowercase   :  int = 40,   __lowercase   :  "PreTrainedTokenizerBase" = None,   ):
							lowercase__   					=			super().generate_dummy_inputs(preprocessor=__lowercase,   framework=__lowercase  )
							if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
										del dummy_inputs["token_type_ids"]
							return dummy_inputs









import fire

from utils import calculate_rouge, save_json



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_=None  ,					**SCREAMING_SNAKE_CASE_					):
			lowercase__   					=			[x.strip() for x in open(SCREAMING_SNAKE_CASE_					).readlines()]
			lowercase__   					=			[x.strip() for x in open(SCREAMING_SNAKE_CASE_					).readlines()][: len(SCREAMING_SNAKE_CASE_					)]
			lowercase__   					=			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)




