



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

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


if TYPE_CHECKING:
							from ...onnx.config import PatchingSpec
							from ...tokenization_utils_base import PreTrainedTokenizerBase


lowercase_						=       logging.get_logger(__name__)

lowercase_						=       {
    """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/config.json""",
    """allenai/longformer-large-4096""": """https://huggingface.co/allenai/longformer-large-4096/resolve/main/config.json""",
    """allenai/longformer-large-4096-finetuned-triviaqa""": (
        """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/config.json"""
    ),
    """allenai/longformer-base-4096-extra.pos.embd.only""": (
        """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/config.json"""
    ),
    """allenai/longformer-large-4096-extra.pos.embd.only""": (
        """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/config.json"""
    ),
}
class 			_snake_case     (   lowercase__):
				UpperCamelCase__			:   Optional[Any]       						="""longformer"""




				def __init__(  self   :  Dict,   __lowercase   :  Union[List[int], int] = 512,   __lowercase   :  int = 2,   __lowercase   :  int = 1,   __lowercase   :  int = 0,   __lowercase   :  int = 2,   __lowercase   :  int = 3_0522,   __lowercase   :  int = 768,   __lowercase   :  int = 12,   __lowercase   :  int = 12,   __lowercase   :  int = 3072,   __lowercase   :  str = "gelu",   __lowercase   :  float = 0.1,   __lowercase   :  float = 0.1,   __lowercase   :  int = 512,   __lowercase   :  int = 2,   __lowercase   :  float = 0.02,   __lowercase   :  float = 1e-1_2,   __lowercase   :  bool = False,   **__lowercase   :  Tuple,   ):
							super().__init__(pad_token_id=__lowercase,   **__lowercase  )

							lowercase__   					=			attention_window
							lowercase__   					=			sep_token_id
							lowercase__   					=			bos_token_id
							lowercase__   					=			eos_token_id
							lowercase__   					=			vocab_size
							lowercase__   					=			hidden_size
							lowercase__   					=			num_hidden_layers
							lowercase__   					=			num_attention_heads
							lowercase__   					=			hidden_act
							lowercase__   					=			intermediate_size
							lowercase__   					=			hidden_dropout_prob
							lowercase__   					=			attention_probs_dropout_prob
							lowercase__   					=			max_position_embeddings
							lowercase__   					=			type_vocab_size
							lowercase__   					=			initializer_range
							lowercase__   					=			layer_norm_eps
							lowercase__   					=			onnx_export
class 			_snake_case     (   lowercase__):




				def __init__(  self   :  Any,   __lowercase   :  "PretrainedConfig",   __lowercase   :  str = "default",   __lowercase   :  "List[PatchingSpec]" = None  ):
							super().__init__(__lowercase,   __lowercase,   __lowercase  )
							lowercase__   					=			True




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




				@property
				def 							A__ (  self   :  Tuple  ):
							lowercase__   					=			super().outputs
							if self.task == "default":
										lowercase__   					=			{0: "batch"}
							return outputs




				@property
				def 							A__ (  self   :  List[Any]  ):
							return 1e-4




				@property
				def 							A__ (  self   :  Optional[int]  ):
							# needs to be >= 14 to support tril operator
							return max(super().default_onnx_opset,   14  )




				def 							A__ (  self   :  str,   __lowercase   :  "PreTrainedTokenizerBase",   __lowercase   :  int = -1,   __lowercase   :  int = -1,   __lowercase   :  bool = False,   __lowercase   :  Optional[TensorType] = None,   ):
							lowercase__   					=			super().generate_dummy_inputs(
							    preprocessor=__lowercase,   batch_size=__lowercase,   seq_length=__lowercase,   is_pair=__lowercase,   framework=__lowercase  )
							import torch

							# for some reason, replacing this code by inputs["global_attention_mask"] = torch.randint(2, inputs["input_ids"].shape, dtype=torch.int64)
							# makes the export fail randomly
							lowercase__   					=			torch.zeros_like(inputs["input_ids"]  )
							# make every second token global
							lowercase__   					=			1

							return 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)




