

from typing import TYPE_CHECKING

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


_lowerCAmelCase  :      Any			 ={"""configuration_gpt_neox""": ["""GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXConfig"""]}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowerCAmelCase  :      Optional[int]			 =["""GPTNeoXTokenizerFast"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_lowerCAmelCase  :      Tuple			 =[
					    """GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """GPTNeoXForCausalLM""",
					    """GPTNeoXForQuestionAnswering""",
					    """GPTNeoXForSequenceClassification""",
					    """GPTNeoXForTokenClassification""",
					    """GPTNeoXLayer""",
					    """GPTNeoXModel""",
					    """GPTNeoXPreTrainedModel""",
					]


if TYPE_CHECKING:
					from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_gpt_neox import (
										    GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GPTNeoXForCausalLM,
										    GPTNeoXForQuestionAnswering,
										    GPTNeoXForSequenceClassification,
										    GPTNeoXForTokenClassification,
										    GPTNeoXLayer,
										    GPTNeoXModel,
										    GPTNeoXPreTrainedModel,
										)


else:
					import sys

					_lowerCAmelCase  :      Optional[Any]			 =_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


import fire

from utils import calculate_rouge, save_json



def 			_A	(      SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE	,SCREAMING_SNAKE_CASE=None	,**SCREAMING_SNAKE_CASE      ):
	UpperCAmelCase__:	Tuple									= [x.strip() for x in open(SCREAMING_SNAKE_CASE      ).readlines()]
	UpperCAmelCase__:	Dict									= [x.strip() for x in open(SCREAMING_SNAKE_CASE      ).readlines()][: len(SCREAMING_SNAKE_CASE      )]
	UpperCAmelCase__:	Any									= 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)