


import importlib
import inspect
from functools import wraps
from typing import TYPE_CHECKING, Optional, Union

from .download.streaming_download_manager import (
    xbasename,
    xdirname,
    xet_parse,
    xexists,
    xgetsize,
    xglob,
    xgzip_open,
    xisdir,
    xisfile,
    xjoin,
    xlistdir,
    xnumpy_load,
    xopen,
    xpandas_read_csv,
    xpandas_read_excel,
    xPath,
    xrelpath,
    xsio_loadmat,
    xsplit,
    xsplitext,
    xwalk,
    xxml_dom_minidom_parse,
)
from .utils.logging import get_logger
from .utils.patching import patch_submodule
from .utils.py_utils import get_imports


__lowerCamelCase   	=  get_logger(__name__)


if TYPE_CHECKING:
       from .builder import DatasetBuilder



def 			_a      (    __UpperCamelCase	,	__UpperCamelCase = None			):
     a_     :  int				      =     importlib.import_module(__UpperCamelCase			)

     # TODO(QL): always update the module to add subsequent new authentication
     if hasattr(__UpperCamelCase	,	"""_patched_for_streaming"""			) and module._patched_for_streaming:
          return

     def wrap_auth(__UpperCamelCase			):
          @wraps(__UpperCamelCase			)
          def wrapper(*__UpperCamelCase	,	**__UpperCamelCase			):
               return function(*__UpperCamelCase	,	use_auth_token=__UpperCamelCase	,	**__UpperCamelCase			)

          a_     :  str				      =     """wrap_auth"""
          return wrapper

     # open files in a streaming fashion
     patch_submodule(__UpperCamelCase	,	"""open"""	,	wrap_auth(__UpperCamelCase			)			).start()
     patch_submodule(__UpperCamelCase	,	"""os.listdir"""	,	wrap_auth(__UpperCamelCase			)			).start()
     patch_submodule(__UpperCamelCase	,	"""os.walk"""	,	wrap_auth(__UpperCamelCase			)			).start()
     patch_submodule(__UpperCamelCase	,	"""glob.glob"""	,	wrap_auth(__UpperCamelCase			)			).start()
     # allow to navigate in remote zip files
     patch_submodule(__UpperCamelCase	,	"""os.path.join"""	,	__UpperCamelCase			).start()
     patch_submodule(__UpperCamelCase	,	"""os.path.dirname"""	,	__UpperCamelCase			).start()
     patch_submodule(__UpperCamelCase	,	"""os.path.basename"""	,	__UpperCamelCase			).start()
     patch_submodule(__UpperCamelCase	,	"""os.path.relpath"""	,	__UpperCamelCase			).start()
     patch_submodule(__UpperCamelCase	,	"""os.path.split"""	,	__UpperCamelCase			).start()
     patch_submodule(__UpperCamelCase	,	"""os.path.splitext"""	,	__UpperCamelCase			).start()
     # allow checks on paths
     patch_submodule(__UpperCamelCase	,	"""os.path.exists"""	,	wrap_auth(__UpperCamelCase			)			).start()
     patch_submodule(__UpperCamelCase	,	"""os.path.isdir"""	,	wrap_auth(__UpperCamelCase			)			).start()
     patch_submodule(__UpperCamelCase	,	"""os.path.isfile"""	,	wrap_auth(__UpperCamelCase			)			).start()
     patch_submodule(__UpperCamelCase	,	"""os.path.getsize"""	,	wrap_auth(__UpperCamelCase			)			).start()
     patch_submodule(__UpperCamelCase	,	"""pathlib.Path"""	,	__UpperCamelCase			).start()
     # file readers
     patch_submodule(__UpperCamelCase	,	"""gzip.open"""	,	wrap_auth(__UpperCamelCase			)			).start()
     patch_submodule(__UpperCamelCase	,	"""numpy.load"""	,	wrap_auth(__UpperCamelCase			)			).start()
     patch_submodule(__UpperCamelCase	,	"""pandas.read_csv"""	,	wrap_auth(__UpperCamelCase			)	,	attrs=["""__version__"""]			).start()
     patch_submodule(__UpperCamelCase	,	"""pandas.read_excel"""	,	wrap_auth(__UpperCamelCase			)	,	attrs=["""__version__"""]			).start()
     patch_submodule(__UpperCamelCase	,	"""scipy.io.loadmat"""	,	wrap_auth(__UpperCamelCase			)	,	attrs=["""__version__"""]			).start()
     patch_submodule(__UpperCamelCase	,	"""xml.etree.ElementTree.parse"""	,	wrap_auth(__UpperCamelCase			)			).start()
     patch_submodule(__UpperCamelCase	,	"""xml.dom.minidom.parse"""	,	wrap_auth(__UpperCamelCase			)			).start()
     a_     :  Optional[int]				      =     True



def 			_a      (    __UpperCamelCase			):
     extend_module_for_streaming(builder.__module__	,	use_auth_token=builder.use_auth_token			)
     # if needed, we also have to extend additional internal imports (like wmt14 -> wmt_utils)
     if not builder.__module__.startswith("""datasets."""			):  # check that it's not a packaged builder like csv
          for imports in get_imports(inspect.getfile(builder.__class__			)			):
               if imports[0] == "internal":
                    a_     :  int				      =     imports[1]
                    a_     :  int				      =     """.""".join(builder.__module__.split("""."""			)[:-1] + [internal_import_name]			)
                    extend_module_for_streaming(__UpperCamelCase	,	use_auth_token=builder.use_auth_token			)

    # builders can inherit from other builders that might use streaming functionality
    # (for example, ImageFolder and AudioFolder inherit from FolderBuilder which implements examples generation)
    # but these parents builders are not patched automatically as they are not instantiated, so we patch them here
     from .builder import DatasetBuilder

     a_     :  Optional[int]				      =     [
         cls.__module__
         for cls in type(__UpperCamelCase			).__mro__[1:]  # make sure it's not the same module we've already patched
         if issubclass(cls	,	__UpperCamelCase			) and cls.__module__ != DatasetBuilder.__module__
     ]  # check it's not a standard builder from datasets.builder
     for module in parent_builder_modules:
          extend_module_for_streaming(__UpperCamelCase	,	use_auth_token=builder.use_auth_token			)










import argparse
import json
import re
import string
import sys
from collections import Counter




def  A_(      A ):

	def remove_articles(A ):
		return re.sub(R"""\b(a|an|the)\b"""					,   """ """					,   A )

	def white_space_fix(A ):
		return " ".join(text.split() )

	def remove_punc(A ):
		UpperCAmelCase_		    =  set(string.punctuation )
		return "".join(ch for ch in text if ch not in exclude )

	def lower(A ):
		return text.lower()

	return white_space_fix(remove_articles(remove_punc(lower(A ) ) ) )




def  A_(      A					,   A ):
	UpperCAmelCase_		    =  normalize_answer(A ).split()
	UpperCAmelCase_		    =  normalize_answer(A ).split()
	UpperCAmelCase_		    =  Counter(A ) & Counter(A )
	UpperCAmelCase_		    =  sum(common.values() )
	if num_same == 0:
		return 0
	UpperCAmelCase_		    =  1.0 * num_same / len(A )
	UpperCAmelCase_		    =  1.0 * num_same / len(A )
	UpperCAmelCase_		    =  (2 * precision * recall) / (precision + recall)
	return fa




def  A_(      A					,   A ):
	return normalize_answer(A ) == normalize_answer(A )




def  A_(      A					,   A					,   A ):
	UpperCAmelCase_		    =  []
	for ground_truth in ground_truths:
		UpperCAmelCase_		    =  metric_fn(A					,   A )
		scores_for_ground_truths.append(A )
	return max(A )




def  A_(      A					,   A ):
	UpperCAmelCase_		    =  UpperCAmelCase_		    =  UpperCAmelCase_		    =  0
	UpperCAmelCase_		    =  []
	for passage in dataset:
		for qa in passage["qas"]:
			total += 1
			if qa["id"] not in predictions:
				UpperCAmelCase_		    =  f"""Unanswered question {qa['id']} will receive score 0."""
				print(A					,   file=sys.stderr )
				continue

			UpperCAmelCase_		    =  [x["""text"""] for x in qa["""answers"""]]
			UpperCAmelCase_		    =  predictions[qa["""id"""]]

			UpperCAmelCase_		    =  metric_max_over_ground_truths(A					,   A					,   A )
			if int(_exact_match ) == 1:
				correct_ids.append(qa["""id"""] )
			exact_match += _exact_match

			fa += metric_max_over_ground_truths(A					,   A					,   A )

	UpperCAmelCase_		    =  exact_match / total
	UpperCAmelCase_		    =  fa / total

	return {"exact_match": exact_match, "f1": fa}, correct_ids


if __name__ == "__main__":
				UpperCamelCase__ :			Any       	=			"""1.0"""
				UpperCamelCase__ :			Optional[Any]       	=			argparse.ArgumentParser("""Official evaluation script for ReCoRD v1.0.""")
				parser.add_argument("""data_file""", help="""The dataset file in JSON format.""")
				parser.add_argument("""pred_file""", help="""The model prediction file in JSON format.""")
				parser.add_argument("""--output_correct_ids""", action="""store_true""", help="""Output the correctly answered query IDs.""")
				UpperCamelCase__ :			Any       	=			parser.parse_args()

				with open(args.data_file) as data_file:
								UpperCamelCase__ :			int       	=			json.load(data_file)
								if dataset_json["version"] != expected_version:
												print(
												    f"Evaluation expects v-{expected_version}, but got dataset with v-{dataset_json['version']}",
												    file=sys.stderr,
												)
								UpperCamelCase__ :			str       	=			dataset_json["""data"""]

				with open(args.pred_file) as pred_file:
								UpperCamelCase__ :			List[Any]       	=			json.load(pred_file)

				UpperCamelCase__	,      UpperCamelCase__ :			Optional[int]       	=			evaluate(dataset, predictions)

				if args.output_correct_ids:
								print(f"Output {len(correct_ids)} correctly answered question IDs.")
								with open("""correct_ids.json""", """w""") as f:
												json.dump(correct_ids, f)


