






"""simple docstring"""

import argparse
import json
import os
import time
import zipfile

from get_ci_error_statistics import download_artifact, get_artifacts_links

from transformers import logging


lowercase__  			=					logging.get_logger(__name__)

def 						__lowerCamelCase      (    __UpperCamelCase ,			__UpperCamelCase			)		->       Optional[Any]:

		"""simple docstring"""







		lowerCAmelCase_  :				Any   							=     set()
		lowerCAmelCase_  :				Any   							=     []

		def parse_line(__UpperCamelCase			):
				for line in fp:
						if isinstance(_snake_case ,			_snake_case			):
								lowerCAmelCase_  :				List[Any]   							=     line.decode("UTF-8"			)
						if "warnings summary (final)" in line:
								continue
						# This means we are outside the body of a warning
						elif not line.startswith(" "			):
								# process a single warning and move it to `selected_warnings`.
								if len(_snake_case			) > 0:
										lowerCAmelCase_  :				Optional[Any]   							=     '\n'.join(_snake_case			)
										# Only keep the warnings specified in `targets`
										if any(f''': {x}: ''' in warning for x in targets			):
												selected_warnings.add(_snake_case			)
										buffer.clear()
								continue
						else:
								lowerCAmelCase_  :				Optional[int]   							=     line.strip()
								buffer.append(_snake_case			)

		if from_gh:
				for filename in os.listdir(_snake_case			):
						lowerCAmelCase_  :				Optional[int]   							=     os.path.join(_snake_case ,			_snake_case			)
						if not os.path.isdir(_snake_case			):
								# read the file
								if filename != "warnings.txt":
										continue
								with open(_snake_case			) as fp:
										parse_line(_snake_case			)
		else:
				try:
						with zipfile.ZipFile(_snake_case			) as z:
								for filename in z.namelist():
										if not os.path.isdir(_snake_case			):
												# read the file
												if filename != "warnings.txt":
														continue
												with z.open(_snake_case			) as fp:
														parse_line(_snake_case			)
				except Exception:
						logger.warning(
						    f'''{artifact_path} is either an invalid zip file or something else wrong. This file is skipped.'''			)

		return selected_warnings

def 						__lowerCamelCase      (    __UpperCamelCase ,			__UpperCamelCase			)		->       Union[str, Any]:

		"""simple docstring"""







		lowerCAmelCase_  :				Union[str, Any]   							=     set()

		lowerCAmelCase_  :				Tuple   							=     [os.path.join(_snake_case ,			_snake_case			) for p in os.listdir(_snake_case			) if (p.endswith(".zip"			) or from_gh)]
		for p in paths:
				selected_warnings.update(extract_warnings_from_single_artifact(_snake_case ,			_snake_case			)			)

		return selected_warnings


if __name__ == "__main__":

					def 						__lowerCamelCase      (    __UpperCamelCase			)		->       int:

							"""simple docstring"""







							return values.split(","			)

					lowercase__  			=					argparse.ArgumentParser()
					# Required parameters
					parser.add_argument("""--workflow_run_id""", type=str, required=True, help="""A GitHub Actions workflow run id.""")
					parser.add_argument(
					    """--output_dir""",
					    type=str,
					    required=True,
					    help="""Where to store the downloaded artifacts and other result files.""",
					)
					parser.add_argument("""--token""", default=None, type=str, help="""A token that has actions:read permission.""")
					# optional parameters
					parser.add_argument(
					    """--targets""",
					    default="""DeprecationWarning,UserWarning,FutureWarning""",
					    type=list_str,
					    help="""Comma-separated list of target warning(s) which we want to extract.""",
					)
					parser.add_argument(
					    """--from_gh""",
					    action="""store_true""",
					    help="""If running from a GitHub action workflow and collecting warnings from its artifacts.""",
					)

					lowercase__  			=					parser.parse_args()

					lowercase__  			=					args.from_gh
					if from_gh:
										# The artifacts have to be downloaded using `actions/download-artifact@v3`
										pass
					else:
										os.makedirs(args.output_dir, exist_ok=True)

										# get download links
										lowercase__  			=					get_artifacts_links(args.workflow_run_id, token=args.token)
										with open(os.path.join(args.output_dir, """artifacts.json"""), """w""", encoding="""UTF-8""") as fp:
															json.dump(artifacts, fp, ensure_ascii=False, indent=4)

										# download artifacts
										for idx, (name, url) in enumerate(artifacts.items()):
															print(name)
															print(url)
															print("""=""" * 80)
															download_artifact(name, url, args.output_dir, args.token)
															# Be gentle to GitHub
															time.sleep(1)

    # extract warnings from artifacts
					lowercase__  			=					extract_warnings(args.output_dir, args.targets)
					lowercase__  			=					sorted(selected_warnings)
					with open(os.path.join(args.output_dir, """selected_warnings.json"""), """w""", encoding="""UTF-8""") as fp:
										json.dump(selected_warnings, fp, ensure_ascii=False, indent=4)


"""simple docstring"""



import unittest

from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


UpperCamelCase__          =	get_tests_dir('fixtures/test_sentencepiece.model')
UpperCamelCase__          =	get_tests_dir('fixtures/test_sentencepiece_bpe.model')

UpperCamelCase__          =	'pt' if is_torch_available() else 'tf'





@require_sentencepiece
@require_tokenizers
class 				a			(					lowercase						,		unittest.TestCase      ):
      UpperCamelCase							:   Optional[int]           =     CamembertTokenizer
      UpperCamelCase							:   Optional[int]           =     CamembertTokenizerFast
      UpperCamelCase							:   str           =     True
      UpperCamelCase							:   Tuple           =     True



      def  __snake_case							(   self      ):
          super().setUp()

          # We have a SentencePiece fixture for testing
          UpperCAmelCase__	:      int     							=					CamembertTokenizer(UpperCamelCase_      )
          tokenizer.save_pretrained(self.tmpdirname      )



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      Optional[int]     							=					'<pad>'
          UpperCAmelCase__	:      Tuple     							=					1

          self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCamelCase_      )     ,	UpperCamelCase_      )
          self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCamelCase_      )     ,	UpperCamelCase_      )



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      Optional[Any]     							=					list(self.get_tokenizer().get_vocab().keys()      )

          self.assertEqual(vocab_keys[0]     ,	'<s>NOTUSED'      )
          self.assertEqual(vocab_keys[1]     ,	'<pad>'      )
          self.assertEqual(vocab_keys[-1]     ,	'<mask>'      )
          self.assertEqual(len(UpperCamelCase_      )     ,	1_004      )



      def  __snake_case							(   self      ):
          self.assertEqual(self.get_tokenizer().vocab_size     ,	1_005      )



      def  __snake_case							(   self      ):
          UpperCAmelCase__	:      Dict     							=					CamembertTokenizer(UpperCamelCase_      )
          tokenizer.save_pretrained(self.tmpdirname      )
          UpperCAmelCase__	:      str     							=					CamembertTokenizerFast.from_pretrained(self.tmpdirname      )

          UpperCAmelCase__	:      Union[str, Any]     							=					'I was born in 92000, and this is falsé.'

          UpperCAmelCase__	:      Optional[Any]     							=					tokenizer.encode(UpperCamelCase_      )
          UpperCAmelCase__	:      Dict     							=					rust_tokenizer.encode(UpperCamelCase_      )
          self.assertListEqual(UpperCamelCase_     ,	UpperCamelCase_      )

          UpperCAmelCase__	:      str     							=					tokenizer.encode(UpperCamelCase_     ,	add_special_tokens=UpperCamelCase_      )
          UpperCAmelCase__	:      Union[str, Any]     							=					rust_tokenizer.encode(UpperCamelCase_     ,	add_special_tokens=UpperCamelCase_      )
          self.assertListEqual(UpperCamelCase_     ,	UpperCamelCase_      )

          # <unk> tokens are not the same for `rust` than for `slow`.
          # Because spm gives back raw token instead of `unk` in EncodeAsPieces
          # tokens = tokenizer.tokenize(sequence)
          UpperCAmelCase__	:      List[Any]     							=					tokenizer.convert_ids_to_tokens(UpperCamelCase_      )
          UpperCAmelCase__	:      str     							=					rust_tokenizer.tokenize(UpperCamelCase_      )
          self.assertListEqual(UpperCamelCase_     ,	UpperCamelCase_      )



      def  __snake_case							(   self      ):
          if not self.test_rust_tokenizer:
              return

          UpperCAmelCase__	:      Any     							=					self.get_tokenizer()
          UpperCAmelCase__	:      List[str]     							=					self.get_rust_tokenizer()

          UpperCAmelCase__	:      List[str]     							=					'I was born in 92000, and this is falsé.'

          UpperCAmelCase__	:      List[str]     							=					tokenizer.tokenize(UpperCamelCase_      )
          UpperCAmelCase__	:      str     							=					rust_tokenizer.tokenize(UpperCamelCase_      )
          self.assertListEqual(UpperCamelCase_     ,	UpperCamelCase_      )

          UpperCAmelCase__	:      Optional[Any]     							=					tokenizer.encode(UpperCamelCase_     ,	add_special_tokens=UpperCamelCase_      )
          UpperCAmelCase__	:      Union[str, Any]     							=					rust_tokenizer.encode(UpperCamelCase_     ,	add_special_tokens=UpperCamelCase_      )
          self.assertListEqual(UpperCamelCase_     ,	UpperCamelCase_      )

          UpperCAmelCase__	:      str     							=					self.get_rust_tokenizer()
          UpperCAmelCase__	:      Union[str, Any]     							=					tokenizer.encode(UpperCamelCase_      )
          UpperCAmelCase__	:      List[str]     							=					rust_tokenizer.encode(UpperCamelCase_      )
          self.assertListEqual(UpperCamelCase_     ,	UpperCamelCase_      )



      @slow
      def  __snake_case							(   self      ):
          # fmt: off
          UpperCAmelCase__	:      Any     							=					{'input_ids': [[5, 54, 7_196, 297, 30, 23, 776, 18, 11, 3_215, 3_705, 8_252, 22, 3_164, 1_181, 2_116, 29, 16, 813, 25, 791, 3_314, 20, 3_446, 38, 27_575, 120, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [5, 468, 17, 11, 9_088, 20, 1_517, 8, 22_804, 18_818, 10, 38, 629, 607, 607, 142, 19, 7_196, 867, 56, 10_326, 24, 2_267, 20, 416, 5_072, 15_612, 233, 734, 7, 2_399, 27, 16, 3_015, 1_649, 7, 24, 20, 4_338, 2_399, 27, 13, 3_400, 14, 13, 6_189, 8, 930, 9, 6]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
          # fmt: on

          # camembert is a french model. So we also use french texts.
          UpperCAmelCase__	:      Union[str, Any]     							=					[
              'Le transformeur est un modèle d\'apprentissage profond introduit en 2017, '
              'utilisé principalement dans le domaine du traitement automatique des langues (TAL).',
              'À l\'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus '
              'pour gérer des données séquentielles, telles que le langage naturel, pour des tâches '
              'telles que la traduction et la synthèse de texte.',
          ]

          self.tokenizer_integration_test_util(
              expected_encoding=UpperCamelCase_     ,	model_name='camembert-base'     ,	revision='3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf'     ,	sequences=UpperCamelCase_     ,	)

