



"""simple docstring"""






import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter

import requests






def      snake_case__   (		__lowerCamelCase				:    Any							,		__lowerCamelCase				:    Any=None	):
			"""simple docstring"""
			lowerCamelCase__		:		Optional[int]			=None
			if token is not None:
						lowerCamelCase__		:		str			={'''Accept''': '''application/vnd.github+json''', '''Authorization''': f'''Bearer {token}'''}

			lowerCamelCase__		:		Optional[Any]			=f'''https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100'''
			lowerCamelCase__		:		Union[str, Any]			=requests.get(__lowerCamelCase							,		headers=__lowerCamelCase	).json()
			lowerCamelCase__		:		int			={}

			try:
						job_links.update({job['''name''']: job['''html_url'''] for job in result['''jobs''']}	)
						lowerCamelCase__		:		List[str]			=math.ceil((result['''total_count'''] - 100) / 100	)

						for i in range(__lowerCamelCase	):
									lowerCamelCase__		:		Tuple			=requests.get(url + f'''&page={i + 2}'''							,		headers=__lowerCamelCase	).json()
									job_links.update({job['''name''']: job['''html_url'''] for job in result['''jobs''']}	)

						return job_links
			except Exception:
						print(f'''Unknown error, could not fetch links:\n{traceback.format_exc()}'''	)

			return {}






def      snake_case__   (		__lowerCamelCase				:    Optional[int]							,		__lowerCamelCase				:    List[Any]=None	):
			"""simple docstring"""
			lowerCamelCase__		:		Any			=None
			if token is not None:
						lowerCamelCase__		:		Union[str, Any]			={'''Accept''': '''application/vnd.github+json''', '''Authorization''': f'''Bearer {token}'''}

			lowerCamelCase__		:		int			=f'''https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100'''
			lowerCamelCase__		:		Optional[int]			=requests.get(__lowerCamelCase							,		headers=__lowerCamelCase	).json()
			lowerCamelCase__		:		Optional[int]			={}

			try:
						artifacts.update({artifact['''name''']: artifact['''archive_download_url'''] for artifact in result['''artifacts''']}	)
						lowerCamelCase__		:		List[str]			=math.ceil((result['''total_count'''] - 100) / 100	)

						for i in range(__lowerCamelCase	):
									lowerCamelCase__		:		str			=requests.get(url + f'''&page={i + 2}'''							,		headers=__lowerCamelCase	).json()
									artifacts.update({artifact['''name''']: artifact['''archive_download_url'''] for artifact in result['''artifacts''']}	)

						return artifacts
			except Exception:
						print(f'''Unknown error, could not fetch links:\n{traceback.format_exc()}'''	)

			return {}






def      snake_case__   (		__lowerCamelCase				:    str							,		__lowerCamelCase				:    Union[str, Any]							,		__lowerCamelCase				:    List[str]							,		__lowerCamelCase				:    List[Any]	):
			"""simple docstring"""
			lowerCamelCase__		:		List[Any]			=None
			if token is not None:
						lowerCamelCase__		:		Any			={'''Accept''': '''application/vnd.github+json''', '''Authorization''': f'''Bearer {token}'''}

			lowerCamelCase__		:		List[str]			=requests.get(__lowerCamelCase							,		headers=__lowerCamelCase							,		allow_redirects=__lowerCamelCase	)
			lowerCamelCase__		:		Tuple			=result.headers['''Location''']
			lowerCamelCase__		:		List[Any]			=requests.get(__lowerCamelCase							,		allow_redirects=__lowerCamelCase	)
			lowerCamelCase__		:		Tuple			=os.path.join(__lowerCamelCase							,		f'''{artifact_name}.zip'''	)
			with open(__lowerCamelCase							,		'''wb'''	) as fp:
						fp.write(response.content	)






def      snake_case__   (		__lowerCamelCase				:    int							,		__lowerCamelCase				:    Any=None	):
			"""simple docstring"""
			lowerCamelCase__		:		Tuple			=[]
			lowerCamelCase__		:		Any			=[]
			lowerCamelCase__		:		Optional[Any]			=None

			with zipfile.ZipFile(__lowerCamelCase	) as z:
						for filename in z.namelist():
									if not os.path.isdir(__lowerCamelCase	):
												# read the file
												if filename in ["failures_line.txt", "summary_short.txt", "job_name.txt"]:
															with z.open(__lowerCamelCase	) as f:
																		for line in f:
																					lowerCamelCase__		:		List[str]			=line.decode('''UTF-8'''	).strip()
																					if filename == "failures_line.txt":
																								try:
																											# `error_line` is the place where `error` occurs
																											lowerCamelCase__		:		Tuple			=line[: line.index(''': '''	)]
																											lowerCamelCase__		:		Union[str, Any]			=line[line.index(''': '''	) + len(''': '''	) :]
																											errors.append([error_line, error]	)
																								except Exception:
																											# skip un-related lines
																											pass
																					elif filename == "summary_short.txt" and line.startswith('''FAILED '''	):
																								# `test` is the test method that failed
																								lowerCamelCase__		:		Any			=line[len('''FAILED '''	) :]
																								failed_tests.append(__lowerCamelCase	)
																					elif filename == "job_name.txt":
																								lowerCamelCase__		:		Union[str, Any]			=line

			if len(__lowerCamelCase	) != len(__lowerCamelCase	):
						raise ValueError(
						    f'''`errors` and `failed_tests` should have the same number of elements. Got {len(__lowerCamelCase	)} for `errors` '''
						    f'''and {len(__lowerCamelCase	)} for `failed_tests` instead. The test reports in {artifact_zip_path} have some'''
						    ''' problem.'''	)

			lowerCamelCase__		:		Tuple			=None
			if job_name and job_links:
						lowerCamelCase__		:		Optional[Any]			=job_links.get(__lowerCamelCase							,		__lowerCamelCase	)

			# A list with elements of the form (line of error, error, failed test)
			lowerCamelCase__		:		str			=[x + [y] + [job_link] for x, y in zip(__lowerCamelCase							,		__lowerCamelCase	)]

			return result






def      snake_case__   (		__lowerCamelCase				:    Tuple							,		__lowerCamelCase				:    Optional[int]=None	):
			"""simple docstring"""
			lowerCamelCase__		:		int			=[]

			lowerCamelCase__		:		Union[str, Any]			=[os.path.join(__lowerCamelCase							,		__lowerCamelCase	) for p in os.listdir(__lowerCamelCase	) if p.endswith('''.zip'''	)]
			for p in paths:
						errors.extend(get_errors_from_single_artifact(__lowerCamelCase							,		job_links=__lowerCamelCase	)	)

			return errors






def      snake_case__   (		__lowerCamelCase				:    Optional[Any]							,		__lowerCamelCase				:    Any=None	):
			"""simple docstring"""
			lowerCamelCase__		:		List[str]			=Counter()
			counter.update([x[1] for x in logs]	)
			lowerCamelCase__		:		int			=counter.most_common()
			lowerCamelCase__		:		Optional[Any]			={}
			for error, count in counts:
						if error_filter is None or error not in error_filter:
									lowerCamelCase__		:		int			={'''count''': count, '''failed_tests''': [(x[2], x[0]) for x in logs if x[1] == error]}

			lowerCamelCase__		:		Optional[Any]			=dict(sorted(r.items()							,		key=lambda __lowerCamelCase	: item[1]["count"]							,		reverse=__lowerCamelCase	)	)
			return r






def      snake_case__   (		__lowerCamelCase				:    List[str]	):
			"""simple docstring"""
			lowerCamelCase__		:		Union[str, Any]			=test.split('''::'''	)[0]
			if test.startswith('''tests/models/'''	):
						lowerCamelCase__		:		Any			=test.split('''/'''	)[2]
			else:
						lowerCamelCase__		:		Optional[Any]			=None

			return test






def      snake_case__   (		__lowerCamelCase				:    int							,		__lowerCamelCase				:    List[str]=None	):
			"""simple docstring"""
			lowerCamelCase__		:		Optional[int]			=[(x[0], x[1], get_model(x[2]	)) for x in logs]
			lowerCamelCase__		:		Any			=[x for x in logs if x[2] is not None]
			lowerCamelCase__		:		int			={x[2] for x in logs}

			lowerCamelCase__		:		str			={}
			for test in tests:
						lowerCamelCase__		:		str			=Counter()
						# count by errors in `test`
						counter.update([x[1] for x in logs if x[2] == test]	)
						lowerCamelCase__		:		List[Any]			=counter.most_common()
						lowerCamelCase__		:		int			={error: count for error, count in counts if (error_filter is None or error not in error_filter)}
						lowerCamelCase__		:		Optional[Any]			=sum(error_counts.values()	)
						if n_errors > 0:
									lowerCamelCase__		:		Dict			={'''count''': n_errors, '''errors''': error_counts}

			lowerCamelCase__		:		Tuple			=dict(sorted(r.items()							,		key=lambda __lowerCamelCase	: item[1]["count"]							,		reverse=__lowerCamelCase	)	)
			return r






def      snake_case__   (		__lowerCamelCase				:    int	):
			"""simple docstring"""
			lowerCamelCase__		:		Optional[int]			='''| no. | error | status |'''
			lowerCamelCase__		:		Optional[Any]			='''|-:|:-|:-|'''
			lowerCamelCase__		:		Any			=[header, sep]
			for error in reduced_by_error:
						lowerCamelCase__		:		Any			=reduced_by_error[error]['''count''']
						lowerCamelCase__		:		Optional[int]			=f'''| {count} | {error[:100]} |  |'''
						lines.append(__lowerCamelCase	)

			return "\n".join(__lowerCamelCase	)






def      snake_case__   (		__lowerCamelCase				:    str	):
			"""simple docstring"""
			lowerCamelCase__		:		str			='''| model | no. of errors | major error | count |'''
			lowerCamelCase__		:		Optional[int]			='''|-:|-:|-:|-:|'''
			lowerCamelCase__		:		List[Any]			=[header, sep]
			for model in reduced_by_model:
						lowerCamelCase__		:		str			=reduced_by_model[model]['''count''']
						lowerCamelCase__	,   lowerCamelCase__		:		Tuple			=list(reduced_by_model[model]['''errors'''].items()	)[0]
						lowerCamelCase__		:		Tuple			=f'''| {model} | {count} | {error[:60]} | {_count} |'''
						lines.append(__lowerCamelCase	)

			return "\n".join(__lowerCamelCase	)


if __name__ == "__main__":
		_lowercase : Tuple      						=						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.")
		_lowercase : int      						=						parser.parse_args()

		os.makedirs(args.output_dir, exist_ok=True)

		_lowercase : List[Any]      						=						get_job_links(args.workflow_run_id, token=args.token)
		_lowercase : str      						=						{}
		# To deal with `workflow_call` event, where a job name is the combination of the job names in the caller and callee.
		# For example, `PyTorch 1.11 / Model tests (models/albert, single-gpu)`.
		if _job_links:
				for k, v in _job_links.items():
						# This is how GitHub actions combine job names.
						if " / " in k:
								_lowercase : List[str]      						=						k.find(" / ")
								_lowercase : Any      						=						k[index + len(" / ") :]
						_lowercase : str      						=						v
		with open(os.path.join(args.output_dir, "job_links.json"), "w", encoding="UTF-8") as fp:
				json.dump(job_links, fp, ensure_ascii=False, indent=4)

		_lowercase : Optional[Any]      						=						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)

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

		_lowercase : Any      						=						get_all_errors(args.output_dir, job_links=job_links)

		# `e[1]` is the error
		_lowercase : int      						=						Counter()
		counter.update([e[1] for e in errors])

		# print the top 30 most common test errors
		_lowercase : Union[str, Any]      						=						counter.most_common(3_0)
		for item in most_common:
				print(item)

		with open(os.path.join(args.output_dir, "errors.json"), "w", encoding="UTF-8") as fp:
				json.dump(errors, fp, ensure_ascii=False, indent=4)

		_lowercase : Union[str, Any]      						=						reduce_by_error(errors)
		_lowercase : Union[str, Any]      						=						reduce_by_model(errors)

		_lowercase : Any      						=						make_github_table(reduced_by_error)
		_lowercase : Optional[Any]      						=						make_github_table_per_model(reduced_by_model)

		with open(os.path.join(args.output_dir, "reduced_by_error.txt"), "w", encoding="UTF-8") as fp:
				fp.write(sa)
		with open(os.path.join(args.output_dir, "reduced_by_model.txt"), "w", encoding="UTF-8") as fp:
				fp.write(sa)









"""simple docstring"""






import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_lowercase : Optional[int]      						=						"▁"

_lowercase : Optional[Any]      						=						{"vocab_file": "spiece.model"}

_lowercase : Optional[Any]      						=						{
    "vocab_file": {"google/pegasus-xsum": "https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model"}
}

_lowercase : Tuple      						=						{
    "google/pegasus-xsum": 5_1_2,
}


_lowercase : Optional[int]      						=						logging.get_logger(__name__)

class        __SCREAMING_SNAKE_CASE	(      lowerCAmelCase_   ):


					'''simple docstring'''





					_a   			=							VOCAB_FILES_NAMES

					_a   			=							VOCAB_FILES_NAMES
					_a   			=							PRETRAINED_VOCAB_FILES_MAP
					_a   			=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					_a   			=							['input_ids', 'attention_mask']



					def __init__(       self							:  Any,  lowerCamelCase							:  Optional[Any],  lowerCamelCase							:  Any="<pad>",  lowerCamelCase							:  Optional[Any]="</s>",  lowerCamelCase							:  Any="<unk>",  lowerCamelCase							:  Tuple="<mask_2>",  lowerCamelCase							:  int="<mask_1>",  lowerCamelCase							:  Optional[Any]=None,  lowerCamelCase							:  Dict=103,  lowerCamelCase							:  Optional[Dict[str, Any]] = None,  **lowerCamelCase							:  Optional[int],  )->					None:
								lowerCamelCase__		:		Union[str, Any]			=offset
								if additional_special_tokens is not None:
											if not isinstance(lowerCamelCase,  lowerCamelCase     ):
														raise TypeError(
														    F'''additional_special_tokens should be of type {type(lowerCamelCase     )}, but is'''
														    F''' {type(lowerCamelCase     )}'''     )

											lowerCamelCase__		:		Any			=(
											    ([mask_token_sent] + additional_special_tokens)
											    if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
											    else additional_special_tokens
											)
											# fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
											additional_special_tokens_extended += [
											    F'''<unk_{i}>''' for i in range(len(lowerCamelCase     ),  self.offset - 1     )
											]

											if len(set(lowerCamelCase     )     ) != len(lowerCamelCase     ):
														raise ValueError(
														    '''Please make sure that the provided additional_special_tokens do not contain an incorrectly'''
														    F''' shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}.'''     )
											lowerCamelCase__		:		Optional[Any]			=additional_special_tokens_extended
								else:
											lowerCamelCase__		:		Tuple			=[mask_token_sent] if mask_token_sent is not None else []
											additional_special_tokens += [F'''<unk_{i}>''' for i in range(2,  self.offset     )]

								lowerCamelCase__		:		Tuple			={} if sp_model_kwargs is None else sp_model_kwargs

								super().__init__(
								    eos_token=lowerCamelCase,  unk_token=lowerCamelCase,  mask_token=lowerCamelCase,  pad_token=lowerCamelCase,  mask_token_sent=lowerCamelCase,  offset=lowerCamelCase,  additional_special_tokens=lowerCamelCase,  sp_model_kwargs=self.sp_model_kwargs,  **lowerCamelCase,  )
								lowerCamelCase__		:		Optional[int]			=mask_token_sent
								lowerCamelCase__		:		Optional[Any]			=vocab_file
								lowerCamelCase__		:		List[str]			=spm.SentencePieceProcessor(**self.sp_model_kwargs     )
								self.sp_model.Load(lowerCamelCase     )

								# add special tokens to encoder dict
								lowerCamelCase__		:		Dict[int, str]			={
								    0: self.pad_token,
								    1: self.eos_token,
								}

								if self.mask_token_sent is not None:
											self.encoder.update(
											    {
											        2: self.mask_token_sent,
											        3: self.mask_token,
											    }     )

								if self.offset > 0:
											# entries 2-104 are only used for pretraining and called <mask_1>, <mask_2>, unk_2, ...unk_102
											# mask_token_sent is already added to list -> so start at 1
											self.encoder.update({i + 3: additional_special_tokens[i] for i in range(1,  self.offset - 1     )}     )

								lowerCamelCase__		:		Dict[str, int]			={v: k for k, v in self.encoder.items()}



					@property
					def 		snake_case       (       self							:  Union[str, Any]     )->					int:
								return len(self.sp_model     ) + self.offset



					def 		snake_case       (       self							:  Optional[Any]     )->					Dict[str, int]:
								lowerCamelCase__		:		List[Any]			={self.convert_ids_to_tokens(lowerCamelCase     ): i for i in range(self.vocab_size     )}
								vocab.update(self.added_tokens_encoder     )
								return vocab



					def __getstate__(       self							:  str     )->					List[Any]:
								lowerCamelCase__		:		Optional[Any]			=self.__dict__.copy()
								lowerCamelCase__		:		Optional[int]			=None
								return state



					def __setstate__(       self							:  Dict,  lowerCamelCase							:  int     )->					Optional[Any]:
								lowerCamelCase__		:		Optional[int]			=d

								# for backward compatibility
								if not hasattr(self,  '''sp_model_kwargs'''     ):
											lowerCamelCase__		:		str			={}

								lowerCamelCase__		:		Union[str, Any]			=spm.SentencePieceProcessor(**self.sp_model_kwargs     )
								self.sp_model.Load(self.vocab_file     )



					def 		snake_case       (       self							:  Any,  lowerCamelCase							:  str     )->					List[str]:
								return self.sp_model.encode(lowerCamelCase,  out_type=lowerCamelCase     )



					def 		snake_case       (       self							:  int,  lowerCamelCase							:  str     )->					int:
								if token in self.decoder:
											return self.decoder[token]
								elif token in self.added_tokens_decoder:
											return self.added_tokens_decoder[token]
								lowerCamelCase__		:		Any			=self.sp_model.piece_to_id(lowerCamelCase     )
								return sp_id + self.offset



					def 		snake_case       (       self							:  Tuple,  lowerCamelCase							:  int     )->					str:
								if index in self.encoder:
											return self.encoder[index]
								elif index in self.added_tokens_encoder:
											return self.added_tokens_encoder[index]
								else:
											lowerCamelCase__		:		Any			=self.sp_model.IdToPiece(index - self.offset     )
								return token



					def 		snake_case       (       self							:  List[Any],  lowerCamelCase							:  Optional[int]     )->					Any:
								lowerCamelCase__		:		Optional[int]			=[]
								lowerCamelCase__		:		Tuple			=''''''
								for token in tokens:
											# make sure that special tokens are not decoded using sentencepiece model
											if token in self.all_special_tokens:
														out_string += self.sp_model.decode(lowerCamelCase     ) + token
														lowerCamelCase__		:		str			=[]
											else:
														current_sub_tokens.append(lowerCamelCase     )
								out_string += self.sp_model.decode(lowerCamelCase     )
								return out_string.strip()



					def 		snake_case       (       self							:  Union[str, Any],  lowerCamelCase							:  Union[str, Any]=False     )->					List[str]:
								return 1



					def 		snake_case       (       self							:  Tuple,  lowerCamelCase							:  Optional[int]     )->					Tuple:
								lowerCamelCase__		:		Tuple			=set(self.all_special_ids     )  # call it once instead of inside list comp
								all_special_ids.remove(self.unk_token_id     )  # <unk> is only sometimes special

								return [1 if x in all_special_ids else 0 for x in seq]



					def 		snake_case       (       self							:  Any,  lowerCamelCase							:  List,  lowerCamelCase							:  Optional[List] = None,  lowerCamelCase							:  bool = False     )->					List[int]:
								if already_has_special_tokens:
											return self._special_token_mask(lowerCamelCase     )
								elif token_ids_a is None:
											return self._special_token_mask(lowerCamelCase     ) + [1]
								else:
											return self._special_token_mask(token_ids_a + token_ids_a     ) + [1]



					def 		snake_case       (       self							:  Optional[Any],  lowerCamelCase							:  List[str],  lowerCamelCase							:  Optional[int]=None     )->					List[int]:
								if token_ids_a is None:
											return token_ids_a + [self.eos_token_id]
								# We don't expect to process pairs, but leave the pair logic for API consistency
								return token_ids_a + token_ids_a + [self.eos_token_id]




					def 		snake_case       (       self							:  Optional[int],  lowerCamelCase							:  str,  lowerCamelCase							:  Optional[str] = None     )->					Tuple[str]:
								if not os.path.isdir(lowerCamelCase     ):
											logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''     )
											return
								lowerCamelCase__		:		List[str]			=os.path.join(
								    lowerCamelCase,  (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']     )

								if os.path.abspath(self.vocab_file     ) != os.path.abspath(lowerCamelCase     ) and os.path.isfile(self.vocab_file     ):
											copyfile(self.vocab_file,  lowerCamelCase     )
								elif not os.path.isfile(self.vocab_file     ):
											with open(lowerCamelCase,  '''wb'''     ) as fi:
														lowerCamelCase__		:		int			=self.sp_model.serialized_model_proto()
														fi.write(lowerCamelCase     )

								return (out_vocab_file,)




