





import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

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


_SCREAMING_SNAKE_CASE 		=						logging.get_logger(__name__)


_SCREAMING_SNAKE_CASE 		=						{
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

_SCREAMING_SNAKE_CASE 		=						{
    """vocab_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"""
    },
    """merges_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"""
    },
    """tokenizer_config_file""": {
        """facebook/blenderbot_small-90M""": (
            """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"""
        )
    },
}

_SCREAMING_SNAKE_CASE 		=						{"""facebook/blenderbot_small-90M""": 5_12}


def 							SCREAMING_SNAKE_CASE__  (      __a				):
	snake_case_						:     List[str]     =		set()
	snake_case_						:     str     =		word[0]
	for char in word[1:]:
		pairs.add((prev_char, char)				)
		snake_case_						:     Dict     =		char

	snake_case_						:     List[Any]     =		set(__a				)
	return pairs


class SCREAMING_SNAKE_CASE_  (   snake_case_   ):
						__magic_name__:     str	 =    VOCAB_FILES_NAMES
						__magic_name__:     Tuple	 =    PRETRAINED_VOCAB_FILES_MAP
						__magic_name__:     int	 =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						__magic_name__:     List[Any]	 =    ["input_ids", "attention_mask"]






						def __init__( self : str						,				_A : Any						,				_A : List[str]						,				_A : Optional[int]="__start__"						,				_A : List[str]="__end__"						,				_A : Dict="__unk__"						,				_A : Union[str, Any]="__null__"						,				**_A : List[Any]						,				)							->      Tuple:







							"""simple docstring"""


							super().__init__(unk_token=_A						,				bos_token=_A						,				eos_token=_A						,				pad_token=_A						,				**_A		)

							with open(_A						,				encoding='utf-8'		) as vocab_handle:
								snake_case_						:     List[Any]     =		json.load(_A		)
							snake_case_						:     Union[str, Any]     =		{v: k for k, v in self.encoder.items()}
							with open(_A						,				encoding='utf-8'		) as merges_handle:
								snake_case_						:     Optional[int]     =		merges_handle.read().split('\n'		)[1:-1]
							snake_case_						:     Union[str, Any]     =		[tuple(merge.split()		) for merge in merges]
							snake_case_						:     int     =		dict(zip(_A						,				range(len(_A		)		)		)		)
							snake_case_						:     List[Any]     =		{}






						@property
						def UpperCAmelCase_			( self : Dict		)							->      int:







							"""simple docstring"""


							return len(self.encoder		)






						def UpperCAmelCase_			( self : Tuple		)							->      Dict:







							"""simple docstring"""


							return dict(self.encoder						,				**self.added_tokens_encoder		)






						def UpperCAmelCase_			( self : Dict						,				_A : str		)							->      str:







							"""simple docstring"""


							if token in self.cache:
								return self.cache[token]
							snake_case_						:     Optional[Any]     =		re.sub('([.,!?()])'						,				R' \1'						,				_A		)
							snake_case_						:     List[str]     =		re.sub('(\')'						,				R' \1 '						,				_A		)
							snake_case_						:     Dict     =		re.sub(R'\s{2,}'						,				' '						,				_A		)
							if "\n" in token:
								snake_case_						:     Dict     =		token.replace('\n'						,				' __newln__'		)

							snake_case_						:     Dict     =		token.split(' '		)
							snake_case_						:     List[Any]     =		[]
							for token in tokens:
								if not len(_A		):
									continue

								snake_case_						:     Optional[int]     =		token.lower()
								snake_case_						:     Optional[int]     =		tuple(_A		)
								snake_case_						:     Tuple     =		tuple(list(word[:-1]		) + [word[-1] + '</w>']		)
								snake_case_						:     Tuple     =		get_pairs(_A		)

								if not pairs:
									words.append(_A		)
									continue

								while True:
									snake_case_						:     List[Any]     =		min(_A						,				key=lambda _A		: self.bpe_ranks.get(_A						,				float('inf'		)		)		)
									if bigram not in self.bpe_ranks:
										break
									snake_case_  ,snake_case_						:     List[str]     =		bigram
									snake_case_						:     Optional[Any]     =		[]
									snake_case_						:     Any     =		0

									while i < len(_A		):
										try:
											snake_case_						:     List[Any]     =		word.index(_A						,				_A		)
											new_word.extend(word[i:j]		)
											snake_case_						:     Any     =		j
										except ValueError:
											new_word.extend(word[i:]		)
											break

										if word[i] == first and i < len(_A		) - 1 and word[i + 1] == second:
											new_word.append(first + second		)
											i += 2
										else:
											new_word.append(word[i]		)
											i += 1
									snake_case_						:     Optional[Any]     =		tuple(_A		)
									snake_case_						:     str     =		new_word
									if len(_A		) == 1:
										break
									else:
										snake_case_						:     str     =		get_pairs(_A		)
								snake_case_						:     List[str]     =		'@@ '.join(_A		)
								snake_case_						:     Tuple     =		word[:-4]

								snake_case_						:     Union[str, Any]     =		word
								words.append(_A		)
							return " ".join(_A		)






						def UpperCAmelCase_			( self : List[str]						,				_A : str		)							->      List[str]:







							"""simple docstring"""


							snake_case_						:     Dict     =		[]

							snake_case_						:     List[str]     =		re.findall(R'\S+\n?'						,				_A		)

							for token in words:
								split_tokens.extend(list(self.bpe(_A		).split(' '		)		)		)
							return split_tokens






						def UpperCAmelCase_			( self : Dict						,				_A : str		)							->      int:







							"""simple docstring"""


							snake_case_						:     Any     =		token.lower()
							return self.encoder.get(_A						,				self.encoder.get(self.unk_token		)		)






						def UpperCAmelCase_			( self : int						,				_A : int		)							->      str:







							"""simple docstring"""


							return self.decoder.get(_A						,				self.unk_token		)






						def UpperCAmelCase_			( self : List[Any]						,				_A : List[str]		)							->      str:







							"""simple docstring"""


							snake_case_						:     str     =		' '.join(_A		).replace('@@ '						,				''		).strip()
							return out_string






						def UpperCAmelCase_			( self : Union[str, Any]						,				_A : str						,				_A : Optional[str] = None		)							->      Tuple[str]:







							"""simple docstring"""


							if not os.path.isdir(_A		):
								logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""		)
								return
							snake_case_						:     int     =		os.path.join(
							    _A						,				(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']		)
							snake_case_						:     List[Any]     =		os.path.join(
							    _A						,				(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']		)

							with open(_A						,				'w'						,				encoding='utf-8'		) as f:
								f.write(json.dumps(self.encoder						,				indent=2						,				sort_keys=_A						,				ensure_ascii=_A		) + '\n'		)

							snake_case_						:     Any     =		0
							with open(_A						,				'w'						,				encoding='utf-8'		) as writer:
								writer.write('#version: 0.2\n'		)
								for bpe_tokens, token_index in sorted(self.bpe_ranks.items()						,				key=lambda _A		: kv[1]		):
									if index != token_index:
										logger.warning(
										    F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
										    ' Please check that the tokenizer is not corrupted!'		)
										snake_case_						:     Optional[Any]     =		token_index
									writer.write(' '.join(_A		) + '\n'		)
									index += 1

							return vocab_file, merge_file








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

import requests


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a=None				):
	snake_case_						:     Optional[int]     =		None
	if token is not None:
		snake_case_						:     List[str]     =		{'Accept': 'application/vnd.github+json', 'Authorization': f"""Bearer {token}"""}

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

	try:
		job_links.update({job['name']: job['html_url'] for job in result['jobs']}				)
		snake_case_						:     Dict     =		math.ceil((result['total_count'] - 1_00) / 1_00				)

		for i in range(__a				):
			snake_case_						:     Optional[Any]     =		requests.get(url + f"""&page={i + 2}"""				,	headers=__a				).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 							SCREAMING_SNAKE_CASE__  (      __a				,	__a=None				):
	snake_case_						:     Union[str, Any]     =		None
	if token is not None:
		snake_case_						:     List[Any]     =		{'Accept': 'application/vnd.github+json', 'Authorization': f"""Bearer {token}"""}

	snake_case_						:     Optional[Any]     =		f"""https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100"""
	snake_case_						:     Union[str, Any]     =		requests.get(__a				,	headers=__a				).json()
	snake_case_						:     Any     =		{}

	try:
		artifacts.update({artifact['name']: artifact['archive_download_url'] for artifact in result['artifacts']}				)
		snake_case_						:     str     =		math.ceil((result['total_count'] - 1_00) / 1_00				)

		for i in range(__a				):
			snake_case_						:     int     =		requests.get(url + f"""&page={i + 2}"""				,	headers=__a				).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 							SCREAMING_SNAKE_CASE__  (      __a				,	__a				,	__a				,	__a				):
	snake_case_						:     Dict     =		None
	if token is not None:
		snake_case_						:     List[Any]     =		{'Accept': 'application/vnd.github+json', 'Authorization': f"""Bearer {token}"""}

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


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a=None				):
	snake_case_						:     Any     =		[]
	snake_case_						:     Any     =		[]
	snake_case_						:     Tuple     =		None

	with zipfile.ZipFile(__a				) as z:
		for filename in z.namelist():
			if not os.path.isdir(__a				):
				# read the file
				if filename in ["failures_line.txt", "summary_short.txt", "job_name.txt"]:
					with z.open(__a				) as f:
						for line in f:
							snake_case_						:     Tuple     =		line.decode('UTF-8'				).strip()
							if filename == "failures_line.txt":
								try:
									# `error_line` is the place where `error` occurs
									snake_case_						:     Tuple     =		line[: line.index(': '				)]
									snake_case_						:     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
								snake_case_						:     Any     =		line[len('FAILED '				) :]
								failed_tests.append(__a				)
							elif filename == "job_name.txt":
								snake_case_						:     Union[str, Any]     =		line

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

	snake_case_						:     List[str]     =		None
	if job_name and job_links:
		snake_case_						:     Union[str, Any]     =		job_links.get(__a				,	__a				)

	# A list with elements of the form (line of error, error, failed test)
	snake_case_						:     Optional[Any]     =		[x + [y] + [job_link] for x, y in zip(__a				,	__a				)]

	return result


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a=None				):
	snake_case_						:     Any     =		[]

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

	return errors


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a=None				):
	snake_case_						:     Optional[int]     =		Counter()
	counter.update([x[1] for x in logs]				)
	snake_case_						:     str     =		counter.most_common()
	snake_case_						:     Tuple     =		{}
	for error, count in counts:
		if error_filter is None or error not in error_filter:
			snake_case_						:     int     =		{'count': count, 'failed_tests': [(x[2], x[0]) for x in logs if x[1] == error]}

	snake_case_						:     int     =		dict(sorted(r.items()				,	key=lambda __a				: item[1]["count"]				,	reverse=__a				)				)
	return r


def 							SCREAMING_SNAKE_CASE__  (      __a				):
	snake_case_						:     Tuple     =		test.split('::'				)[0]
	if test.startswith('tests/models/'				):
		snake_case_						:     List[str]     =		test.split('/'				)[2]
	else:
		snake_case_						:     Union[str, Any]     =		None

	return test


def 							SCREAMING_SNAKE_CASE__  (      __a				,	__a=None				):
	snake_case_						:     Optional[int]     =		[(x[0], x[1], get_model(x[2]				)) for x in logs]
	snake_case_						:     str     =		[x for x in logs if x[2] is not None]
	snake_case_						:     int     =		{x[2] for x in logs}

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

	snake_case_						:     int     =		dict(sorted(r.items()				,	key=lambda __a				: item[1]["count"]				,	reverse=__a				)				)
	return r


def 							SCREAMING_SNAKE_CASE__  (      __a				):
	snake_case_						:     Optional[Any]     =		'| no. | error | status |'
	snake_case_						:     str     =		'|-:|:-|:-|'
	snake_case_						:     Tuple     =		[header, sep]
	for error in reduced_by_error:
		snake_case_						:     Dict     =		reduced_by_error[error]['count']
		snake_case_						:     List[str]     =		f"""| {count} | {error[:1_00]} |  |"""
		lines.append(__a				)

	return "\n".join(__a				)


def 							SCREAMING_SNAKE_CASE__  (      __a				):
	snake_case_						:     Optional[Any]     =		'| model | no. of errors | major error | count |'
	snake_case_						:     Union[str, Any]     =		'|-:|-:|-:|-:|'
	snake_case_						:     Optional[int]     =		[header, sep]
	for model in reduced_by_model:
		snake_case_						:     Any     =		reduced_by_model[model]['count']
		snake_case_  ,snake_case_						:     Dict     =		list(reduced_by_model[model]['errors'].items()				)[0]
		snake_case_						:     Any     =		f"""| {model} | {count} | {error[:60]} | {_count} |"""
		lines.append(__a				)

	return "\n".join(__a				)


if __name__ == "__main__":
						_SCREAMING_SNAKE_CASE 		=						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.""")
						_SCREAMING_SNAKE_CASE 		=						parser.parse_args()

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

						_SCREAMING_SNAKE_CASE 		=						get_job_links(args.workflow_run_id, token=args.token)
						_SCREAMING_SNAKE_CASE 		=						{}
						# 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:
																								_SCREAMING_SNAKE_CASE 		=						k.find(""" / """)
																								_SCREAMING_SNAKE_CASE 		=						k[index + len(""" / """) :]
																		_SCREAMING_SNAKE_CASE 		=						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)

						_SCREAMING_SNAKE_CASE 		=						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)

						_SCREAMING_SNAKE_CASE 		=						get_all_errors(args.output_dir, job_links=job_links)

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

						# print the top 30 most common test errors
						_SCREAMING_SNAKE_CASE 		=						counter.most_common(30)
						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)

						_SCREAMING_SNAKE_CASE 		=						reduce_by_error(errors)
						_SCREAMING_SNAKE_CASE 		=						reduce_by_model(errors)

						_SCREAMING_SNAKE_CASE 		=						make_github_table(reduced_by_error)
						_SCREAMING_SNAKE_CASE 		=						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)

