


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

import requests







def 						lowerCamelCase(   a__	,a__=None):
				_SCREAMING_SNAKE_CASE			  =None
				if token is not None:
								_SCREAMING_SNAKE_CASE			  ={'''Accept''': '''application/vnd.github+json''', '''Authorization''': f"Bearer {token}"}

				_SCREAMING_SNAKE_CASE			  =f"https://api.github.com/repos/huggingface/transformers/actions/runs/{workflow_run_id}/jobs?per_page=100"
				_SCREAMING_SNAKE_CASE			  =requests.get(a__	,headers=a__).json()
				_SCREAMING_SNAKE_CASE			  ={}

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

								for i in range(a__):
												_SCREAMING_SNAKE_CASE			  =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 						lowerCamelCase(   a__	,a__=None):
				_SCREAMING_SNAKE_CASE			  =None
				if token is not None:
								_SCREAMING_SNAKE_CASE			  ={'''Accept''': '''application/vnd.github+json''', '''Authorization''': f"Bearer {token}"}

				_SCREAMING_SNAKE_CASE			  =f"https://api.github.com/repos/huggingface/transformers/actions/runs/{worflow_run_id}/artifacts?per_page=100"
				_SCREAMING_SNAKE_CASE			  =requests.get(a__	,headers=a__).json()
				_SCREAMING_SNAKE_CASE			  ={}

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

								for i in range(a__):
												_SCREAMING_SNAKE_CASE			  =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 						lowerCamelCase(   a__	,a__	,a__	,a__):
				_SCREAMING_SNAKE_CASE			  =None
				if token is not None:
								_SCREAMING_SNAKE_CASE			  ={'''Accept''': '''application/vnd.github+json''', '''Authorization''': f"Bearer {token}"}

				_SCREAMING_SNAKE_CASE			  =requests.get(a__	,headers=a__	,allow_redirects=a__)
				_SCREAMING_SNAKE_CASE			  =result.headers['''Location''']
				_SCREAMING_SNAKE_CASE			  =requests.get(a__	,allow_redirects=a__)
				_SCREAMING_SNAKE_CASE			  =os.path.join(a__	,f"{artifact_name}.zip")
				with open(a__	,'''wb''') as fp:
								fp.write(response.content)







def 						lowerCamelCase(   a__	,a__=None):
				_SCREAMING_SNAKE_CASE			  =[]
				_SCREAMING_SNAKE_CASE			  =[]
				_SCREAMING_SNAKE_CASE			  =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:
																												_SCREAMING_SNAKE_CASE			  =line.decode('''UTF-8''').strip()
																												if filename == "failures_line.txt":
																																try:
																																				# `error_line` is the place where `error` occurs
																																				_SCREAMING_SNAKE_CASE			  =line[: line.index(''': ''')]
																																				_SCREAMING_SNAKE_CASE			  =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
																																_SCREAMING_SNAKE_CASE			  =line[len('''FAILED ''') :]
																																failed_tests.append(a__)
																												elif filename == "job_name.txt":
																																_SCREAMING_SNAKE_CASE			  =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.''')

				_SCREAMING_SNAKE_CASE			  =None
				if job_name and job_links:
								_SCREAMING_SNAKE_CASE			  =job_links.get(a__	,a__)

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

				return result







def 						lowerCamelCase(   a__	,a__=None):
				_SCREAMING_SNAKE_CASE			  =[]

				_SCREAMING_SNAKE_CASE			  =[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 						lowerCamelCase(   a__	,a__=None):
				_SCREAMING_SNAKE_CASE			  =Counter()
				counter.update([x[1] for x in logs])
				_SCREAMING_SNAKE_CASE			  =counter.most_common()
				_SCREAMING_SNAKE_CASE			  ={}
				for error, count in counts:
								if error_filter is None or error not in error_filter:
												_SCREAMING_SNAKE_CASE			  ={'''count''': count, '''failed_tests''': [(x[2], x[0]) for x in logs if x[1] == error]}

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







def 						lowerCamelCase(   a__):
				_SCREAMING_SNAKE_CASE			  =test.split('''::''')[0]
				if test.startswith('''tests/models/'''):
								_SCREAMING_SNAKE_CASE			  =test.split('''/''')[2]
				else:
								_SCREAMING_SNAKE_CASE			  =None

				return test







def 						lowerCamelCase(   a__	,a__=None):
				_SCREAMING_SNAKE_CASE			  =[(x[0], x[1], get_model(x[2])) for x in logs]
				_SCREAMING_SNAKE_CASE			  =[x for x in logs if x[2] is not None]
				_SCREAMING_SNAKE_CASE			  ={x[2] for x in logs}

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

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







def 						lowerCamelCase(   a__):
				_SCREAMING_SNAKE_CASE			  ='''| no. | error | status |'''
				_SCREAMING_SNAKE_CASE			  ='''|-:|:-|:-|'''
				_SCREAMING_SNAKE_CASE			  =[header, sep]
				for error in reduced_by_error:
								_SCREAMING_SNAKE_CASE			  =reduced_by_error[error]['''count''']
								_SCREAMING_SNAKE_CASE			  =f"| {count} | {error[:100]} |  |"
								lines.append(a__)

				return "\n".join(a__)







def 						lowerCamelCase(   a__):
				_SCREAMING_SNAKE_CASE			  ='''| model | no. of errors | major error | count |'''
				_SCREAMING_SNAKE_CASE			  ='''|-:|-:|-:|-:|'''
				_SCREAMING_SNAKE_CASE			  =[header, sep]
				for model in reduced_by_model:
								_SCREAMING_SNAKE_CASE			  =reduced_by_model[model]['''count''']
								_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE			  =list(reduced_by_model[model]['''errors'''].items())[0]
								_SCREAMING_SNAKE_CASE			  =f"| {model} | {count} | {error[:60]} | {_count} |"
								lines.append(a__)

				return "\n".join(a__)


if __name__ == "__main__":
							snake_case_						:			List[str]													=							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.''')
							snake_case_						:			Optional[Any]													=							parser.parse_args()

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

							snake_case_						:			int													=							get_job_links(args.workflow_run_id, token=args.token)
							snake_case_						:			List[Any]													=							{}
							# 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:
																												snake_case_						:			List[Any]													=							k.find(''' / ''')
																												snake_case_						:			Any													=							k[index + len(''' / ''') :]
																					snake_case_						:			List[Any]													=							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)

							snake_case_						:			Union[str, 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)

							snake_case_						:			str													=							get_all_errors(args.output_dir, job_links=job_links)

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

							# print the top 30 most common test errors
							snake_case_						:			List[str]													=							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)

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

							snake_case_						:			List[Any]													=							make_github_table(reduced_by_error)
							snake_case_						:			Dict													=							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)



import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union

import pandas as pd
import pyarrow as pa

import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_utils import Literal


snake_case_						:			Any													=							datasets.utils.logging.get_logger(__name__)

snake_case_						:			List[Any]													=							['''names''', '''prefix''']
snake_case_						:			Dict													=							['''warn_bad_lines''', '''error_bad_lines''', '''mangle_dupe_cols''']
snake_case_						:			Dict													=							['''encoding_errors''', '''on_bad_lines''']
snake_case_						:			Optional[Any]													=							['''date_format''']

@dataclass
class 						A__							(		datasets.BuilderConfig  ):
						UpperCAmelCase             =						","
						UpperCAmelCase             =						None
						UpperCAmelCase             =						"infer"
						UpperCAmelCase             =						None
						UpperCAmelCase             =						None
						UpperCAmelCase             =						None
						UpperCAmelCase             =						None
						UpperCAmelCase             =						None
						UpperCAmelCase             =						True
						UpperCAmelCase             =						None
						UpperCAmelCase             =						None
						UpperCAmelCase             =						None
						UpperCAmelCase             =						None
						UpperCAmelCase             =						False
						UpperCAmelCase             =						None
						UpperCAmelCase             =						None
						UpperCAmelCase             =						None
						UpperCAmelCase             =						True
						UpperCAmelCase             =						True
						UpperCAmelCase             =						False
						UpperCAmelCase             =						True
						UpperCAmelCase             =						None
						UpperCAmelCase             =						"."
						UpperCAmelCase             =						None
						UpperCAmelCase             =						'"'
						UpperCAmelCase             =						0
						UpperCAmelCase             =						None
						UpperCAmelCase             =						None
						UpperCAmelCase             =						None
						UpperCAmelCase             =						None
						UpperCAmelCase             =						True
						UpperCAmelCase             =						True
						UpperCAmelCase             =						0
						UpperCAmelCase             =						True
						UpperCAmelCase             =						False
						UpperCAmelCase             =						None
						UpperCAmelCase             =						10000
						UpperCAmelCase             =						None
						UpperCAmelCase             =						"strict"
						UpperCAmelCase             =						"error"
						UpperCAmelCase             =						None




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


										"""simple docstring"""





										if self.delimiter is not None:
														_SCREAMING_SNAKE_CASE			  =self.delimiter
										if self.column_names is not None:
														_SCREAMING_SNAKE_CASE			  =self.column_names




						@property
						def 							__UpperCamelCase				(       self					:      Dict  )							->     List[Any]:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  ={
										    '''sep''': self.sep,
										    '''header''': self.header,
										    '''names''': self.names,
										    '''index_col''': self.index_col,
										    '''usecols''': self.usecols,
										    '''prefix''': self.prefix,
										    '''mangle_dupe_cols''': self.mangle_dupe_cols,
										    '''engine''': self.engine,
										    '''converters''': self.converters,
										    '''true_values''': self.true_values,
										    '''false_values''': self.false_values,
										    '''skipinitialspace''': self.skipinitialspace,
										    '''skiprows''': self.skiprows,
										    '''nrows''': self.nrows,
										    '''na_values''': self.na_values,
										    '''keep_default_na''': self.keep_default_na,
										    '''na_filter''': self.na_filter,
										    '''verbose''': self.verbose,
										    '''skip_blank_lines''': self.skip_blank_lines,
										    '''thousands''': self.thousands,
										    '''decimal''': self.decimal,
										    '''lineterminator''': self.lineterminator,
										    '''quotechar''': self.quotechar,
										    '''quoting''': self.quoting,
										    '''escapechar''': self.escapechar,
										    '''comment''': self.comment,
										    '''encoding''': self.encoding,
										    '''dialect''': self.dialect,
										    '''error_bad_lines''': self.error_bad_lines,
										    '''warn_bad_lines''': self.warn_bad_lines,
										    '''skipfooter''': self.skipfooter,
										    '''doublequote''': self.doublequote,
										    '''memory_map''': self.memory_map,
										    '''float_precision''': self.float_precision,
										    '''chunksize''': self.chunksize,
										    '''encoding_errors''': self.encoding_errors,
										    '''on_bad_lines''': self.on_bad_lines,
										    '''date_format''': self.date_format,
										}

										# some kwargs must not be passed if they don't have a default value
										# some others are deprecated and we can also not pass them if they are the default value
										for pd_read_csv_parameter in _PANDAS_READ_CSV_NO_DEFAULT_PARAMETERS + _PANDAS_READ_CSV_DEPRECATED_PARAMETERS:
														if pd_read_csv_kwargs[pd_read_csv_parameter] == getattr(CsvConfig()				,    _a  ):
																		del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 2.0 new arguments
										if not (datasets.config.PANDAS_VERSION.major >= 2):
														for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_2_0_0_PARAMETERS:
																		del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 1.3 new arguments
										if not (datasets.config.PANDAS_VERSION.major >= 1 and datasets.config.PANDAS_VERSION.minor >= 3):
														for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_1_3_0_PARAMETERS:
																		del pd_read_csv_kwargs[pd_read_csv_parameter]

										return pd_read_csv_kwargs

class 						A__							(		datasets.ArrowBasedBuilder  ):
						UpperCAmelCase             =						CsvConfig




						def 							__UpperCamelCase				(       self					:      Optional[int]  )							->     int:


										"""simple docstring"""





										return datasets.DatasetInfo(features=self.config.features  )




						def 							__UpperCamelCase				(       self					:      Dict				,    _a					:      str  )							->     List[str]:


										"""simple docstring"""





										if not self.config.data_files:
														raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}"  )
										_SCREAMING_SNAKE_CASE			  =dl_manager.download_and_extract(self.config.data_files  )
										if isinstance(_a				,    (str, list, tuple)  ):
														_SCREAMING_SNAKE_CASE			  =data_files
														if isinstance(_a				,    _a  ):
																		_SCREAMING_SNAKE_CASE			  =[files]
														_SCREAMING_SNAKE_CASE			  =[dl_manager.iter_files(_a  ) for file in files]
														return [datasets.SplitGenerator(name=datasets.Split.TRAIN				,    gen_kwargs={'''files''': files}  )]
										_SCREAMING_SNAKE_CASE			  =[]
										for split_name, files in data_files.items():
														if isinstance(_a				,    _a  ):
																		_SCREAMING_SNAKE_CASE			  =[files]
														_SCREAMING_SNAKE_CASE			  =[dl_manager.iter_files(_a  ) for file in files]
														splits.append(datasets.SplitGenerator(name=_a				,    gen_kwargs={'''files''': files}  )  )
										return splits




						def 							__UpperCamelCase				(       self					:      Tuple				,    _a					:      pa.Table  )							->     pa.Table:


										"""simple docstring"""





										if self.config.features is not None:
														_SCREAMING_SNAKE_CASE			  =self.config.features.arrow_schema
														if all(not require_storage_cast(_a  ) for feature in self.config.features.values()  ):
																		# cheaper cast
																		_SCREAMING_SNAKE_CASE			  =pa.Table.from_arrays([pa_table[field.name] for field in schema]				,    schema=_a  )
														else:
																		# more expensive cast; allows str <-> int/float or str to Audio for example
																		_SCREAMING_SNAKE_CASE			  =table_cast(_a				,    _a  )
										return pa_table




						def 							__UpperCamelCase				(       self					:      str				,    _a					:      Union[str, Any]  )							->     int:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE			  =self.config.features.arrow_schema if self.config.features else None
										# dtype allows reading an int column as str
										_SCREAMING_SNAKE_CASE			  =(
										    {
										        name: dtype.to_pandas_dtype() if not require_storage_cast(_a  ) else object
										        for name, dtype, feature in zip(schema.names				,    schema.types				,    self.config.features.values()  )
										    }
										    if schema is not None
										    else None
										)
										for file_idx, file in enumerate(itertools.chain.from_iterable(_a  )  ):
														_SCREAMING_SNAKE_CASE			  =pd.read_csv(_a				,    iterator=_a				,    dtype=_a				,    **self.config.pd_read_csv_kwargs  )
														try:
																		for batch_idx, df in enumerate(_a  ):
																						_SCREAMING_SNAKE_CASE			  =pa.Table.from_pandas(_a  )
																						# Uncomment for debugging (will print the Arrow table size and elements)
																						# logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
																						# logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
																						yield (file_idx, batch_idx), self._cast_table(_a  )
														except ValueError as e:
																		logger.error(f"Failed to read file '{file}' with error {type(_a  )}: {e}"  )
																		raise