






'''simple docstring'''


import json
import os
from datetime import date
from pathlib import Path

from tabulate import DataRow, TableFormat, tabulate


lowerCamelCase_				: Dict    	=							TableFormat(
    lineabove=None,
    linebelowheader=None,
    linebetweenrows=None,
    linebelow=None,
    headerrow=DataRow('''''', '''|''', '''|'''),
    datarow=DataRow('''''', '''|''', '''|'''),
    padding=1,
    with_header_hide=None,
)


lowerCamelCase_				: Tuple    	=							[]
lowerCamelCase_				: Optional[int]    	=							[]

lowerCamelCase_				: List[str]    	=							{'''type''': '''section''', '''text''': {'''type''': '''plain_text''', '''text''': '''No failed tests! 🤗''', '''emoji''': True}}

lowerCamelCase_				: Optional[Any]    	=							[
    {
        '''type''': '''header''',
        '''text''': {
            '''type''': '''plain_text''',
            '''text''': f"""🤗 Accelerate nightly {os.environ.get("TEST_TYPE", "")} test results""",
            '''emoji''': True,
        },
    }
]

lowerCamelCase_				: Tuple    	=							0
for log in Path().glob('''*.log'''):
					lowerCamelCase_				: str    	=							0
					with open(log, '''r''') as f:
										for line in f:
															lowerCamelCase_				: Dict    	=							json.loads(line)
															if line.get('''nodeid''', '''''') != "":
																				lowerCamelCase_				: Any    	=							line['''nodeid''']
																				if line.get('''duration''', None) is not None:
																									lowerCamelCase_				: Any    	=							f"""{line["duration"]:.4f}"""
																									if line.get('''outcome''', '''''') == "failed":
																														section_num_failed += 1
																														failed.append([test, duration, log.name.split('''_''')[0]])
																														total_num_failed += 1
					group_info.append([str(log), section_num_failed, failed])
					lowerCamelCase_				: List[Any]    	=							[]
					log.unlink()

lowerCamelCase_				: str    	=							''''''
lowerCamelCase_				: Dict    	=							[]
if total_num_failed > 0:
					for name, num_failed, failed_tests in group_info:
										if num_failed > 0:
															if num_failed == 1:
																				message += f"*{name[1:]}: {num_failed} failed test*\n"
															else:
																				message += f"*{name[1:]}: {num_failed} failed tests*\n"
															lowerCamelCase_				: Any    	=							[]
															lowerCamelCase_				: Tuple    	=							{}
															for test in failed_tests:
																				lowerCamelCase_				: Optional[int]    	=							test[0].split('''::''')
																				lowerCamelCase_				: List[Any]    	=							data[0].split('''/''')[-1]
																				if data[0] not in filesafailed:
																									lowerCamelCase_				: str    	=							[data[1:]]
																				else:
																									filesafailed[data[0]] += [data[1:]]
																				failed_table.append(data)

															lowerCamelCase_				: List[Any]    	=							[test[0] for test in failed_table]
															lowerCamelCase_				: List[str]    	=							list(set(files))
															# Count number of instances in failed_tests
															lowerCamelCase_				: Tuple    	=							[]
															for file in individual_files:
																				table.append([file, len(filesafailed[file])])

															lowerCamelCase_				: List[Any]    	=							tabulate(
															    table,
															    headers=['''Test Location''', '''Num Failed'''],
															    tablefmt=hf_table_format,
															    stralign='''right''',
															)
															message += f"\n```\n{failed_table}\n```"
															all_filesafailed.append(filesafailed)
					if len(message) > 3000:
										lowerCamelCase_				: Tuple    	=							'''Too many failed tests, please see the full report in the Action results.'''
										lowerCamelCase_				: Optional[Any]    	=							len(err) + 10
										lowerCamelCase_				: Union[str, Any]    	=							message[: 3000 - offset] + f"""\n...\n```\n{err}"""
					print(f"""### {message}""")
else:
					lowerCamelCase_				: Union[str, Any]    	=							'''No failed tests! 🤗'''
					print(f"""## {message}""")
					payload.append(no_error_payload)

if os.environ.get('''TEST_TYPE''', '''''') != "":
					from slack_sdk import WebClient

					lowerCamelCase_				: Tuple    	=							WebClient(token=os.environ['''SLACK_API_TOKEN'''])
					if message != "No failed tests! 🤗":
										lowerCamelCase_				: Dict    	=							{
										    '''type''': '''section''',
										    '''text''': {
										        '''type''': '''mrkdwn''',
										        '''text''': message,
										    },
										}
										payload.append(md_report)
										lowerCamelCase_				: List[Any]    	=							{
										    '''type''': '''section''',
										    '''text''': {
										        '''type''': '''mrkdwn''',
										        '''text''': '''*For more details:*''',
										    },
										    '''accessory''': {
										        '''type''': '''button''',
										        '''text''': {
										            '''type''': '''plain_text''',
										            '''text''': '''Check Action results''',
										            '''emoji''': True,
										        },
										        '''url''': f"""https://github.com/{os.environ["GITHUB_REPOSITORY"]}/actions/runs/{os.environ["GITHUB_RUN_ID"]}""",
										    },
										}
										payload.append(action_button)
										lowerCamelCase_				: List[Any]    	=							{
										    '''type''': '''context''',
										    '''elements''': [
										        {
										            '''type''': '''plain_text''',
										            '''text''': f"""Nightly {os.environ.get("TEST_TYPE")} test results for {date.today()}""",
										        }
										    ],
										}
										payload.append(date_report)
					lowerCamelCase_				: Union[str, Any]    	=							client.chat_postMessage(channel='''#accelerate-ci-daily''', text=message, blocks=payload)
					lowerCamelCase_				: List[str]    	=							response.data['''ts''']
					for failed_file in all_filesafailed:
										for test_location, test_failures in failed_file.items():
															# Keep only the first instance of the test name
															lowerCamelCase_				: List[Any]    	=							''''''
															for i, row in enumerate(test_failures):
																				if row[0] != test_class:
																									lowerCamelCase_				: List[str]    	=							row[0]
																				else:
																									lowerCamelCase_				: Tuple    	=							''''''

															lowerCamelCase_				: Any    	=							{
															    '''type''': '''section''',
															    '''text''': {
															        '''type''': '''mrkdwn''',
															        '''text''': f"""Test location: {test_location}\n```\n{tabulate(test_failures, headers=["Class", "Test"], tablefmt=hf_table_format, stralign="right")}\n```""",
															    },
															}

															client.chat_postMessage(
															    channel='''#accelerate-ci-daily''',
															    thread_ts=ts,
															    blocks=[payload],
															)








'''simple docstring'''


from collections import Counter
from pathlib import Path
from typing import Optional, Tuple

import yaml
class    _SCREAMING_SNAKE_CASE							(		yaml.SafeLoader	):


			'''simple docstring'''





			def 				A      (   self							:						List[str] ,      lowercase							:						List[Any]			)							->    int:

									'''simple docstring'''







									UpperCamelCase__         = [self.constructed_objects[key_node] for key_node, _ in node.value]
									UpperCamelCase__         = [tuple(lowercase			) if isinstance(lowercase ,      lowercase			) else key for key in keys]
									UpperCamelCase__         = Counter(lowercase			)
									UpperCamelCase__         = [key for key in counter if counter[key] > 1]
									if duplicate_keys:
															raise TypeError(f"Got duplicate yaml keys: {duplicate_keys}"			)







			def 				A      (   self							:						List[str] ,      lowercase							:						int ,      lowercase							:						str=False			)							->    Any:

									'''simple docstring'''







									UpperCamelCase__         = super().construct_mapping(lowercase ,      deep=lowercase			)
									self._check_no_duplicates_on_constructed_node(lowercase			)
									return mapping







def 	__magic_name__( _A					):
						'''simple docstring'''





						UpperCamelCase__         = list(readme_content.splitlines()					)
						if full_content and full_content[0] == "---" and "---" in full_content[1:]:
												UpperCamelCase__         = full_content[1:].index("""---"""					) + 1
												UpperCamelCase__         = """\n""".join(full_content[1:sep_idx]					)
												return yamlblock, "\n".join(full_content[sep_idx + 1 :]					)

						return None, "\n".join(_A					)
class    _SCREAMING_SNAKE_CASE							(		SCREAMING_SNAKE_CASE	):


			'''simple docstring'''





			__a							:							Tuple					     =					{"train_eval_index"}  # train-eval-index in the YAML metadata






			@classmethod
			def 				A      (   cls							:						int ,      lowercase							:						Path			)							->    "DatasetMetadata":

									'''simple docstring'''







									with open(lowercase ,      encoding="""utf-8"""			) as readme_file:
															UpperCamelCase__    ,   UpperCamelCase__         = _split_yaml_from_readme(readme_file.read()			)
									if yaml_string is not None:
															return cls.from_yaml_string(lowercase			)
									else:
															return cls()






			def 				A      (   self							:						int ,      lowercase							:						Path			)							->    Dict:

									'''simple docstring'''







									if path.exists():
															with open(lowercase ,      encoding="""utf-8"""			) as readme_file:
																					UpperCamelCase__         = readme_file.read()
									else:
															UpperCamelCase__         = None
									UpperCamelCase__         = self._to_readme(lowercase			)
									with open(lowercase ,      """w""" ,      encoding="""utf-8"""			) as readme_file:
															readme_file.write(lowercase			)






			def 				A      (   self							:						Any ,      lowercase							:						Optional[str] = None			)							->    str:

									'''simple docstring'''







									if readme_content is not None:
															UpperCamelCase__    ,   UpperCamelCase__         = _split_yaml_from_readme(lowercase			)
															UpperCamelCase__         = """---\n""" + self.to_yaml_string() + """---\n""" + content
									else:
															UpperCamelCase__         = """---\n""" + self.to_yaml_string() + """---\n"""
									return full_content






			@classmethod
			def 				A      (   cls							:						Tuple ,      lowercase							:						str			)							->    "DatasetMetadata":

									'''simple docstring'''







									UpperCamelCase__         = yaml.load(lowercase ,      Loader=_NoDuplicateSafeLoader			) or {}

									# Convert the YAML keys to DatasetMetadata fields
									UpperCamelCase__         = {
									    (key.replace("""-""" ,      """_"""			) if key.replace("""-""" ,      """_"""			) in cls._FIELDS_WITH_DASHES else key): value
									    for key, value in metadata_dict.items()
									}
									return cls(**lowercase			)







			def 				A      (   self							:						Dict			)							->    str:

									'''simple docstring'''







									return yaml.safe_dump(
									    {
									        (key.replace("""_""" ,      """-"""			) if key in self._FIELDS_WITH_DASHES else key): value
									        for key, value in self.items()
									    } ,      sort_keys=lowercase ,      allow_unicode=lowercase ,      encoding="""utf-8""" ,      ).decode("""utf-8"""			)
lowerCamelCase_				: str    	=							{
    '''image-classification''': [],
    '''translation''': [],
    '''image-segmentation''': [],
    '''fill-mask''': [],
    '''automatic-speech-recognition''': [],
    '''token-classification''': [],
    '''sentence-similarity''': [],
    '''audio-classification''': [],
    '''question-answering''': [],
    '''summarization''': [],
    '''zero-shot-classification''': [],
    '''table-to-text''': [],
    '''feature-extraction''': [],
    '''other''': [],
    '''multiple-choice''': [],
    '''text-classification''': [],
    '''text-to-image''': [],
    '''text2text-generation''': [],
    '''zero-shot-image-classification''': [],
    '''tabular-classification''': [],
    '''tabular-regression''': [],
    '''image-to-image''': [],
    '''tabular-to-text''': [],
    '''unconditional-image-generation''': [],
    '''text-retrieval''': [],
    '''text-to-speech''': [],
    '''object-detection''': [],
    '''audio-to-audio''': [],
    '''text-generation''': [],
    '''conversational''': [],
    '''table-question-answering''': [],
    '''visual-question-answering''': [],
    '''image-to-text''': [],
    '''reinforcement-learning''': [],
    '''voice-activity-detection''': [],
    '''time-series-forecasting''': [],
    '''document-question-answering''': [],
}


if __name__ == "__main__":
					from argparse import ArgumentParser

					lowerCamelCase_				: Tuple    	=							ArgumentParser(usage='''Validate the yaml metadata block of a README.md file.''')
					ap.add_argument('''readme_filepath''')
					lowerCamelCase_				: str    	=							ap.parse_args()

					lowerCamelCase_				: List[str]    	=							Path(args.readme_filepath)
					lowerCamelCase_				: Tuple    	=							DatasetMetadata.from_readme(readme_filepath)
					print(dataset_metadata)
					dataset_metadata.to_readme(readme_filepath)
