






import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict

import requests
from slack_sdk import WebClient


SCREAMING_SNAKE_CASE 							=						WebClient(token=os.environ['CI_SLACK_BOT_TOKEN'])

def      _lowerCamelCase	(						__A    :							Optional[Any] )      ->					int:
    _UpperCAmelCase				:      Optional[int]			  =				test_results.split(''' ''' )

    _UpperCAmelCase				:      Optional[int]			  =				0
    _UpperCAmelCase				:      Union[str, Any]			  =				0

    # When the output is short enough, the output is surrounded by = signs: "== OUTPUT =="
    # When it is too long, those signs are not present.
    _UpperCAmelCase				:      Tuple			  =				expressions[-2] if '''=''' in expressions[-1] else expressions[-1]

    for i, expression in enumerate(__A ):
        if "failed" in expression:
            failed += int(expressions[i - 1] )
        if "passed" in expression:
            success += int(expressions[i - 1] )

    return failed, success, time_spent

def      _lowerCamelCase	(						__A    :							List[str] )      ->					int:
    _UpperCAmelCase				:      Optional[Any]			  =				{}
    _UpperCAmelCase				:      int			  =				None
    _UpperCAmelCase				:      Any			  =				False
    for line in failures_short_lines.split('''\n''' ):
        if re.search(r'''_ \[doctest\]'''		,		__A ):
            _UpperCAmelCase				:      Tuple			  =				True
            _UpperCAmelCase				:      Optional[Any]			  =				line.split(''' ''' )[2]
        elif in_error and not line.split(''' ''' )[0].isdigit():
            _UpperCAmelCase				:      int			  =				line
            _UpperCAmelCase				:      Optional[Any]			  =				False

    return failures
class 							A_    :






 '''simple docstring'''




 def __init__(	self							,  _A							,  _A) ->		Optional[int]:

     """simple docstring"""



     _UpperCAmelCase				:      Tuple			  =				title

     _UpperCAmelCase				:      List[str]			  =				doc_test_results['''time_spent'''].split(''',''')[0]
     _UpperCAmelCase				:      List[Any]			  =				doc_test_results['''success''']
     _UpperCAmelCase				:      Optional[Any]			  =				doc_test_results['''failures''']
     _UpperCAmelCase				:      Tuple			  =				self.n_success + self.n_failures

     # Failures and success of the modeling tests
     _UpperCAmelCase				:      Optional[int]			  =				doc_test_results


 @property
 def  snake_case__				(	self) ->		str:

     """simple docstring"""



     _UpperCAmelCase				:      List[str]			  =				[self._time_spent]
     _UpperCAmelCase				:      Dict			  =				0

     for time in time_spent:
         _UpperCAmelCase				:      Optional[int]			  =				time.split(''':''')

         # Time can be formatted as xx:xx:xx, as .xx, or as x.xx if the time spent was less than a minute.
         if len(_A) == 1:
             _UpperCAmelCase				:      List[Any]			  =				[0, 0, time_parts[0]]

         _UpperCAmelCase  , _UpperCAmelCase  , _UpperCAmelCase				:      Optional[int]			  =				int(time_parts[0]), int(time_parts[1]), float(time_parts[2])
         total_secs += hours * 3600 + minutes * 60 + seconds

     _UpperCAmelCase  , _UpperCAmelCase  , _UpperCAmelCase				:      Dict			  =				total_secs // 3600, (total_secs % 3600) // 60, total_secs % 60
     return f'''{int(_A)}h{int(_A)}m{int(_A)}s'''


 @property
 def  snake_case__				(	self) ->		Dict:

     """simple docstring"""



     return {"type": "header", "text": {"type": "plain_text", "text": self.title}}


 @property
 def  snake_case__				(	self) ->		Dict:

     """simple docstring"""



     return {
         "type": "section",
         "text": {
             "type": "plain_text",
             "text": f'''🌞 There were no failures: all {self.n_tests} tests passed. The suite ran in {self.time}.''',
             "emoji": True,
         },
         "accessory": {
             "type": "button",
             "text": {"type": "plain_text", "text": "Check Action results", "emoji": True},
             "url": f'''https://github.com/huggingface/transformers/actions/runs/{os.environ['GITHUB_RUN_ID']}''',
         },
     }


 @property
 def  snake_case__				(	self) ->		Dict:

     """simple docstring"""



     return {
         "type": "section",
         "text": {
             "type": "plain_text",
             "text": (
                 f'''There were {self.n_failures} failures, out of {self.n_tests} tests.\nThe suite ran in'''
                 f''' {self.time}.'''
             ),
             "emoji": True,
         },
         "accessory": {
             "type": "button",
             "text": {"type": "plain_text", "text": "Check Action results", "emoji": True},
             "url": f'''https://github.com/huggingface/transformers/actions/runs/{os.environ['GITHUB_RUN_ID']}''',
         },
     }


 @property
 def  snake_case__				(	self) ->		Dict:

     """simple docstring"""



     _UpperCAmelCase				:      List[str]			  =				40
     _UpperCAmelCase				:      List[str]			  =				{k: v['''failed'''] for k, v in doc_test_results.items() if isinstance(_A							,  _A)}

     _UpperCAmelCase				:      List[Any]			  =				''''''
     for category, failures in category_failures.items():
         if len(_A) == 0:
             continue

         if report != "":
             report += "\n\n"

         report += f'''*{category} failures*:'''.ljust(line_length // 2).rjust(line_length // 2) + "\n"
         report += "`"
         report += "`\n`".join(_A)
         report += "`"

     return {
         "type": "section",
         "text": {
             "type": "mrkdwn",
             "text": f'''The following examples had failures:\n\n\n{report}\n''',
         },
     }


 @property
 def  snake_case__				(	self) ->		str:

     """simple docstring"""



     _UpperCAmelCase				:      int			  =				[self.header]

     if self.n_failures > 0:
         blocks.append(self.failures)

     if self.n_failures > 0:
         blocks.extend([self.category_failures])

     if self.n_failures == 0:
         blocks.append(self.no_failures)

     return json.dumps(_A)


 @staticmethod
 def  snake_case__				(	) ->		List[str]:

     """simple docstring"""



     _UpperCAmelCase				:      Union[str, Any]			  =				[
         {
             '''type''': '''section''',
             '''text''': {
                 '''type''': '''plain_text''',
                 '''text''': '''There was an issue running the tests.''',
             },
             '''accessory''': {
                 '''type''': '''button''',
                 '''text''': {'''type''': '''plain_text''', '''text''': '''Check Action results''', '''emoji''': True},
                 '''url''': f'''https://github.com/huggingface/transformers/actions/runs/{os.environ['GITHUB_RUN_ID']}''',
             },
         }
     ]

     print('''Sending the following payload''')
     print(json.dumps({'''blocks''': json.loads(_A)}))

     client.chat_postMessage(
         channel=os.environ['''CI_SLACK_CHANNEL_ID_DAILY''']							,  text='''There was an issue running the tests.'''							,  blocks=_A							,  )


 def  snake_case__				(	self) ->		str:

     """simple docstring"""



     print('''Sending the following payload''')
     print(json.dumps({'''blocks''': json.loads(self.payload)}))

     _UpperCAmelCase				:      str			  =				f'''{self.n_failures} failures out of {self.n_tests} tests,''' if self.n_failures else '''All tests passed.'''

     _UpperCAmelCase				:      Optional[Any]			  =				client.chat_postMessage(
         channel=os.environ['''CI_SLACK_CHANNEL_ID_DAILY''']							,  blocks=self.payload							,  text=_A							,  )


 def  snake_case__				(	self							,  _A							,  _A							,  _A							,  _A) ->		Dict:

     """simple docstring"""



     _UpperCAmelCase				:      Optional[int]			  =				''''''
     for key, value in failures.items():
         _UpperCAmelCase				:      str			  =				value[:200] + ''' [Truncated]''' if len(_A) > 250 else value
         failures_text += f'''*{key}*\n_{value}_\n\n'''

     _UpperCAmelCase				:      Optional[Any]			  =				job_name
     _UpperCAmelCase				:      Any			  =				{'''type''': '''section''', '''text''': {'''type''': '''mrkdwn''', '''text''': text}}

     if job_link is not None:
         _UpperCAmelCase				:      List[Any]			  =				{
             '''type''': '''button''',
             '''text''': {'''type''': '''plain_text''', '''text''': '''GitHub Action job''', '''emoji''': True},
             '''url''': job_link,
         }

     return [
         {"type": "header", "text": {"type": "plain_text", "text": title.upper(), "emoji": True}},
         content,
         {"type": "section", "text": {"type": "mrkdwn", "text": failures_text}},
     ]


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

     """simple docstring"""



     if self.thread_ts is None:
         raise ValueError('''Can only post reply if a post has been made.''')

     _UpperCAmelCase				:      Tuple			  =				self.doc_test_results.pop('''job_link''')
     self.doc_test_results.pop('''failures''')
     self.doc_test_results.pop('''success''')
     self.doc_test_results.pop('''time_spent''')

     _UpperCAmelCase				:      Any			  =				sorted(self.doc_test_results.items()							,  key=lambda _A: t[0])
     for job, job_result in sorted_dict:
         if len(job_result['''failures''']):
             _UpperCAmelCase				:      Dict			  =				f'''*Num failures* :{len(job_result['failed'])} \n'''
             _UpperCAmelCase				:      Tuple			  =				job_result['''failures''']
             _UpperCAmelCase				:      Dict			  =				self.get_reply_blocks(_A							,  _A							,  _A							,  text=_A)

             print('''Sending the following reply''')
             print(json.dumps({'''blocks''': blocks}))

             client.chat_postMessage(
                 channel=os.environ['''CI_SLACK_CHANNEL_ID_DAILY''']							,  text=f'''Results for {job}'''							,  blocks=_A							,  thread_ts=self.thread_ts['''ts''']							,  )

             time.sleep(1)



def      _lowerCamelCase	(						)      ->					str:
    _UpperCAmelCase				:      Any			  =				os.environ['''GITHUB_RUN_ID''']
    _UpperCAmelCase				:      Any			  =				f'''https://api.github.com/repos/huggingface/transformers/actions/runs/{run_id}/jobs?per_page=100'''
    _UpperCAmelCase				:      Optional[int]			  =				requests.get(__A ).json()
    _UpperCAmelCase				:      Optional[int]			  =				{}

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

        for i in range(__A ):
            _UpperCAmelCase				:      int			  =				requests.get(url + f'''&page={i + 2}''' ).json()
            jobs.update({job['''name''']: job['''html_url'''] for job in result['''jobs''']} )

        return jobs
    except Exception as e:
        print('''Unknown error, could not fetch links.'''		,		__A )

    return {}

def      _lowerCamelCase	(						__A    :							str )      ->					Tuple:
    _UpperCAmelCase				:      Optional[Any]			  =				{}

    if os.path.exists(__A ):
        _UpperCAmelCase				:      Optional[int]			  =				os.listdir(__A )
        for file in files:
            try:
                with open(os.path.join(__A		,		__A )		,		encoding='''utf-8''' ) as f:
                    _UpperCAmelCase				:      Tuple			  =				f.read()
            except UnicodeDecodeError as e:
                raise ValueError(f'''Could not open {os.path.join(__A		,		__A )}.''' ) from e

    return _artifact

def      _lowerCamelCase	(						)      ->					List[str]:
    class 							A_    :






     '''simple docstring'''




     def __init__(	self							,  _A) ->		int:

         """simple docstring"""



         _UpperCAmelCase				:      List[Any]			  =				name
         _UpperCAmelCase				:      Union[str, Any]			  =				[]


     def __str__(	self) ->		int:

         """simple docstring"""



         return self.name


     def  snake_case__				(	self							,  _A) ->		int:

         """simple docstring"""



         self.paths.append({'''name''': self.name, '''path''': path})



    _UpperCAmelCase				:      Dict[str, Artifact]			  =				{}

    _UpperCAmelCase				:      Dict			  =				filter(os.path.isdir		,		os.listdir() )
    for directory in directories:
        _UpperCAmelCase				:      List[str]			  =				directory
        if artifact_name not in _available_artifacts:
            _UpperCAmelCase				:      Optional[int]			  =				Artifact(__A )

            _available_artifacts[artifact_name].add_path(__A )

    return _available_artifacts


if __name__ == "__main__":
  SCREAMING_SNAKE_CASE 							=						get_job_links()
  SCREAMING_SNAKE_CASE 							=						retrieve_available_artifacts()

  SCREAMING_SNAKE_CASE 							=						collections.OrderedDict(
      [
          ('*.py', 'API Examples'),
          ('*.md', 'MD Examples'),
      ]
  )

  # This dict will contain all the information relative to each doc test category:
  # - failed: list of failed tests
  # - failures: dict in the format 'test': 'error_message'
  SCREAMING_SNAKE_CASE 							=						{
      v: {
          'failed': [],
          'failures': {},
      }
      for v in docs.values()
  }

  # Link to the GitHub Action job
  SCREAMING_SNAKE_CASE 							=						github_actions_job_links.get('run_doctests')

  SCREAMING_SNAKE_CASE 							=						available_artifacts['doc_tests_gpu_test_reports'].paths[0]
  SCREAMING_SNAKE_CASE 							=						retrieve_artifact(artifact_path['name'])
  if "stats" in artifact:
    SCREAMING_SNAKE_CASE							,			SCREAMING_SNAKE_CASE							,			SCREAMING_SNAKE_CASE 							=						handle_test_results(artifact['stats'])
    SCREAMING_SNAKE_CASE 							=						failed
    SCREAMING_SNAKE_CASE 							=						success
    SCREAMING_SNAKE_CASE 							=						time_spent[1:-1] + ', '

    SCREAMING_SNAKE_CASE 							=						extract_first_line_failure(artifact['failures_short'])
    for line in artifact["summary_short"].split('\n'):
      if re.search('FAILED', line):
        SCREAMING_SNAKE_CASE 							=						line.replace('FAILED ', '')
        SCREAMING_SNAKE_CASE 							=						line.split()[0].replace('\n', '')

        if "::" in line:
          SCREAMING_SNAKE_CASE							,			SCREAMING_SNAKE_CASE 							=						line.split('::')
        else:
          SCREAMING_SNAKE_CASE							,			SCREAMING_SNAKE_CASE 							=						line, line

        for file_regex in docs.keys():
          if fnmatch(file_path, file_regex):
            SCREAMING_SNAKE_CASE 							=						docs[file_regex]
            doc_test_results[category]["failed"].append(test)

            SCREAMING_SNAKE_CASE 							=						all_failures[test] if test in all_failures else 'N/A'
            SCREAMING_SNAKE_CASE 							=						failure
            break

  SCREAMING_SNAKE_CASE 							=						Message('🤗 Results of the doc tests.', doc_test_results)
  message.post()
  message.post_reply()












import math_equivalence  # From: git+https://github.com/hendrycks/math.git

import datasets


SCREAMING_SNAKE_CASE 							=						'\\n@article{hendrycksmath2021,\n  title={Measuring Mathematical Problem Solving With the MATH Dataset},\n  author={Dan Hendrycks\n    and Collin Burns\n    and Saurav Kadavath\n    and Akul Arora\n    and Steven Basart\n    and Eric Tang\n    and Dawn Song\n    and Jacob Steinhardt},\n  journal={arXiv preprint arXiv:2103.03874},\n  year={2021}\n}\n'


SCREAMING_SNAKE_CASE 							=						'\\nThis metric is used to assess performance on the Mathematics Aptitude Test of Heuristics (MATH) dataset.\nIt first canonicalizes the inputs (e.g., converting "1/2" to "\\frac{1}{2}") and then computes accuracy.\n'


SCREAMING_SNAKE_CASE 							=						R'\nCalculates accuracy after canonicalizing inputs.\n\nArgs:\n    predictions: list of predictions to score. Each prediction\n        is a string that contains natural language and LaTex.\n    references: list of reference for each prediction. Each\n        reference is a string that contains natural language\n        and LaTex.\nReturns:\n    accuracy: accuracy after canonicalizing inputs\n        (e.g., converting "1/2" to "\\frac{1}{2}")\n\nExamples:\n    >>> metric = datasets.load_metric("competition_math")\n    >>> results = metric.compute(references=["\\frac{1}{2}"], predictions=["1/2"])\n    >>> print(results)\n    {\'accuracy\': 1.0}\n'
@datasets.utils.file_utils.add_end_docstrings(_DESCRIPTION ,   _KWARGS_DESCRIPTION			)
class 							A_    (						datasets.Metric			):






 '''simple docstring'''




 def  snake_case__				(	self) ->		Optional[Any]:

     """simple docstring"""



     return datasets.MetricInfo(
         description=_DESCRIPTION							,  citation=_CITATION							,  inputs_description=_KWARGS_DESCRIPTION							,  features=datasets.Features(
             {
                 '''predictions''': datasets.Value('''string'''),
                 '''references''': datasets.Value('''string'''),
             })							,  homepage='''https://github.com/hendrycks/math'''							,  codebase_urls=['''https://github.com/hendrycks/math''']							,  )


 def  snake_case__				(	self							,  _A							,  _A) ->		Tuple:

     """simple docstring"""



     _UpperCAmelCase				:      Tuple			  =				0.0
     for i, j in zip(_A							,  _A):
         n_correct += 1.0 if math_equivalence.is_equiv(_A							,  _A) else 0.0
     _UpperCAmelCase				:      Tuple			  =				n_correct / len(_A)
     return {
         "accuracy": accuracy,
     }




