
'''simple docstring'''





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


a__						:      Any   				=				WebClient(token=os.environ["CI_SLACK_BOT_TOKEN"])





def 				snake_case							(						UpperCAmelCase		)->	int:







      """simple docstring"""
      __A						=	test_results.split(' '		)

      __A						=	0
      __A						=	0

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

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

      return failed, success, time_spent





def 				snake_case							(						UpperCAmelCase		)->	Union[str, Any]:







      """simple docstring"""
      __A						=	{}
      __A						=	None
      __A						=	False
      for line in failures_short_lines.split('\n'		):
            if re.search(R'_ \[doctest\]'					,     _lowercase		):
                  __A						=	True
                  __A						=	line.split(' '		)[2]
            elif in_error and not line.split(' '		)[0].isdigit():
                  __A						=	line
                  __A						=	False

      return failures


class        UpperCamelCase__     :






 def __init__(	self     :List[Any]		, _A     :str		, _A     :Dict	) ->	int:







       '''simple docstring'''



       __A						=	title

       __A						=	doc_test_results['''time_spent'''].split(','	)[0]
       __A						=	doc_test_results['''success''']
       __A						=	doc_test_results['''failures''']
       __A						=	self.n_success + self.n_failures

       # Failures and success of the modeling tests
       __A						=	doc_test_results






 @property
 def 		lowercase_  (	self     :Any	) ->	int:







       '''simple docstring'''



       __A						=	[self._time_spent]
       __A						=	0

       for time in time_spent:
             __A						=	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(UpperCamelCase__	) == 1:
                   __A						=	[0, 0, time_parts[0]]

             __A						=	int(time_parts[0]	), int(time_parts[1]	), float(time_parts[2]	)
             total_secs += hours * 3_600 + minutes * 60 + seconds

       __A						=	total_secs // 3_600, (total_secs % 3_600) // 60, total_secs % 60
       return F'{int(UpperCamelCase__	)}h{int(UpperCamelCase__	)}m{int(UpperCamelCase__	)}s'






 @property
 def 		lowercase_  (	self     :List[str]	) ->	Optional[int]:







       '''simple docstring'''



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






 @property
 def 		lowercase_  (	self     :List[str]	) ->	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 		lowercase_  (	self     :Union[str, Any]	) ->	Union[str, Any]:







       '''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 		lowercase_  (	self     :Dict	) ->	List[Any]:







       '''simple docstring'''



       __A						=	40
       __A						=	{k: v['''failed'''] for k, v in doc_test_results.items() if isinstance(UpperCamelCase__		, UpperCamelCase__	)}

       __A						=	''''''
       for category, failures in category_failures.items():
             if len(UpperCamelCase__	) == 0:
                   continue

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

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

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






 @property
 def 		lowercase_  (	self     :Optional[Any]	) ->	Optional[Any]:







       '''simple docstring'''



       __A						=	[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(UpperCamelCase__	)






 @staticmethod
 def 		lowercase_  (	) ->	List[Any]:







       '''simple docstring'''



       __A						=	[
           {
               '''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(UpperCamelCase__	)}	)	)

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






 def 		lowercase_  (	self     :int	) ->	Dict:







       '''simple docstring'''



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

       __A						=	F'{self.n_failures} failures out of {self.n_tests} tests,' if self.n_failures else '''All tests passed.'''

       __A						=	client.chat_postMessage(
           channel=os.environ['CI_SLACK_CHANNEL_ID_DAILY']		, blocks=self.payload		, text=UpperCamelCase__		, )






 def 		lowercase_  (	self     :Dict		, _A     :Optional[int]		, _A     :List[Any]		, _A     :Dict		, _A     :str	) ->	Union[str, Any]:







       '''simple docstring'''



       __A						=	''''''
       for key, value in failures.items():
             __A						=	value[:200] + ''' [Truncated]''' if len(UpperCamelCase__	) > 250 else value
             failures_text += F'*{key}*\n_{value}_\n\n'

       __A						=	job_name
       __A						=	{'''type''': '''section''', '''text''': {'''type''': '''mrkdwn''', '''text''': text}}

       if job_link is not None:
             __A						=	{
                 '''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 		lowercase_  (	self     :Dict	) ->	Tuple:







       '''simple docstring'''



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

       __A						=	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'	)

       __A						=	sorted(self.doc_test_results.items()		, key=lambda _A	: t[0]	)
       for job, job_result in sorted_dict:
             if len(job_result['failures']	):
                   __A						=	F'*Num failures* :{len(job_result["failed"]	)} \n'
                   __A						=	job_result['''failures''']
                   __A						=	self.get_reply_blocks(UpperCamelCase__		, UpperCamelCase__		, UpperCamelCase__		, text=UpperCamelCase__	)

                   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=UpperCamelCase__		, thread_ts=self.thread_ts['ts']		, )

                   time.sleep(1	)





def 				snake_case							(						)->	Tuple:







      """simple docstring"""
      __A						=	os.environ['''GITHUB_RUN_ID''']
      __A						=	f'https://api.github.com/repos/huggingface/transformers/actions/runs/{run_id}/jobs?per_page=100'
      __A						=	requests.get(_lowercase		).json()
      __A						=	{}

      try:
            jobs.update({job['name']: job['html_url'] for job in result['jobs']}		)
            __A						=	math.ceil((result['total_count'] - 1_0_0) / 1_0_0		)

            for i in range(_lowercase		):
                  __A						=	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.'					,     _lowercase		)

      return {}





def 				snake_case							(						UpperCAmelCase		)->	Tuple:







      """simple docstring"""
      __A						=	{}

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

      return _artifact





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







      """simple docstring"""


      class        UpperCamelCase__     :






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







             '''simple docstring'''



             __A						=	name
             __A						=	[]






       def __str__(	self     :str	) ->	str:







             '''simple docstring'''



             return self.name






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







             '''simple docstring'''



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

      __A						=	filter(os.path.isdir					,     os.listdir()		)
      for directory in directories:
            __A						=	directory
            if artifact_name not in _available_artifacts:
                  __A						=	Artifact(_lowercase		)

                  _available_artifacts[artifact_name].add_path(_lowercase		)

      return _available_artifacts


if __name__ == "__main__":
 a__						:      List[Any]   				=				get_job_links()
 a__						:      List[str]   				=				retrieve_available_artifacts()

 a__						:      str   				=				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'
 a__						:      List[Any]   				=				{
     v: {
         'failed': [],
         'failures': {},
     }
     for v in docs.values()
 }

 # Link to the GitHub Action job
 a__						:      str   				=				github_actions_job_links.get("run_doctests")

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

  a__						:      Optional[Any]   				=				extract_first_line_failure(artifact["failures_short"])
  for line in artifact["summary_short"].split("\n"):
   if re.search("FAILED", line):
    a__						:      Tuple   				=				line.replace("FAILED ", "")
    a__						:      str   				=				line.split()[0].replace("\n", "")

    if "::" in line:
     a__						:      List[Any]   				=				line.split("::")
    else:
     a__						:      Optional[Any]   				=				line, line

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

      a__						:      int   				=				all_failures[test] if test in all_failures else 'N/A'
      a__						:      List[str]   				=				failure
      break

 a__						:      Union[str, Any]   				=				Message("🤗 Results of the doc tests.", doc_test_results)
 message.post()
 message.post_reply()







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__UpperCamelCase		:       Any									=     {'configuration_mbart': ['MBART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MBartConfig', 'MBartOnnxConfig']}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase		:       List[str]									=     ['MBartTokenizer']

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase		:       Dict									=     ['MBartTokenizerFast']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase		:       List[str]									=     [
					    'MBART_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'MBartForCausalLM',
					    'MBartForConditionalGeneration',
					    'MBartForQuestionAnswering',
					    'MBartForSequenceClassification',
					    'MBartModel',
					    'MBartPreTrainedModel',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase		:       str									=     [
					    'TFMBartForConditionalGeneration',
					    'TFMBartModel',
					    'TFMBartPreTrainedModel',
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase		:       List[str]									=     [
					    'FlaxMBartForConditionalGeneration',
					    'FlaxMBartForQuestionAnswering',
					    'FlaxMBartForSequenceClassification',
					    'FlaxMBartModel',
					    'FlaxMBartPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_mbart import MBART_PRETRAINED_CONFIG_ARCHIVE_MAP, MBartConfig, MBartOnnxConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_mbart import MBartTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_mbart_fast import MBartTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_mbart import (
										    MBART_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MBartForCausalLM,
										    MBartForConditionalGeneration,
										    MBartForQuestionAnswering,
										    MBartForSequenceClassification,
										    MBartModel,
										    MBartPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_mbart import TFMBartForConditionalGeneration, TFMBartModel, TFMBartPreTrainedModel

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_mbart import (
										    FlaxMBartForConditionalGeneration,
										    FlaxMBartForQuestionAnswering,
										    FlaxMBartForSequenceClassification,
										    FlaxMBartModel,
										    FlaxMBartPreTrainedModel,
										)

else:
					import sys

					__UpperCamelCase		:       int									=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





