






"""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


UpperCamelCase							       =  WebClient(token=os.environ["""CI_SLACK_BOT_TOKEN"""])






def        lowerCAmelCase (      UpperCamelCase_:							Any					)       ->							List[str]:







  '''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(_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 (      UpperCamelCase_:							List[Any]					)       ->							int:







  '''simple docstring'''







  _a							=	{}
  _a							=	None
  _a							=	False
  for line in failures_short_lines.split("\n"					):
    if re.search(r"_ \[doctest\]"     , _A					):
      _a							=	True
      _a							=	line.split(" "					)[2]
    elif in_error and not line.split(" "					)[0].isdigit():
      _a							=	line
      _a							=	False

  return failures




class    lowercase_    :






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







        '''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 			lowerCamelCase__    (    self	)	->str:







        '''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			,	_a			,	_a							=	int(time_parts[0]	), int(time_parts[1]	), float(time_parts[2]	)
          total_secs += hours * 3_6_0_0 + minutes * 6_0 + seconds

        _a			,	_a			,	_a							=	total_secs // 3_6_0_0, (total_secs % 3_6_0_0) // 6_0, total_secs % 6_0
        return f'''{int(__UpperCamelCase	)}h{int(__UpperCamelCase	)}m{int(__UpperCamelCase	)}s'''






      @property
      def 			lowerCamelCase__    (    self	)	->Dict:







        '''simple docstring'''


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






      @property
      def 			lowerCamelCase__    (    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 			lowerCamelCase__    (    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 			lowerCamelCase__    (    self	)	->Dict:







        '''simple docstring'''


        _a							=	4_0
        _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 			lowerCamelCase__    (    self	)	->str:







        '''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 			lowerCamelCase__    (    )	->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 			lowerCamelCase__    (    self	)	->Optional[Any]:







        '''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 			lowerCamelCase__    (    self     ,     a_     ,     a_     ,     a_     ,     a_	)	->str:







        '''simple docstring'''


        _a							=	""
        for key, value in failures.items():
          _a							=	value[:2_0_0] + " [Truncated]" if len(__UpperCamelCase	) > 2_5_0 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 			lowerCamelCase__    (    self	)	->Optional[Any]:







        '''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        lowerCAmelCase (      )       ->							List[str]:







  '''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(_A					).json()
  _a							=	{}

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

    for i in range(_A					):
      _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."     , _A					)

  return {}






def        lowerCAmelCase (      UpperCamelCase_:							Optional[int]					)       ->							Optional[int]:







  '''simple docstring'''







  _a							=	{}

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

  return _artifact






def        lowerCAmelCase (      )       ->							int:







  '''simple docstring'''







  class    lowercase_    :






        def __init__(    self     ,     a_	)	->Tuple:







          '''simple docstring'''


          _a							=	name
          _a							=	[]






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







          '''simple docstring'''


          return self.name






        def 			lowerCamelCase__    (    self     ,     a_	)	->int:







          '''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(_A					)

      _available_artifacts[artifact_name].add_path(_A					)

  return _available_artifacts


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

     UpperCamelCase							       =  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'
     UpperCamelCase							       =  {
         v: {
             '''failed''': [],
             '''failures''': {},
         }
         for v in docs.values()
     }

     # Link to the GitHub Action job
     UpperCamelCase							       =  github_actions_job_links.get("""run_doctests""")

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

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

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

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

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

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










"""simple docstring"""




import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize






def        lowerCAmelCase (      UpperCamelCase_:							ndarray					)       ->							float:







  '''simple docstring'''







  return np.dot(UpperCamelCase_     , UpperCamelCase_					)




class    lowercase_    :






      def __init__(    self     ,     *,
          a_ = np.inf     ,     a_ = "linear"     ,     a_ = 0.0     ,     )	->None:







        '''simple docstring'''


        _a							=	regularization
        _a							=	gamma
        if kernel == "linear":
          _a							=	self.__linear
        elif kernel == "rbf":
          if self.gamma == 0:
            raise ValueError("rbf kernel requires gamma"	)
          if not isinstance(self.gamma     ,     (float, int)	):
            raise ValueError("gamma must be float or int"	)
          if not self.gamma > 0:
            raise ValueError("gamma must be > 0"	)
          _a							=	self.__rbf
          # in the future, there could be a default value like in sklearn
          # sklear: def_gamma = 1/(n_features * X.var()) (wiki)
          # previously it was 1/(n_features)
        else:
          _a							=	f'''Unknown kernel: {kernel}'''
          raise ValueError(a_	)






      def 			lowerCamelCase__    (    self     ,     a_     ,     a_	)	->float:







        '''simple docstring'''


        return np.dot(a_     ,     a_	)






      def 			lowerCamelCase__    (    self     ,     a_     ,     a_	)	->float:







        '''simple docstring'''


        return np.exp(-(self.gamma * norm_squared(vectora - vectora	))	)






      def 			lowerCamelCase__    (    self     ,     a_     ,     a_	)	->None:







        '''simple docstring'''


        _a							=	observations
        _a							=	classes

        # using Wolfe's Dual to calculate w.
        # Primal problem: minimize 1/2*norm_squared(w)
        #   constraint: yn(w . xn + b) >= 1
        #
        # With l a vector
        # Dual problem: maximize sum_n(ln) -
        #       1/2 * sum_n(sum_m(ln*lm*yn*ym*xn . xm))
        #   constraint: self.C >= ln >= 0
        #           and sum_n(ln*yn) = 0
        # Then we get w using w = sum_n(ln*yn*xn)
        # At the end we can get b ~= mean(yn - w . xn)
        #
        # Since we use kernels, we only need l_star to calculate b
        # and to classify observations

        ((_a)			,	)							=	np.shape(a_	)

        def to_minimize(a_	) -> float:
          _a							=	0
          ((_a)			,	)							=	np.shape(a_	)
          for i in range(a_	):
            for j in range(a_	):
              s += (
                  candidate[i]
                  * candidate[j]
                  * classes[i]
                  * classes[j]
                  * self.kernel(observations[i]     ,     observations[j]	)
              )
          return 1 / 2 * s - sum(a_	)

        _a							=	LinearConstraint(a_     ,     0     ,     0	)
        _a							=	Bounds(0     ,     self.regularization	)

        _a							=	minimize(
            a_     ,     np.ones(a_	)     ,     bounds=a_     ,     constraints=[ly_contraint]	).x
        _a							=	l_star

        # calculating mean offset of separation plane to points
        _a							=	0
        for i in range(a_	):
          for j in range(a_	):
            s += classes[i] - classes[i] * self.optimum[i] * self.kernel(
                observations[i]     ,     observations[j]	)
        _a							=	s / n






      def 			lowerCamelCase__    (    self     ,     a_	)	->int:







        '''simple docstring'''


        _a							=	sum(
            self.optimum[n]
            * self.classes[n]
            * self.kernel(self.observations[n]     ,     a_	)
            for n in range(len(self.classes	)	)	)
        return 1 if s + self.offset >= 0 else -1


if __name__ == "__main__":
     import doctest

     doctest.testmod()


