
"""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


lowerCamelCase__   					=		WebClient(token=os.environ["""CI_SLACK_BOT_TOKEN"""])
def     __lowerCAmelCase				(_UpperCamelCase		):
	__lowerCAmelCase			:						List[str]									=      test_results.split(' '		)

	__lowerCAmelCase			:						Tuple									=      0
	__lowerCAmelCase			:						List[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.
	__lowerCAmelCase			:						int									=      expressions[-2] if '=' in expressions[-1] else expressions[-1]

	for i, expression in enumerate(_UpperCamelCase		):
		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		):
	__lowerCAmelCase			:						Optional[int]									=      {}
	__lowerCAmelCase			:						int									=      None
	__lowerCAmelCase			:						List[Any]									=      False
	for line in failures_short_lines.split('\n'		):
		if re.search(r'_ \[doctest\]'       ,  _UpperCamelCase		):
			__lowerCAmelCase			:						List[str]									=      True
			__lowerCAmelCase			:						Union[str, Any]									=      line.split(' '		)[2]
		elif in_error and not line.split(' '		)[0].isdigit():
			__lowerCAmelCase			:						Union[str, Any]									=      line
			__lowerCAmelCase			:						Any									=      False

	return failures




class  A__       :

		def __init__(      self       ,		_SCREAMING_SNAKE_CASE       ,		_SCREAMING_SNAKE_CASE ):
			__lowerCAmelCase			:						Optional[int]									=      title

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

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

		@property
		def 							__lowerCamelCase							(      self ):
			__lowerCAmelCase			:						Union[str, Any]									=      [self._time_spent]
			__lowerCAmelCase			:						int									=      0

			for time in time_spent:
				__lowerCAmelCase			:						Tuple									=      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(_SCREAMING_SNAKE_CASE ) == 1:
					__lowerCAmelCase			:						Dict									=      [0, 0, time_parts[0]]

				__lowerCAmelCase			,   __lowerCAmelCase			,   __lowerCAmelCase			:						Optional[Any]									=      int(time_parts[0] ), int(time_parts[1] ), float(time_parts[2] )
				total_secs += hours * 36_00 + minutes * 60 + seconds

			__lowerCAmelCase			,   __lowerCAmelCase			,   __lowerCAmelCase			:						Any									=      total_secs // 36_00, (total_secs % 36_00) // 60, total_secs % 60
			return f"{int(_SCREAMING_SNAKE_CASE )}h{int(_SCREAMING_SNAKE_CASE )}m{int(_SCREAMING_SNAKE_CASE )}s"

		@property
		def 							__lowerCamelCase							(      self ):
			return {"type": "header", "text": {"type": "plain_text", "text": self.title}}

		@property
		def 							__lowerCamelCase							(      self ):
			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 ):
			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 ):
			__lowerCAmelCase			:						Any									=      40
			__lowerCAmelCase			:						int									=      {k: v['failed'] for k, v in doc_test_results.items() if isinstance(_SCREAMING_SNAKE_CASE       ,		_SCREAMING_SNAKE_CASE )}

			__lowerCAmelCase			:						Any									=      ''
			for category, failures in category_failures.items():
				if len(_SCREAMING_SNAKE_CASE ) == 0:
					continue

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

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

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

		@property
		def 							__lowerCamelCase							(      self ):
			__lowerCAmelCase			:						List[Any]									=      [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(_SCREAMING_SNAKE_CASE )

		@staticmethod
		def 							__lowerCamelCase							(      ):
			__lowerCAmelCase			:						Dict									=      [
			    {
			        '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(_SCREAMING_SNAKE_CASE )} ) )

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

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

			__lowerCAmelCase			:						Any									=      f"{self.n_failures} failures out of {self.n_tests} tests," if self.n_failures else 'All tests passed.'

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

		def 							__lowerCamelCase							(      self       ,		_SCREAMING_SNAKE_CASE       ,		_SCREAMING_SNAKE_CASE       ,		_SCREAMING_SNAKE_CASE       ,		_SCREAMING_SNAKE_CASE ):
			__lowerCAmelCase			:						Any									=      ''
			for key, value in failures.items():
				__lowerCAmelCase			:						str									=      value[:2_00] + ' [Truncated]' if len(_SCREAMING_SNAKE_CASE ) > 2_50 else value
				failures_text += f"*{key}*\n_{value}_\n\n"

			__lowerCAmelCase			:						int									=      job_name
			__lowerCAmelCase			:						str									=      {'type': 'section', 'text': {'type': 'mrkdwn', 'text': text}}

			if job_link is not None:
				__lowerCAmelCase			:						int									=      {
				    '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 ):
			if self.thread_ts is None:
				raise ValueError('Can only post reply if a post has been made.' )

			__lowerCAmelCase			:						int									=      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' )

			__lowerCAmelCase			:						Union[str, Any]									=      sorted(self.doc_test_results.items()       ,		key=lambda _SCREAMING_SNAKE_CASE : t[0] )
			for job, job_result in sorted_dict:
				if len(job_result['failures'] ):
					__lowerCAmelCase			:						List[Any]									=      f"*Num failures* :{len(job_result['failed'] )} \n"
					__lowerCAmelCase			:						Optional[int]									=      job_result['failures']
					__lowerCAmelCase			:						Dict									=      self.get_reply_blocks(_SCREAMING_SNAKE_CASE       ,		_SCREAMING_SNAKE_CASE       ,		_SCREAMING_SNAKE_CASE       ,		text=_SCREAMING_SNAKE_CASE )

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

					time.sleep(1 )



def     __lowerCAmelCase				():
	__lowerCAmelCase			:						int									=      os.environ['GITHUB_RUN_ID']
	__lowerCAmelCase			:						Optional[int]									=      F"https://api.github.com/repos/huggingface/transformers/actions/runs/{run_id}/jobs?per_page=100"
	__lowerCAmelCase			:						int									=      requests.get(_UpperCamelCase		).json()
	__lowerCAmelCase			:						int									=      {}

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

		for i in range(_UpperCamelCase		):
			__lowerCAmelCase			:						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.'       ,  _UpperCamelCase		)

	return {}
def     __lowerCAmelCase				(_UpperCamelCase		):
	__lowerCAmelCase			:						List[str]									=      {}

	if os.path.exists(_UpperCamelCase		):
		__lowerCAmelCase			:						Any									=      os.listdir(_UpperCamelCase		)
		for file in files:
			try:
				with open(os.path.join(_UpperCamelCase       ,  _UpperCamelCase		)       ,  encoding='utf-8'		) as f:
					__lowerCAmelCase			:						List[str]									=      f.read()
			except UnicodeDecodeError as e:
				raise ValueError(F"Could not open {os.path.join(_UpperCamelCase       ,  _UpperCamelCase		)}."		) from e

	return _artifact
def     __lowerCAmelCase				():




	class  A__       :

			def __init__(      self       ,		_SCREAMING_SNAKE_CASE ):
				__lowerCAmelCase			:						str									=      name
				__lowerCAmelCase			:						str									=      []

			def __str__(      self ):
				return self.name







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



	__lowerCAmelCase			:						Dict[str, Artifact]									=      {}

	__lowerCAmelCase			:						Optional[Any]									=      filter(os.path.isdir       ,  os.listdir()		)
	for directory in directories:
		__lowerCAmelCase			:						Optional[int]									=      directory
		if artifact_name not in _available_artifacts:
			__lowerCAmelCase			:						Union[str, Any]									=      Artifact(_UpperCamelCase		)

			_available_artifacts[artifact_name].add_path(_UpperCamelCase		)

	return _available_artifacts


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

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

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

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

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

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

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

																																										lowerCamelCase__   					=		all_failures[test] if test in all_failures else """N/A"""
																																										lowerCamelCase__   					=		failure
																																										break

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






import math
from typing import List, Optional, Tuple, Union

import numpy as np
import torch

from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput





class  _A						(       lowerCAmelCase  ,    lowerCAmelCase	):
      snake_case__			:   Tuple							  =	1

      @register_to_config
      def __init__(						self		,       __lowerCAmelCase = 1000		,       __lowerCAmelCase = None						):







            """simple docstring"""



            self.set_timesteps(__lowerCAmelCase						)

            # standard deviation of the initial noise distribution
            lowercase														=	1.0

            # For now we only support F-PNDM, i.e. the runge-kutta method
            # For more information on the algorithm please take a look at the paper: https://arxiv.org/pdf/2202.09778.pdf
            # mainly at formula (9), (12), (13) and the Algorithm 2.
            lowercase														=	4

            # running values
            lowercase														=	[]

      def 				A__       (						self		,       __lowerCAmelCase		,       __lowerCAmelCase = None						):







            """simple docstring"""



            lowercase														=	num_inference_steps
            lowercase														=	torch.linspace(1		,       0		,       num_inference_steps + 1						)[:-1]
            lowercase														=	torch.cat([steps, torch.tensor([0.0]						)]						)

            if self.config.trained_betas is not None:
                  lowercase														=	torch.tensor(self.config.trained_betas		,       dtype=torch.floataa						)
            else:
                  lowercase														=	torch.sin(steps * math.pi / 2						) ** 2

            lowercase														=	(1.0 - self.betas**2) ** 0.5

            lowercase														=	(torch.atana(self.betas		,       self.alphas						) / math.pi * 2)[:-1]
            lowercase														=	timesteps.to(__lowerCAmelCase						)

            lowercase														=	[]

      def 				A__       (						self		,       __lowerCAmelCase		,       __lowerCAmelCase		,       __lowerCAmelCase		,       __lowerCAmelCase = True		,       ):







            """simple docstring"""



            if self.num_inference_steps is None:
                  raise ValueError(
                      """Number of inference steps is 'None', you need to run 'set_timesteps' after creating the scheduler"""						)

            lowercase														=	(self.timesteps == timestep).nonzero().item()
            lowercase														=	timestep_index + 1

            lowercase														=	sample * self.betas[timestep_index] + model_output * self.alphas[timestep_index]
            self.ets.append(__lowerCAmelCase						)

            if len(self.ets						) == 1:
                  lowercase														=	self.ets[-1]
            elif len(self.ets						) == 2:
                  lowercase														=	(3 * self.ets[-1] - self.ets[-2]) / 2
            elif len(self.ets						) == 3:
                  lowercase														=	(23 * self.ets[-1] - 16 * self.ets[-2] + 5 * self.ets[-3]) / 12
            else:
                  lowercase														=	(1 / 24) * (55 * self.ets[-1] - 59 * self.ets[-2] + 37 * self.ets[-3] - 9 * self.ets[-4])

            lowercase														=	self._get_prev_sample(__lowerCAmelCase		,       __lowerCAmelCase		,       __lowerCAmelCase		,       __lowerCAmelCase						)

            if not return_dict:
                  return (prev_sample,)

            return SchedulerOutput(prev_sample=__lowerCAmelCase						)

      def 				A__       (						self		,       __lowerCAmelCase		,       *__lowerCAmelCase		,       **__lowerCAmelCase						):







            """simple docstring"""



            return sample

      def 				A__       (						self		,       __lowerCAmelCase		,       __lowerCAmelCase		,       __lowerCAmelCase		,       __lowerCAmelCase						):







            """simple docstring"""



            lowercase														=	self.alphas[timestep_index]
            lowercase														=	self.betas[timestep_index]

            lowercase														=	self.alphas[prev_timestep_index]
            lowercase														=	self.betas[prev_timestep_index]

            lowercase														=	(sample - sigma * ets) / max(__lowerCAmelCase		,       1E-8						)
            lowercase														=	next_alpha * pred + ets * next_sigma

            return prev_sample







      def __len__(						self						):







            """simple docstring"""



            return self.config.num_train_timesteps



