



'''simple docstring'''





import csv
import json
import logging
import os
import re
import subprocess
import tempfile
import unittest
import zipfile
from pathlib import Path
from typing import Optional
from unittest import mock

import torch

# We use TF to parse the logs
from accelerate import Accelerator
from accelerate.test_utils.testing import (
    MockingTestCase,
    TempDirTestCase,
    require_comet_ml,
    require_tensorboard,
    require_wandb,
    skip,
)
from accelerate.tracking import CometMLTracker, GeneralTracker
from accelerate.utils import ProjectConfiguration, is_comet_ml_available, is_tensorboard_available


if is_comet_ml_available():
   from comet_ml import OfflineExperiment

if is_tensorboard_available():
   import struct

   import tensorboard.compat.proto.event_pba as event_pba

_UpperCamelCase							    =						logging.getLogger(__name__)






@require_tensorboard
class  lowerCamelCase_   (    unittest.TestCase					):
  """simple docstring"""




  def 						_lowercase					(			self				:     Optional[int]       ) -> Tuple:
    __lowerCamelCase	:	Any   	=			'test_project_with_config'
    with tempfile.TemporaryDirectory() as dirpath:
      __lowerCamelCase	:	Optional[int]   	=			Accelerator(log_with='tensorboard'      ,     project_dir=SCREAMING_SNAKE_CASE_       )
      __lowerCamelCase	:	Union[str, Any]   	=			{'num_iterations': 12, 'learning_rate': 1e-2, 'some_boolean': False, 'some_string': 'some_value'}
      accelerator.init_trackers(SCREAMING_SNAKE_CASE_      ,     SCREAMING_SNAKE_CASE_       )
      accelerator.end_training()
      for child in Path(f'{dirpath}/{project_name}'       ).glob('*/**'       ):
        __lowerCamelCase	:	int   	=			list(filter(lambda _a       : x.is_file()      ,     child.iterdir()       )       )[0]
      self.assertNotEqual(str(SCREAMING_SNAKE_CASE_       )      ,     ''       )




  def 						_lowercase					(			self				:     str       ) -> int:
    __lowerCamelCase	:	str   	=			'test_project_with_log'
    with tempfile.TemporaryDirectory() as dirpath:
      __lowerCamelCase	:	List[str]   	=			Accelerator(log_with='tensorboard'      ,     project_dir=SCREAMING_SNAKE_CASE_       )
      accelerator.init_trackers(SCREAMING_SNAKE_CASE_       )
      __lowerCamelCase	:	Optional[Any]   	=			{'total_loss': 0.1, 'iteration': 1, 'my_text': 'some_value'}
      accelerator.log(SCREAMING_SNAKE_CASE_      ,     step=0       )
      accelerator.end_training()
      # Logged values are stored in the outermost-tfevents file and can be read in as a TFRecord
      # Names are randomly generated each time
      __lowerCamelCase	:	Tuple   	=			list(filter(lambda _a       : x.is_file()      ,     Path(f'{dirpath}/{project_name}'       ).iterdir()       )       )[0]
      self.assertNotEqual(str(SCREAMING_SNAKE_CASE_       )      ,     ''       )




  def 						_lowercase					(			self				:     Dict       ) -> List[str]:
    __lowerCamelCase	:	Optional[Any]   	=			'test_project_with_log'
    with tempfile.TemporaryDirectory() as dirpath:
      __lowerCamelCase	:	Any   	=			Accelerator(log_with='tensorboard'      ,     project_dir=SCREAMING_SNAKE_CASE_       )
      accelerator.init_trackers(SCREAMING_SNAKE_CASE_       )
      __lowerCamelCase	:	List[Any]   	=			{'tensor': torch.tensor(1       )}
      accelerator.log(SCREAMING_SNAKE_CASE_      ,     step=0       )
      accelerator.end_training()
      # Logged values are stored in the outermost-tfevents file and can be read in as a TFRecord
      # Names are randomly generated each time
      __lowerCamelCase	:	Tuple   	=			list(filter(lambda _a       : x.is_file()      ,     Path(f'{dirpath}/{project_name}'       ).iterdir()       )       )[0]
      # Reading implementation based on https://github.com/pytorch/pytorch/issues/45327#issuecomment-703757685
      with open(SCREAMING_SNAKE_CASE_      ,     'rb'       ) as f:
        __lowerCamelCase	:	Any   	=			f.read()
      __lowerCamelCase	:	Union[str, Any]   	=			False
      while data:
        __lowerCamelCase	:	Tuple   	=			struct.unpack('Q'      ,     data[:8]       )

        __lowerCamelCase	:	str   	=			data[12 : 12 + int(header[0]       )]  # 8+4
        __lowerCamelCase	:	Optional[int]   	=			data[12 + int(header[0]       ) + 4 :]
        __lowerCamelCase	:	str   	=			event_pba.Event()

        event.ParseFromString(SCREAMING_SNAKE_CASE_       )
        if event.HasField('summary'       ):
          for value in event.summary.value:
            if value.simple_value == 1.0 and value.tag == "tensor":
              __lowerCamelCase	:	List[Any]   	=			True
      self.assertTrue(SCREAMING_SNAKE_CASE_      ,     'Converted tensor was not found in the log file!'       )




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






    with self.assertRaisesRegex(SCREAMING_SNAKE_CASE_      ,     'Logging with `tensorboard` requires a `logging_dir`'       ):
      __lowerCamelCase	:	int   	=			Accelerator(log_with='tensorboard'       )
    with tempfile.TemporaryDirectory() as dirpath:
      __lowerCamelCase	:	Any   	=			Accelerator(log_with='tensorboard'      ,     project_dir=SCREAMING_SNAKE_CASE_       )




  def 						_lowercase					(			self				:     str       ) -> Optional[Any]:
    __lowerCamelCase	:	str   	=			ProjectConfiguration(total_limit=30       )
    with tempfile.TemporaryDirectory() as dirpath:
      __lowerCamelCase	:	int   	=			Accelerator(log_with='tensorboard'      ,     project_dir=SCREAMING_SNAKE_CASE_      ,     project_config=SCREAMING_SNAKE_CASE_       )






@require_wandb
@mock.patch.dict(os.environ       ,       {"""WANDB_MODE""": """offline"""}					)
class  lowerCamelCase_   (    SCREAMING_SNAKE_CASE_       ,       SCREAMING_SNAKE_CASE_					):
  """simple docstring"""




  def 						_lowercase					(			self				:     List[str]       ) -> Optional[int]:
    super().setUp()
    # wandb let's us override where logs are stored to via the WANDB_DIR env var
    self.add_mocks(mock.patch.dict(os.environ      ,     {'WANDB_DIR': self.tmpdir}       )       )




  @staticmethod
  def 						_lowercase					(			_a				:     Optional[int]      ,     _a				:     int      ,     _a				:     Dict = True       ) -> Dict:
    __lowerCamelCase	:	List[Any]   	=			Rf'{section} ([\S\s]*?)\n\n'
    if record:
      __lowerCamelCase	:	Optional[Any]   	=			Rf'Record: {pattern}'
    __lowerCamelCase	:	Union[str, Any]   	=			re.findall(SCREAMING_SNAKE_CASE_      ,     SCREAMING_SNAKE_CASE_       )[0]
    # A config
    if section == "config" or section == "history":
      __lowerCamelCase	:	int   	=			re.findall(R'"([a-zA-Z0-9_.,]+)'      ,     SCREAMING_SNAKE_CASE_       )
      return {key: val for key, val in zip(cleaned_record[0::2]      ,     cleaned_record[1::2]       )}
    # Everything else
    else:
      return dict(re.findall(R'(\w+): "([^\s]+)"'      ,     SCREAMING_SNAKE_CASE_       )       )




  @skip
  def 						_lowercase					(			self				:     List[str]       ) -> List[str]:
    __lowerCamelCase	:	Union[str, Any]   	=			'test_project_with_config'
    __lowerCamelCase	:	Dict   	=			Accelerator(log_with='wandb'       )
    __lowerCamelCase	:	Optional[int]   	=			{'num_iterations': 12, 'learning_rate': 1e-2, 'some_boolean': False, 'some_string': 'some_value'}
    __lowerCamelCase	:	Any   	=			{'wandb': {'tags': ['my_tag']}}
    accelerator.init_trackers(SCREAMING_SNAKE_CASE_      ,     SCREAMING_SNAKE_CASE_      ,     SCREAMING_SNAKE_CASE_       )
    __lowerCamelCase	:	Any   	=			{'total_loss': 0.1, 'iteration': 1, 'my_text': 'some_value'}
    accelerator.log(SCREAMING_SNAKE_CASE_      ,     step=0       )
    accelerator.end_training()
    # The latest offline log is stored at wandb/latest-run/*.wandb
    for child in Path(f'{self.tmpdir}/wandb/latest-run'       ).glob('*'       ):
      if child.is_file() and child.suffix == ".wandb":
        __lowerCamelCase	:	List[Any]   	=			subprocess.check_output(
            ['wandb', 'sync', '--view', '--verbose', str(SCREAMING_SNAKE_CASE_       )]      ,     env=os.environ.copy()       ).decode('utf8'      ,     'ignore'       )
        break

        # Check HPS through careful parsing and cleaning
    __lowerCamelCase	:	Optional[int]   	=			self.parse_log(SCREAMING_SNAKE_CASE_      ,     'config'       )
    self.assertEqual(logged_items['num_iterations']      ,     '12'       )
    self.assertEqual(logged_items['learning_rate']      ,     '0.01'       )
    self.assertEqual(logged_items['some_boolean']      ,     'false'       )
    self.assertEqual(logged_items['some_string']      ,     'some_value'       )
    self.assertEqual(logged_items['some_string']      ,     'some_value'       )

    # Run tags
    __lowerCamelCase	:	Union[str, Any]   	=			self.parse_log(SCREAMING_SNAKE_CASE_      ,     'run'      ,     SCREAMING_SNAKE_CASE_       )
    self.assertEqual(logged_items['tags']      ,     'my_tag'       )

    # Actual logging
    __lowerCamelCase	:	int   	=			self.parse_log(SCREAMING_SNAKE_CASE_      ,     'history'       )
    self.assertEqual(logged_items['total_loss']      ,     '0.1'       )
    self.assertEqual(logged_items['iteration']      ,     '1'       )
    self.assertEqual(logged_items['my_text']      ,     'some_value'       )
    self.assertEqual(logged_items['_step']      ,     '0'       )




def 	a_					(							self	,_lowerCAmelCase	,_lowerCAmelCase	)				->				Any:
  __lowerCamelCase	:	Any   	=			run_name
  __lowerCamelCase	:	List[Any]   	=			OfflineExperiment(project_name=_lowerCAmelCase	,offline_directory=_lowerCAmelCase	)
  logger.info(F'Initialized offline CometML project {self.run_name}'	)
  logger.info('Make sure to log any initial configurations with `self.store_init_configuration` before training!'	)






@require_comet_ml
@mock.patch.object(SCREAMING_SNAKE_CASE_       ,       """__init__"""       ,       SCREAMING_SNAKE_CASE_					)
class  lowerCamelCase_   (    unittest.TestCase					):
  """simple docstring"""




  @staticmethod
  def 						_lowercase					(			_a				:     Optional[Any]      ,     _a				:     Tuple      ,     _a				:     str = False       ) -> List[str]:






    for log in log_list:
      __lowerCamelCase	:	Optional[Any]   	=			json.loads(SCREAMING_SNAKE_CASE_       )['payload']
      if is_param and "param" in j.keys():
        if j["param"]["paramName"] == key:
          return j["param"]["paramValue"]
      if "log_other" in j.keys():
        if j["log_other"]["key"] == key:
          return j["log_other"]["val"]
      if "metric" in j.keys():
        if j["metric"]["metricName"] == key:
          return j["metric"]["metricValue"]




  def 						_lowercase					(			self				:     Any       ) -> List[Any]:






    with tempfile.TemporaryDirectory() as d:
      __lowerCamelCase	:	Optional[int]   	=			CometMLTracker('test_project_with_config'      ,     SCREAMING_SNAKE_CASE_       )
      __lowerCamelCase	:	List[Any]   	=			Accelerator(log_with=SCREAMING_SNAKE_CASE_       )
      __lowerCamelCase	:	Union[str, Any]   	=			{'num_iterations': 12, 'learning_rate': 1e-2, 'some_boolean': False, 'some_string': 'some_value'}
      accelerator.init_trackers(SCREAMING_SNAKE_CASE_      ,     SCREAMING_SNAKE_CASE_       )
      accelerator.end_training()
      __lowerCamelCase	:	Tuple   	=			os.listdir(SCREAMING_SNAKE_CASE_       )[0]  # Comet is nice, it's just a zip file here
      # We parse the raw logs
      __lowerCamelCase	:	Any   	=			os.path.join(SCREAMING_SNAKE_CASE_      ,     SCREAMING_SNAKE_CASE_       )
      __lowerCamelCase	:	Optional[int]   	=			zipfile.ZipFile(SCREAMING_SNAKE_CASE_      ,     'r'       )
      __lowerCamelCase	:	Union[str, Any]   	=			archive.open('messages.json'       ).read().decode('utf-8'       )
    __lowerCamelCase	:	Any   	=			log.split('\n'       )[:-1]
    self.assertEqual(self.get_value_from_key(SCREAMING_SNAKE_CASE_      ,     'num_iterations'      ,     SCREAMING_SNAKE_CASE_       )      ,     12       )
    self.assertEqual(self.get_value_from_key(SCREAMING_SNAKE_CASE_      ,     'learning_rate'      ,     SCREAMING_SNAKE_CASE_       )      ,     0.01       )
    self.assertEqual(self.get_value_from_key(SCREAMING_SNAKE_CASE_      ,     'some_boolean'      ,     SCREAMING_SNAKE_CASE_       )      ,     SCREAMING_SNAKE_CASE_       )
    self.assertEqual(self.get_value_from_key(SCREAMING_SNAKE_CASE_      ,     'some_string'      ,     SCREAMING_SNAKE_CASE_       )      ,     'some_value'       )




  def 						_lowercase					(			self				:     List[Any]       ) -> Optional[int]:






    with tempfile.TemporaryDirectory() as d:
      __lowerCamelCase	:	List[str]   	=			CometMLTracker('test_project_with_config'      ,     SCREAMING_SNAKE_CASE_       )
      __lowerCamelCase	:	List[Any]   	=			Accelerator(log_with=SCREAMING_SNAKE_CASE_       )
      accelerator.init_trackers(SCREAMING_SNAKE_CASE_       )
      __lowerCamelCase	:	Optional[int]   	=			{'total_loss': 0.1, 'iteration': 1, 'my_text': 'some_value'}
      accelerator.log(SCREAMING_SNAKE_CASE_      ,     step=0       )
      accelerator.end_training()
      __lowerCamelCase	:	List[Any]   	=			os.listdir(SCREAMING_SNAKE_CASE_       )[0]  # Comet is nice, it's just a zip file here
      # We parse the raw logs
      __lowerCamelCase	:	int   	=			os.path.join(SCREAMING_SNAKE_CASE_      ,     SCREAMING_SNAKE_CASE_       )
      __lowerCamelCase	:	Union[str, Any]   	=			zipfile.ZipFile(SCREAMING_SNAKE_CASE_      ,     'r'       )
      __lowerCamelCase	:	str   	=			archive.open('messages.json'       ).read().decode('utf-8'       )
    __lowerCamelCase	:	Optional[int]   	=			log.split('\n'       )[:-1]
    self.assertEqual(self.get_value_from_key(SCREAMING_SNAKE_CASE_      ,     'curr_step'      ,     SCREAMING_SNAKE_CASE_       )      ,     0       )
    self.assertEqual(self.get_value_from_key(SCREAMING_SNAKE_CASE_      ,     'total_loss'       )      ,     0.1       )
    self.assertEqual(self.get_value_from_key(SCREAMING_SNAKE_CASE_      ,     'iteration'       )      ,     1       )
    self.assertEqual(self.get_value_from_key(SCREAMING_SNAKE_CASE_      ,     'my_text'       )      ,     'some_value'       )






class  lowerCamelCase_   (    SCREAMING_SNAKE_CASE_					):
  """simple docstring"""




  a_							 =[
      """total_loss""",
      """iteration""",
      """my_text""",
      """learning_rate""",
      """num_iterations""",
      """some_boolean""",
      """some_string""",
  ]

  a_							 ="""my_custom_tracker"""
  a_							 =False




  def __init__(			self				:     Tuple      ,     _a				:     Optional[int]       ) -> Optional[Any]:
    __lowerCamelCase	:	Any   	=			open(f'{dir}/log.csv'      ,     'w+'       )
    __lowerCamelCase	:	Any   	=			csv.DictWriter(self.f      ,     fieldnames=self._col_names       )
    self.writer.writeheader()




  @property
  def 						_lowercase					(			self				:     Optional[Any]       ) -> Tuple:
    return self.writer




  def 						_lowercase					(			self				:     Optional[Any]      ,     _a				:     Dict       ) -> Optional[int]:
    logger.info('Call init'       )
    self.writer.writerow(SCREAMING_SNAKE_CASE_       )




  def 						_lowercase					(			self				:     List[str]      ,     _a				:     Optional[Any]      ,     _a				:     List[Any]       ) -> Optional[int]:
    logger.info('Call log'       )
    self.writer.writerow(SCREAMING_SNAKE_CASE_       )




  def 						_lowercase					(			self				:     Tuple       ) -> Dict:
    self.f.close()






class  lowerCamelCase_   (    unittest.TestCase					):
  """simple docstring"""




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






    with tempfile.TemporaryDirectory() as d:
      __lowerCamelCase	:	Optional[Any]   	=			MyCustomTracker(SCREAMING_SNAKE_CASE_       )
      __lowerCamelCase	:	Any   	=			Accelerator(log_with=SCREAMING_SNAKE_CASE_       )
      __lowerCamelCase	:	Optional[Any]   	=			{'num_iterations': 12, 'learning_rate': 1e-2, 'some_boolean': False, 'some_string': 'some_value'}
      accelerator.init_trackers('Some name'      ,     SCREAMING_SNAKE_CASE_       )
      accelerator.end_training()
      with open(f'{d}/log.csv'      ,     'r'       ) as f:
        __lowerCamelCase	:	int   	=			csv.DictReader(SCREAMING_SNAKE_CASE_       )
        __lowerCamelCase	:	str   	=			next(SCREAMING_SNAKE_CASE_       )
        __lowerCamelCase	:	Optional[int]   	=			{
            'total_loss': '',
            'iteration': '',
            'my_text': '',
            'learning_rate': '0.01',
            'num_iterations': '12',
            'some_boolean': 'False',
            'some_string': 'some_value',
        }
        self.assertDictEqual(SCREAMING_SNAKE_CASE_      ,     SCREAMING_SNAKE_CASE_       )




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






    with tempfile.TemporaryDirectory() as d:
      __lowerCamelCase	:	List[Any]   	=			MyCustomTracker(SCREAMING_SNAKE_CASE_       )
      __lowerCamelCase	:	Tuple   	=			Accelerator(log_with=SCREAMING_SNAKE_CASE_       )
      accelerator.init_trackers('Some name'       )
      __lowerCamelCase	:	Dict   	=			{'total_loss': 0.1, 'iteration': 1, 'my_text': 'some_value'}
      accelerator.log(SCREAMING_SNAKE_CASE_      ,     step=0       )
      accelerator.end_training()
      with open(f'{d}/log.csv'      ,     'r'       ) as f:
        __lowerCamelCase	:	str   	=			csv.DictReader(SCREAMING_SNAKE_CASE_       )
        __lowerCamelCase	:	str   	=			next(SCREAMING_SNAKE_CASE_       )
        __lowerCamelCase	:	Optional[Any]   	=			{
            'total_loss': '0.1',
            'iteration': '1',
            'my_text': 'some_value',
            'learning_rate': '',
            'num_iterations': '',
            'some_boolean': '',
            'some_string': '',
        }
        self.assertDictEqual(SCREAMING_SNAKE_CASE_      ,     SCREAMING_SNAKE_CASE_       )











'''simple docstring'''





import unittest

from diffusers import __version__
from diffusers.utils import deprecate






class  lowerCamelCase_   (    unittest.TestCase					):
  """simple docstring"""




  a_							 =""".""".join([str(int(__version__.split("""."""					)[0]					) + 1					)] + __version__.split("""."""					)[1:]					)
  a_							 ="""0.0.1"""




  def 						_lowercase					(			self				:     Optional[Any]       ) -> int:
    __lowerCamelCase	:	Any   	=			{'deprecated_arg': 4}

    with self.assertWarns(_a       ) as warning:
      __lowerCamelCase	:	Optional[int]   	=			deprecate('deprecated_arg'      ,     self.higher_version      ,     'message'      ,     take_from=_a       )

    assert output == 4
    assert (
        str(warning.warning       )
        == f'The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}.'
        " message"
    )




  def 						_lowercase					(			self				:     Union[str, Any]       ) -> Optional[int]:
    __lowerCamelCase	:	int   	=			{'deprecated_arg': 4}

    with self.assertWarns(_a       ) as warning:
      __lowerCamelCase	:	Optional[Any]   	=			deprecate(('deprecated_arg', self.higher_version, 'message')      ,     take_from=_a       )

    assert output == 4
    assert (
        str(warning.warning       )
        == f'The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}.'
        " message"
    )




  def 						_lowercase					(			self				:     int       ) -> Optional[Any]:
    __lowerCamelCase	:	Optional[int]   	=			{'deprecated_arg_1': 4, 'deprecated_arg_2': 8}
    with self.assertWarns(_a       ) as warning:
      __lowerCamelCase	,__lowerCamelCase	:	Any   	=			deprecate(
          ('deprecated_arg_1', self.higher_version, 'Hey')      ,     ('deprecated_arg_2', self.higher_version, 'Hey')      ,     take_from=_a      ,     )
    assert output_a == 4
    assert output_a == 8
    assert (
        str(warning.warnings[0].message       )
        == "The `deprecated_arg_1` argument is deprecated and will be removed in version"
        f' {self.higher_version}. Hey'
    )
    assert (
        str(warning.warnings[1].message       )
        == "The `deprecated_arg_2` argument is deprecated and will be removed in version"
        f' {self.higher_version}. Hey'
    )




  def 						_lowercase					(			self				:     str       ) -> Optional[Any]:
    __lowerCamelCase	:	Optional[int]   	=			{'deprecated_arg': 4}

    with self.assertRaises(_a       ) as error:
      deprecate(('wrong_arg', self.higher_version, 'message')      ,     take_from=_a       )

    assert "test_deprecate_function_incorrect_arg in" in str(error.exception       )
    assert "line" in str(error.exception       )
    assert "got an unexpected keyword argument `deprecated_arg`" in str(error.exception       )




  def 						_lowercase					(			self				:     Optional[Any]       ) -> Union[str, Any]:
    with self.assertWarns(_a       ) as warning:
      deprecate(('deprecated_arg', self.higher_version, 'message')       )

    assert (
        str(warning.warning       )
        == f'`deprecated_arg` is deprecated and will be removed in version {self.higher_version}. message'
    )




  def 						_lowercase					(			self				:     Optional[Any]       ) -> Union[str, Any]:
    with self.assertWarns(_a       ) as warning:
      deprecate(
          ('deprecated_arg_1', self.higher_version, 'Hey')      ,     ('deprecated_arg_2', self.higher_version, 'Hey')      ,     )
    assert (
        str(warning.warnings[0].message       )
        == f'`deprecated_arg_1` is deprecated and will be removed in version {self.higher_version}. Hey'
    )
    assert (
        str(warning.warnings[1].message       )
        == f'`deprecated_arg_2` is deprecated and will be removed in version {self.higher_version}. Hey'
    )




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






    class  lowerCamelCase_   :
      """simple docstring"""




      a_							 =5

    with self.assertWarns(_a       ) as warning:
      __lowerCamelCase	:	int   	=			deprecate(('arg', self.higher_version, 'message')      ,     take_from=Args()       )

    assert arg == 5
    assert (
        str(warning.warning       )
        == f'The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message'
    )




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






    class  lowerCamelCase_   :
      """simple docstring"""




      a_							 =5
      a_							 =7

    with self.assertWarns(_a       ) as warning:
      __lowerCamelCase	,__lowerCamelCase	:	List[str]   	=			deprecate(
          ('arg', self.higher_version, 'message')      ,     ('foo', self.higher_version, 'message')      ,     ('does not exist', self.higher_version, 'message')      ,     take_from=Args()      ,     )

    assert arg_a == 5
    assert arg_a == 7
    assert (
        str(warning.warning       )
        == f'The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message'
    )
    assert (
        str(warning.warnings[0].message       )
        == f'The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message'
    )
    assert (
        str(warning.warnings[1].message       )
        == f'The `foo` attribute is deprecated and will be removed in version {self.higher_version}. message'
    )




  def 						_lowercase					(			self				:     Union[str, Any]       ) -> List[str]:
    __lowerCamelCase	:	Union[str, Any]   	=			{'deprecated_arg': 4}

    with self.assertRaises(_a       ) as error:
      deprecate(('wrong_arg', self.lower_version, 'message')      ,     take_from=_a       )

    assert (
        str(error.exception       )
        == "The deprecation tuple ('wrong_arg', '0.0.1', 'message') should be removed since diffusers' version"
        f' {__version__} is >= {self.lower_version}'
    )




  def 						_lowercase					(			self				:     Optional[int]       ) -> str:
    with self.assertWarns(_a       ) as warning:
      deprecate(('deprecated_arg', self.higher_version, 'This message is better!!!')      ,     standard_warn=_a       )

    assert str(warning.warning       ) == "This message is better!!!"




  def 						_lowercase					(			self				:     List[Any]       ) -> Union[str, Any]:
    with self.assertWarns(_a       ) as warning:
      deprecate(('deprecated_arg', self.higher_version, 'This message is better!!!')      ,     standard_warn=_a       )
    assert str(warning.warning       ) == "This message is better!!!"
    assert "diffusers/tests/others/test_utils.py" in warning.filename






