






'''simple docstring'''

import tempfile
import unittest

from diffusers import (
    DDIMScheduler,
    DDPMScheduler,
    DPMSolverMultistepScheduler,
    EulerAncestralDiscreteScheduler,
    EulerDiscreteScheduler,
    PNDMScheduler,
    logging,
)
from diffusers.configuration_utils import ConfigMixin, register_to_config
from diffusers.utils.testing_utils import CaptureLogger






class 				__magic_name__  (						UpperCAmelCase_					):







	"""simple docstring"""



	SCREAMING_SNAKE_CASE_       :   List[str]   =	'config.json'
	@register_to_config
	def __init__(				self	,   _lowercase=2	,   _lowercase=5	,   _lowercase=(2, 5)	,   _lowercase="for diffusion"	,   _lowercase=[1, 3]	,   )    ->	Any:
							pass






class 				__magic_name__  (						UpperCAmelCase_					):







	"""simple docstring"""



	SCREAMING_SNAKE_CASE_       :   Union[str, Any]   =	'config.json'
	@register_to_config
	def __init__(				self	,   _lowercase=2	,   _lowercase=5	,   _lowercase=(2, 5)	,   _lowercase="for diffusion"	,   _lowercase=[1, 3]	,   )    ->	Optional[Any]:
							pass






class 				__magic_name__  (						UpperCAmelCase_					):







	"""simple docstring"""



	SCREAMING_SNAKE_CASE_       :   str   =	'config.json'
	@register_to_config
	def __init__(				self	,   _lowercase=2	,   _lowercase=5	,   _lowercase=(2, 5)	,   _lowercase="for diffusion"	,   _lowercase=[1, 3]	,   _lowercase=[1, 3]	,   )    ->	Union[str, Any]:
							pass






class 				__magic_name__  (						UpperCAmelCase_					):







	"""simple docstring"""



	SCREAMING_SNAKE_CASE_       :   str   =	'config.json'
	@register_to_config
	def __init__(				self	,   _lowercase=2	,   _lowercase=5	,   _lowercase=(2, 5)	,   _lowercase="for diffusion"	,   _lowercase=[1, 5]	,   _lowercase=[5, 4]	,   )    ->	List[str]:
							pass






class 				__magic_name__  (						unittest.TestCase					):







	"""simple docstring"""



	def 							lowerCamelCase__		(				self							)    ->	Optional[int]:
							with self.assertRaises(_lowercase							):
													ConfigMixin.load_config('dummy_path'							)
	def 							lowerCamelCase__		(				self							)    ->	Optional[Any]:
							lowercase_   : Optional[int]   	=      SampleObject()
							lowercase_   : Dict   	=      obj.config
							assert config["a"] == 2
							assert config["b"] == 5
							assert config["c"] == (2, 5)
							assert config["d"] == "for diffusion"
							assert config["e"] == [1, 3]

							# init ignore private arguments
							lowercase_   : str   	=      SampleObject(_name_or_path='lalala'							)
							lowercase_   : Any   	=      obj.config
							assert config["a"] == 2
							assert config["b"] == 5
							assert config["c"] == (2, 5)
							assert config["d"] == "for diffusion"
							assert config["e"] == [1, 3]

							# can override default
							lowercase_   : Union[str, Any]   	=      SampleObject(c=6							)
							lowercase_   : int   	=      obj.config
							assert config["a"] == 2
							assert config["b"] == 5
							assert config["c"] == 6
							assert config["d"] == "for diffusion"
							assert config["e"] == [1, 3]

							# can use positional arguments.
							lowercase_   : Tuple   	=      SampleObject(1	,   c=6							)
							lowercase_   : Tuple   	=      obj.config
							assert config["a"] == 1
							assert config["b"] == 5
							assert config["c"] == 6
							assert config["d"] == "for diffusion"
							assert config["e"] == [1, 3]
	def 							lowerCamelCase__		(				self							)    ->	Tuple:
							lowercase_   : Tuple   	=      SampleObject()
							lowercase_   : Optional[int]   	=      obj.config

							assert config["a"] == 2
							assert config["b"] == 5
							assert config["c"] == (2, 5)
							assert config["d"] == "for diffusion"
							assert config["e"] == [1, 3]

							with tempfile.TemporaryDirectory() as tmpdirname:
													obj.save_config(_lowercase							)
													lowercase_   : List[Any]   	=      SampleObject.from_config(SampleObject.load_config(_lowercase							)							)
													lowercase_   : Optional[Any]   	=      new_obj.config

							# unfreeze configs
							lowercase_   : Any   	=      dict(_lowercase							)
							lowercase_   : Optional[int]   	=      dict(_lowercase							)

							assert config.pop('c'							) == (2, 5)  # instantiated as tuple
							assert new_config.pop('c'							) == [2, 5]  # saved & loaded as list because of json
							config.pop('_use_default_values'							)
							assert config == new_config
	def 							lowerCamelCase__		(				self							)    ->	Optional[int]:
							lowercase_   : List[Any]   	=      logging.get_logger('diffusers.configuration_utils'							)
							# 30 for warning
							logger.setLevel(30							)

							with CaptureLogger(_lowercase							) as cap_logger:
													lowercase_   : Tuple   	=      DDIMScheduler.from_pretrained(
													    'hf-internal-testing/tiny-stable-diffusion-torch'	,   subfolder='scheduler'							)

							assert ddim.__class__ == DDIMScheduler
							# no warning should be thrown
							assert cap_logger.out == ""
	def 							lowerCamelCase__		(				self							)    ->	str:
							lowercase_   : str   	=      logging.get_logger('diffusers.configuration_utils'							)
							# 30 for warning
							logger.setLevel(30							)

							with CaptureLogger(_lowercase							) as cap_logger:
													lowercase_   : Tuple   	=      EulerDiscreteScheduler.from_pretrained(
													    'hf-internal-testing/tiny-stable-diffusion-torch'	,   subfolder='scheduler'							)

							assert euler.__class__ == EulerDiscreteScheduler
							# no warning should be thrown
							assert cap_logger.out == ""
	def 							lowerCamelCase__		(				self							)    ->	int:
							lowercase_   : List[str]   	=      logging.get_logger('diffusers.configuration_utils'							)
							# 30 for warning
							logger.setLevel(30							)

							with CaptureLogger(_lowercase							) as cap_logger:
													lowercase_   : Optional[Any]   	=      EulerAncestralDiscreteScheduler.from_pretrained(
													    'hf-internal-testing/tiny-stable-diffusion-torch'	,   subfolder='scheduler'							)

							assert euler.__class__ == EulerAncestralDiscreteScheduler
							# no warning should be thrown
							assert cap_logger.out == ""
	def 							lowerCamelCase__		(				self							)    ->	Any:
							lowercase_   : Optional[int]   	=      logging.get_logger('diffusers.configuration_utils'							)
							# 30 for warning
							logger.setLevel(30							)

							with CaptureLogger(_lowercase							) as cap_logger:
													lowercase_   : str   	=      PNDMScheduler.from_pretrained(
													    'hf-internal-testing/tiny-stable-diffusion-torch'	,   subfolder='scheduler'							)

							assert pndm.__class__ == PNDMScheduler
							# no warning should be thrown
							assert cap_logger.out == ""
	def 							lowerCamelCase__		(				self							)    ->	int:
							lowercase_   : Any   	=      logging.get_logger('diffusers.configuration_utils'							)
							# 30 for warning
							logger.setLevel(30							)

							with CaptureLogger(_lowercase							) as cap_logger:
													lowercase_   : List[str]   	=      DDPMScheduler.from_pretrained(
													    'hf-internal-testing/tiny-stable-diffusion-torch'	,   subfolder='scheduler'	,   prediction_type='sample'	,   beta_end=8	,   )

							with CaptureLogger(_lowercase							) as cap_logger_a:
													lowercase_   : str   	=      DDPMScheduler.from_pretrained('google/ddpm-celebahq-256'	,   beta_start=88							)

							assert ddpm.__class__ == DDPMScheduler
							assert ddpm.config.prediction_type == "sample"
							assert ddpm.config.beta_end == 8
							assert ddpm_a.config.beta_start == 88

							# no warning should be thrown
							assert cap_logger.out == ""
							assert cap_logger_a.out == ""
	def 							lowerCamelCase__		(				self							)    ->	Optional[Any]:
							lowercase_   : Any   	=      logging.get_logger('diffusers.configuration_utils'							)
							# 30 for warning
							logger.setLevel(30							)

							with CaptureLogger(_lowercase							) as cap_logger:
													lowercase_   : List[str]   	=      DPMSolverMultistepScheduler.from_pretrained(
													    'hf-internal-testing/tiny-stable-diffusion-torch'	,   subfolder='scheduler'							)

							assert dpm.__class__ == DPMSolverMultistepScheduler
							# no warning should be thrown
							assert cap_logger.out == ""







	def 							lowerCamelCase__		(				self							)    ->	Optional[int]:
							# let's first save a config that should be in the form
							#    a=2,
							#    b=5,
							#    c=(2, 5),
							#    d="for diffusion",
							#    e=[1, 3],

							lowercase_   : int   	=      SampleObject()

							lowercase_   : int   	=      {k: v for k, v in config.config.items() if not k.startswith('_'							)}

							# make sure that default config has all keys in `_use_default_values`
							assert set(config_dict.keys()							) == set(config.config._use_default_values							)

							with tempfile.TemporaryDirectory() as tmpdirname:
													config.save_config(_lowercase							)

													# now loading it with SampleObject2 should put f into `_use_default_values`
													lowercase_   : Any   	=      SampleObjecta.from_config(_lowercase							)

													assert "f" in config._use_default_values
													assert config.f == [1, 3]

							# now loading the config, should **NOT** use [1, 3] for `f`, but the default [1, 4] value
							# **BECAUSE** it is part of `config._use_default_values`
							lowercase_   : Optional[int]   	=      SampleObjecta.from_config(config.config							)
							assert new_config.f == [5, 4]

							config.config._use_default_values.pop()
							lowercase_   : Tuple   	=      SampleObjecta.from_config(config.config							)
							assert new_config_a.f == [1, 3]

							# Nevertheless "e" should still be correctly loaded to [1, 3] from SampleObject2 instead of defaulting to [1, 5]
							assert new_config_a.e == [1, 3]








'''simple docstring'''

import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp






def 						_UpperCAmelCase     (	)      ->      Optional[Any]:





						"""simple docstring"""
						lowercase_   : List[str]   	=      ArgumentParser(
						    description=(
						        'PyTorch TPU distributed training launch helper utility that will spawn up multiple distributed processes'
						    )				)

						# Optional arguments for the launch helper
						parser.add_argument('--num_cores'    ,      type=a    ,      default=1    ,      help='Number of TPU cores to use (1 or 8).'				)

						# positional
						parser.add_argument(
						    'training_script'    ,      type=a    ,      help=(
						        'The full path to the single TPU training '
						        'program/script to be launched in parallel, '
						        'followed by all the arguments for the '
						        'training script'
						    )    ,      )

						# rest from the training program
						parser.add_argument('training_script_args'    ,      nargs=a				)

						return parser.parse_args()






def 						_UpperCAmelCase     (	)      ->      str:





						"""simple docstring"""
						lowercase_   : Optional[int]   	=      parse_args()

						# Import training_script as a module.
						lowercase_   : str   	=      Path(args.training_script				)
						sys.path.append(str(script_fpath.parent.resolve()				)				)
						lowercase_   : int   	=      script_fpath.stem
						lowercase_   : List[Any]   	=      importlib.import_module(a				)

						# Patch sys.argv
						lowercase_   : List[str]   	=      [args.training_script] + args.training_script_args + ['--tpu_num_cores', str(args.num_cores				)]

						xmp.spawn(mod._mp_fn    ,      args=()    ,      nprocs=args.num_cores				)


if __name__ == "__main__":
						main()
