
from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
					if not (is_transformers_available() and is_torch_available()):
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					from ...utils.dummy_torch_and_transformers_objects import KandinskyPipeline, KandinskyPriorPipeline
else:
					from .pipeline_kandinsky import KandinskyPipeline
					from .pipeline_kandinsky_imgaimg import KandinskyImgaImgPipeline
					from .pipeline_kandinsky_inpaint import KandinskyInpaintPipeline
					from .pipeline_kandinsky_prior import KandinskyPriorPipeline, KandinskyPriorPipelineOutput
					from .text_encoder import MultilingualCLIP

import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment







@require_huggingface_suite
class  UpperCamelCase__		(    unittest.TestCase   ):







	'''simple docstring'''





	def   __snake_case				(			self		):
					A__  :	Dict         =							inspect.getfile(accelerate.test_utils		)
					A__  :	Any         =							os.path.sep.join(
					    mod_file.split(os.path.sep		)[:-1] + ['''scripts''', '''external_deps''', '''test_metrics.py''']		)

					from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

					A__  :	Tuple         =							test_metrics





	@require_cpu
	def   __snake_case				(			self		):
					debug_launcher(self.test_metrics.main				,       num_processes=1		)





	@require_cpu
	def   __snake_case				(			self		):
					debug_launcher(self.test_metrics.main		)





	@require_single_gpu
	def   __snake_case				(			self		):
					self.test_metrics.main()





	@require_multi_gpu
	def   __snake_case				(			self		):
					print(F"Found {torch.cuda.device_count()} devices."		)
					A__  :	int         =							['''torchrun''', F"--nproc_per_node={torch.cuda.device_count()}", self.test_file_path]
					with patch_environment(omp_num_threads=1		):
									execute_subprocess_async(UpperCamelCase__				,       env=os.environ.copy()		)