





import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock

import torch

from ..state import AcceleratorState, PartialState
from ..utils import (
    gather,
    is_bnb_available,
    is_comet_ml_available,
    is_datasets_available,
    is_deepspeed_available,
    is_mps_available,
    is_safetensors_available,
    is_tensorboard_available,
    is_torch_version,
    is_tpu_available,
    is_transformers_available,
    is_wandb_available,
    is_xpu_available,
)


def 							SCREAMING_SNAKE_CASE__  (			__a      ,       __a=False      ):


	try:
		snake_case_						:	str      =		os.environ[key]
	except KeyError:
		# KEY isn't set, default to `default`.
		snake_case_						:	Union[str, Any]      =		default
	else:
		# KEY is set, convert it to True or False.
		try:
			snake_case_						:	Optional[int]      =		strtobool(_UpperCamelCase      )
		except ValueError:
			# More values are supported, but let's keep the message simple.
			raise ValueError(f"""If set, {key} must be yes or no."""      )
	return _value


_SCREAMING_SNAKE_CASE							=						parse_flag_from_env("""RUN_SLOW""", default=False)


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skip('Test was skipped'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(_run_slow_tests      ,       'test is slow'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(not torch.cuda.is_available()      ,       'test requires only a CPU'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(torch.cuda.is_available()      ,       'test requires a GPU'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(is_xpu_available()      ,       'test requires a XPU'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(is_mps_available()      ,       'test requires a `mps` backend support in `torch`'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(
	    is_transformers_available() and is_datasets_available()      ,       'test requires the Hugging Face suite'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(is_bnb_available()      ,       'test requires the bitsandbytes library'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(is_tpu_available()      ,       'test requires TPU'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(torch.cuda.device_count() == 1      ,       'test requires a GPU'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(torch.xpu.device_count() == 1      ,       'test requires a XPU'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(torch.cuda.device_count() > 1      ,       'test requires multiple GPUs'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(torch.xpu.device_count() > 1      ,       'test requires multiple XPUs'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(is_safetensors_available()      ,       'test requires safetensors'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(is_deepspeed_available()      ,       'test requires DeepSpeed'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(is_torch_version('>='      ,       '1.12.0'      )      ,       'test requires torch version >= 1.12.0'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a=None      ,       __a=None      ):


	if test_case is None:
		return partial(_UpperCamelCase      ,       version=_UpperCamelCase      )
	return unittest.skipUnless(is_torch_version('>='      ,       _UpperCamelCase      )      ,       f"""test requires torch version >= {version}"""      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(is_tensorboard_available()      ,       'test requires Tensorboard'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(is_wandb_available()      ,       'test requires wandb'      )(_UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(is_comet_ml_available()      ,       'test requires comet_ml'      )(_UpperCamelCase      )


_SCREAMING_SNAKE_CASE							=						(
    any([is_wandb_available(), is_tensorboard_available()]) and not is_comet_ml_available()
)


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	return unittest.skipUnless(
	    _atleast_one_tracker_available      ,       'test requires at least one tracker to be available and for `comet_ml` to not be installed'      ,       )(_UpperCamelCase      )
class SCREAMING_SNAKE_CASE_  (    unittest.TestCase    ):
						__magic_name__:	Union[str, Any]       					=				True






						@classmethod
						def UpperCAmelCase_ (					cls					:					Optional[int]		)							->			int:







							"""simple docstring"""


							snake_case_						:	Optional[Any]      =		tempfile.mkdtemp()






						@classmethod
						def UpperCAmelCase_ (					cls					:					Tuple		)							->			List[str]:







							"""simple docstring"""


							if os.path.exists(cls.tmpdir		):
								shutil.rmtree(cls.tmpdir		)






						def UpperCAmelCase_ (					self					:					int		)							->			Any:







							"""simple docstring"""


							if self.clear_on_setup:
								for path in Path(self.tmpdir		).glob('**/*'		):
									if path.is_file():
										path.unlink()
									elif path.is_dir():
										shutil.rmtree(_A		)
class SCREAMING_SNAKE_CASE_  (    unittest.TestCase    ):






						def UpperCAmelCase_ (					self					:					str		)							->			Optional[Any]:







							"""simple docstring"""


							super().tearDown()
							# Reset the state of the AcceleratorState singleton.
							AcceleratorState._reset_state()
							PartialState._reset_state()
class SCREAMING_SNAKE_CASE_  (    unittest.TestCase    ):






						def UpperCAmelCase_ (					self					:					List[str]						,      _A					:					Optional[int]		)							->			List[str]:







							"""simple docstring"""


							snake_case_						:	Optional[int]      =		mocks if isinstance(_A						,      (tuple, list)		) else [mocks]
							for m in self.mocks:
								m.start()
								self.addCleanup(m.stop		)


def 							SCREAMING_SNAKE_CASE__  (			__a      ):
	snake_case_						:	Union[str, Any]      =		AcceleratorState()
	snake_case_						:	str      =		tensor[None].clone().to(state.device      )
	snake_case_						:	Dict      =		gather(_UpperCamelCase      ).cpu()
	snake_case_						:	Any      =		tensor[0].cpu()
	for i in range(tensors.shape[0]      ):
		if not torch.equal(tensors[i]      ,       _UpperCamelCase      ):
			return False
	return True
class SCREAMING_SNAKE_CASE_  :






						def __init__(					self					:					Optional[int]						,      _A					:					Optional[int]						,      _A					:					str						,      _A					:					Dict		)							->			Tuple:







							"""simple docstring"""


							snake_case_						:	Optional[Any]      =		returncode
							snake_case_						:	Union[str, Any]      =		stdout
							snake_case_						:	List[str]      =		stderr


async def 							SCREAMING_SNAKE_CASE__  (			__a      ,       __a      ):


	while True:
		snake_case_						:	List[str]      =		await stream.readline()
		if line:
			callback(_UpperCamelCase      )
		else:
			break


async def 							SCREAMING_SNAKE_CASE__  (			__a      ,       __a=None      ,       __a=None      ,       __a=None      ,       __a=False      ,       __a=False      ):


	if echo:
		print('\nRunning: '      ,       ' '.join(_UpperCamelCase      )      )

	snake_case_						:	Optional[int]      =		await asyncio.create_subprocess_exec(
	    cmd[0]      ,       *cmd[1:]      ,       stdin=_UpperCamelCase      ,       stdout=asyncio.subprocess.PIPE      ,       stderr=asyncio.subprocess.PIPE      ,       env=_UpperCamelCase      ,       )

	# note: there is a warning for a possible deadlock when using `wait` with huge amounts of data in the pipe
	# https://docs.python.org/3/library/asyncio-subprocess.html#asyncio.asyncio.subprocess.Process.wait
	#
	# If it starts hanging, will need to switch to the following code. The problem is that no data
	# will be seen until it's done and if it hangs for example there will be no debug info.
	# out, err = await p.communicate()
	# return _RunOutput(p.returncode, out, err)

	snake_case_						:	Optional[Any]      =		[]
	snake_case_						:	Any      =		[]

	def tee(__a      ,       __a      ,       __a      ,       __a=""      ):
		snake_case_						:	List[str]      =		line.decode('utf-8'      ).rstrip()
		sink.append(_UpperCamelCase      )
		if not quiet:
			print(_UpperCamelCase      ,       _UpperCamelCase      ,       file=_UpperCamelCase      )

    # XXX: the timeout doesn't seem to make any difference here
	await asyncio.wait(
	    [
	        asyncio.create_task(_read_stream(p.stdout      ,       lambda __a      : tee(_UpperCamelCase      ,       _UpperCamelCase      ,       sys.stdout      ,       label='stdout:'      )      )      ),
	        asyncio.create_task(_read_stream(p.stderr      ,       lambda __a      : tee(_UpperCamelCase      ,       _UpperCamelCase      ,       sys.stderr      ,       label='stderr:'      )      )      ),
	    ]      ,       timeout=_UpperCamelCase      ,       )
	return _RunOutput(await p.wait()      ,       _UpperCamelCase      ,       _UpperCamelCase      )


def 							SCREAMING_SNAKE_CASE__  (			__a      ,       __a=None      ,       __a=None      ,       __a=1_80      ,       __a=False      ,       __a=True      ):
	snake_case_						:	int      =		asyncio.get_event_loop()
	snake_case_						:	Tuple      =		loop.run_until_complete(
	    _stream_subprocess(_UpperCamelCase      ,       env=_UpperCamelCase      ,       stdin=_UpperCamelCase      ,       timeout=_UpperCamelCase      ,       quiet=_UpperCamelCase      ,       echo=_UpperCamelCase      )      )

	snake_case_						:	Any      =		''' '''.join(_UpperCamelCase      )
	if result.returncode > 0:
		snake_case_						:	Union[str, Any]      =		'''\n'''.join(result.stderr      )
		raise RuntimeError(
		    f"""\'{cmd_str}\' failed with returncode {result.returncode}\n\n"""
		    f"""The combined stderr from workers follows:\n{stderr}"""      )

	return result
class SCREAMING_SNAKE_CASE_  (    _a    ):
						pass


def 							SCREAMING_SNAKE_CASE__  (			__a      ,       __a=False      ):


	try:
		snake_case_						:	Dict      =		subprocess.check_output(_UpperCamelCase      ,       stderr=subprocess.STDOUT      )
		if return_stdout:
			if hasattr(_UpperCamelCase      ,       'decode'      ):
				snake_case_						:	Optional[Any]      =		output.decode('utf-8'      )
			return output
	except subprocess.CalledProcessError as e:
		raise SubprocessCallException(
		    f"""Command `{' '.join(_UpperCamelCase      )}` failed with the following error:\n\n{e.output.decode()}"""      ) from e








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


try:
	if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	from ...utils.dummy_torch_and_transformers_objects import UnCLIPImageVariationPipeline, UnCLIPPipeline
else:
	from .pipeline_unclip import UnCLIPPipeline
	from .pipeline_unclip_image_variation import UnCLIPImageVariationPipeline
	from .text_proj import UnCLIPTextProjModel
