




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


__A        =    {"configuration_fnet": ["FNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FNetConfig"]}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__A        =    ["FNetTokenizer"]

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__A        =    ["FNetTokenizerFast"]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__A        =    [
					    "FNET_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "FNetForMaskedLM",
					    "FNetForMultipleChoice",
					    "FNetForNextSentencePrediction",
					    "FNetForPreTraining",
					    "FNetForQuestionAnswering",
					    "FNetForSequenceClassification",
					    "FNetForTokenClassification",
					    "FNetLayer",
					    "FNetModel",
					    "FNetPreTrainedModel",
					]


if TYPE_CHECKING:
					from .configuration_fnet import FNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FNetConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_fnet import FNetTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_fnet_fast import FNetTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_fnet import (
										    FNET_PRETRAINED_MODEL_ARCHIVE_LIST,
										    FNetForMaskedLM,
										    FNetForMultipleChoice,
										    FNetForNextSentencePrediction,
										    FNetForPreTraining,
										    FNetForQuestionAnswering,
										    FNetForSequenceClassification,
										    FNetForTokenClassification,
										    FNetLayer,
										    FNetModel,
										    FNetPreTrainedModel,
										)


else:
					import sys

					__A        =    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










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      lowercase__      (     __snake_case    :							List[Any]     ,       __snake_case    :							List[str]=False  ):


					'''simple docstring'''


					try:
										UpperCAmelCase_    :      int            =						os.environ[key]
					except KeyError:
										# KEY isn't set, default to `default`.
										UpperCAmelCase_    :      Optional[int]            =						default
					else:
										# KEY is set, convert it to True or False.
										try:
															UpperCAmelCase_    :      List[Any]            =						strtobool(__snake_case  )
										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


__UpperCAmelCase								=						parse_flag_from_env('RUN_SLOW', default=False)




def      lowercase__      (     __snake_case    :							int  ):


					'''simple docstring'''


					return unittest.skip('Test was skipped'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							Tuple  ):


					'''simple docstring'''


					return unittest.skipUnless(_run_slow_tests     ,       'test is slow'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							List[str]  ):


					'''simple docstring'''


					return unittest.skipUnless(not torch.cuda.is_available()     ,       'test requires only a CPU'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							Tuple  ):


					'''simple docstring'''


					return unittest.skipUnless(torch.cuda.is_available()     ,       'test requires a GPU'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							List[str]  ):


					'''simple docstring'''


					return unittest.skipUnless(is_xpu_available()     ,       'test requires a XPU'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							str  ):


					'''simple docstring'''


					return unittest.skipUnless(is_mps_available()     ,       'test requires a `mps` backend support in `torch`'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							Tuple  ):


					'''simple docstring'''


					return unittest.skipUnless(
					    is_transformers_available() and is_datasets_available()     ,       'test requires the Hugging Face suite'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							str  ):


					'''simple docstring'''


					return unittest.skipUnless(is_bnb_available()     ,       'test requires the bitsandbytes library'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							Dict  ):


					'''simple docstring'''


					return unittest.skipUnless(is_tpu_available()     ,       'test requires TPU'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							Tuple  ):


					'''simple docstring'''


					return unittest.skipUnless(torch.cuda.device_count() == 1     ,       'test requires a GPU'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							Dict  ):


					'''simple docstring'''


					return unittest.skipUnless(torch.xpu.device_count() == 1     ,       'test requires a XPU'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							Optional[int]  ):


					'''simple docstring'''


					return unittest.skipUnless(torch.cuda.device_count() > 1     ,       'test requires multiple GPUs'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							int  ):


					'''simple docstring'''


					return unittest.skipUnless(torch.xpu.device_count() > 1     ,       'test requires multiple XPUs'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							Dict  ):


					'''simple docstring'''


					return unittest.skipUnless(is_safetensors_available()     ,       'test requires safetensors'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							Tuple  ):


					'''simple docstring'''


					return unittest.skipUnless(is_deepspeed_available()     ,       'test requires DeepSpeed'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							List[Any]  ):


					'''simple docstring'''


					return unittest.skipUnless(is_torch_version('>='     ,       '1.12.0'  )     ,       'test requires torch version >= 1.12.0'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							Dict=None     ,       __snake_case    :							Dict=None  ):


					'''simple docstring'''


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




def      lowercase__      (     __snake_case    :							str  ):


					'''simple docstring'''


					return unittest.skipUnless(is_tensorboard_available()     ,       'test requires Tensorboard'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							List[str]  ):


					'''simple docstring'''


					return unittest.skipUnless(is_wandb_available()     ,       'test requires wandb'  )(__snake_case  )




def      lowercase__      (     __snake_case    :							str  ):


					'''simple docstring'''


					return unittest.skipUnless(is_comet_ml_available()     ,       'test requires comet_ml'  )(__snake_case  )


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




def      lowercase__      (     __snake_case    :							List[Any]  ):


					'''simple docstring'''


					return unittest.skipUnless(
					    _atleast_one_tracker_available     ,       'test requires at least one tracker to be available and for `comet_ml` to not be installed'     ,       )(__snake_case  )



class   lowerCamelCase      (unittest.TestCase			):







		'''simple docstring'''



		_snake_case    :    Union[str, Any]       						=  True



		@classmethod
		def 					__UpperCAmelCase			(							cls   )	->							Union[str, Any]:
							UpperCAmelCase_    :      List[Any]            =						tempfile.mkdtemp()



		@classmethod
		def 					__UpperCAmelCase			(							cls   )	->							List[str]:
							if os.path.exists(cls.tmpdir   ):
												shutil.rmtree(cls.tmpdir   )



		def 					__UpperCAmelCase			(							self   )	->							str:
							if self.clear_on_setup:
												for path in Path(self.tmpdir   ).glob('**/*'   ):
																	if path.is_file():
																						path.unlink()
																	elif path.is_dir():
																						shutil.rmtree(_UpperCamelCase   )





class   lowerCamelCase      (unittest.TestCase			):







		'''simple docstring'''



		def 					__UpperCAmelCase			(							self   )	->							Optional[int]:
							super().tearDown()
							# Reset the state of the AcceleratorState singleton.
							AcceleratorState._reset_state()
							PartialState._reset_state()





class   lowerCamelCase      (unittest.TestCase			):







		'''simple docstring'''



		def 					__UpperCAmelCase			(							self				,		_UpperCamelCase   )	->							Any:
							UpperCAmelCase_    :      List[Any]            =						mocks if isinstance(_UpperCamelCase				,		(tuple, list)   ) else [mocks]
							for m in self.mocks:
												m.start()
												self.addCleanup(m.stop   )





def      lowercase__      (     __snake_case    :							int  ):


					'''simple docstring'''


					UpperCAmelCase_    :      int            =						AcceleratorState()
					UpperCAmelCase_    :      str            =						tensor[None].clone().to(state.device  )
					UpperCAmelCase_    :      List[str]            =						gather(__snake_case  ).cpu()
					UpperCAmelCase_    :      List[Any]            =						tensor[0].cpu()
					for i in range(tensors.shape[0]  ):
										if not torch.equal(tensors[i]     ,       __snake_case  ):
															return False
					return True



class   lowerCamelCase      :







		'''simple docstring'''



		def __init__(							self				,		_UpperCamelCase				,		_UpperCamelCase				,		_UpperCamelCase   )	->							Any:
							UpperCAmelCase_    :      str            =						returncode
							UpperCAmelCase_    :      Optional[Any]            =						stdout
							UpperCAmelCase_    :      Optional[Any]            =						stderr





async def      lowercase__      (     __snake_case    :							Optional[Any]     ,       __snake_case    :							Optional[int]  ):


					'''simple docstring'''


					while True:
										UpperCAmelCase_    :      Dict            =						await stream.readline()
										if line:
															callback(__snake_case  )
										else:
															break




async def      lowercase__      (     __snake_case    :							Optional[int]     ,       __snake_case    :							Dict=None     ,       __snake_case    :							str=None     ,       __snake_case    :							Dict=None     ,       __snake_case    :							List[str]=False     ,       __snake_case    :							Optional[int]=False  ):


					'''simple docstring'''


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

					UpperCAmelCase_    :      Optional[Any]            =						await asyncio.create_subprocess_exec(
					    cmd[0]     ,       *cmd[1:]     ,       stdin=__snake_case     ,       stdout=asyncio.subprocess.PIPE     ,       stderr=asyncio.subprocess.PIPE     ,       env=__snake_case     ,       )

					# 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)

					UpperCAmelCase_    :      Any            =						[]
					UpperCAmelCase_    :      str            =						[]

					def tee(__snake_case    :							Dict     ,       __snake_case    :							Union[str, Any]     ,       __snake_case    :							Tuple     ,       __snake_case    :							Optional[int]=""  ):
										UpperCAmelCase_    :      List[str]            =						line.decode('utf-8'  ).rstrip()
										sink.append(__snake_case  )
										if not quiet:
															print(__snake_case     ,       __snake_case     ,       file=__snake_case  )

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




def      lowercase__      (     __snake_case    :							Optional[Any]     ,       __snake_case    :							List[Any]=None     ,       __snake_case    :							str=None     ,       __snake_case    :							Tuple=180     ,       __snake_case    :							Dict=False     ,       __snake_case    :							Optional[Any]=True  ):


					'''simple docstring'''


					UpperCAmelCase_    :      str            =						asyncio.get_event_loop()
					UpperCAmelCase_    :      int            =						loop.run_until_complete(
					    _stream_subprocess(__snake_case     ,       env=__snake_case     ,       stdin=__snake_case     ,       timeout=__snake_case     ,       quiet=__snake_case     ,       echo=__snake_case  )  )

					UpperCAmelCase_    :      int            =						' '.join(__snake_case  )
					if result.returncode > 0:
										UpperCAmelCase_    :      int            =						'\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   lowerCamelCase      (_snake_case			):







		'''simple docstring'''



		pass





def      lowercase__      (     __snake_case    :							List[str]     ,       __snake_case    :							List[Any]=False  ):


					'''simple docstring'''


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






