




'''simple docstring'''
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 			lowerCamelCase(							SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_=False     )		->		str:
			try:
						A_									= os.environ[key]
			except KeyError:
						# KEY isn't set, default to `default`.
						A_									= default
			else:
						# KEY is set, convert it to True or False.
						try:
									A_									= strtobool(SCREAMING_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


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





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Tuple:
			return unittest.skip('Test was skipped'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Tuple:
			return unittest.skipUnless(_run_slow_tests       ,'test is slow'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Any:
			return unittest.skipUnless(not torch.cuda.is_available()       ,'test requires only a CPU'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Dict:
			return unittest.skipUnless(torch.cuda.is_available()       ,'test requires a GPU'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Any:
			return unittest.skipUnless(is_xpu_available()       ,'test requires a XPU'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Any:
			return unittest.skipUnless(is_mps_available()       ,'test requires a `mps` backend support in `torch`'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		List[str]:
			return unittest.skipUnless(
			    is_transformers_available() and is_datasets_available()       ,'test requires the Hugging Face suite'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		List[Any]:
			return unittest.skipUnless(is_bnb_available()       ,'test requires the bitsandbytes library'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Union[str, Any]:
			return unittest.skipUnless(is_tpu_available()       ,'test requires TPU'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Dict:
			return unittest.skipUnless(torch.cuda.device_count() == 1       ,'test requires a GPU'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Any:
			return unittest.skipUnless(torch.xpu.device_count() == 1       ,'test requires a XPU'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Optional[int]:
			return unittest.skipUnless(torch.cuda.device_count() > 1       ,'test requires multiple GPUs'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Tuple:
			return unittest.skipUnless(torch.xpu.device_count() > 1       ,'test requires multiple XPUs'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Optional[Any]:
			return unittest.skipUnless(is_safetensors_available()       ,'test requires safetensors'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Union[str, Any]:
			return unittest.skipUnless(is_deepspeed_available()       ,'test requires DeepSpeed'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Tuple:
			return unittest.skipUnless(is_torch_version('>='       ,'1.12.0'     )       ,'test requires torch version >= 1.12.0'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_=None       ,SCREAMING_SNAKE_CASE_=None     )		->		List[str]:
			if test_case is None:
						return partial(SCREAMING_SNAKE_CASE_       ,version=SCREAMING_SNAKE_CASE_     )
			return unittest.skipUnless(is_torch_version('>='       ,SCREAMING_SNAKE_CASE_     )       ,F'test requires torch version >= {version}'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Dict:
			return unittest.skipUnless(is_tensorboard_available()       ,'test requires Tensorboard'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Tuple:
			return unittest.skipUnless(is_wandb_available()       ,'test requires wandb'     )(SCREAMING_SNAKE_CASE_     )





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Tuple:
			return unittest.skipUnless(is_comet_ml_available()       ,'test requires comet_ml'     )(SCREAMING_SNAKE_CASE_     )


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





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Dict:
			return unittest.skipUnless(
			    _atleast_one_tracker_available       ,'test requires at least one tracker to be available and for `comet_ml` to not be installed'       ,)(SCREAMING_SNAKE_CASE_     )
class   __UpperCAmelCase				(     unittest.TestCase				):



					'''simple docstring'''





					_UpperCamelCase							=		True



					@classmethod
					def     __snake_case						(	cls     :						Tuple)    ->							List[str]:
								A_									= tempfile.mkdtemp()



					@classmethod
					def     __snake_case						(	cls     :						str)    ->							str:
								if os.path.exists(cls.tmpdir):
											shutil.rmtree(cls.tmpdir)



					def     __snake_case						(	self     :						int)    ->							Tuple:
								if self.clear_on_setup:
											for path in Path(self.tmpdir).glob('**/*'):
														if path.is_file():
																	path.unlink()
														elif path.is_dir():
																	shutil.rmtree(_lowercase)





class   __UpperCAmelCase				(     unittest.TestCase				):



					'''simple docstring'''





					def     __snake_case						(	self     :						Dict)    ->							Any:
								super().tearDown()
								# Reset the state of the AcceleratorState singleton.
								AcceleratorState._reset_state()
								PartialState._reset_state()





class   __UpperCAmelCase				(     unittest.TestCase				):



					'''simple docstring'''





					def     __snake_case						(	self     :						Optional[Any]      ,       _lowercase     :						Union[mock.Mock, List[mock.Mock]])    ->							Any:
								A_									= mocks if isinstance(_lowercase      ,       (tuple, list)) else [mocks]
								for m in self.mocks:
											m.start()
											self.addCleanup(m.stop)





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		int:
			A_									= AcceleratorState()
			A_									= tensor[None].clone().to(state.device     )
			A_									= gather(SCREAMING_SNAKE_CASE_     ).cpu()
			A_									= tensor[0].cpu()
			for i in range(tensors.shape[0]     ):
						if not torch.equal(tensors[i]       ,SCREAMING_SNAKE_CASE_     ):
									return False
			return True
class   __UpperCAmelCase				:



					'''simple docstring'''





					def __init__(	self     :						Optional[Any]      ,       _lowercase     :						Dict      ,       _lowercase     :						Optional[int]      ,       _lowercase     :						Optional[int])    ->							Union[str, Any]:
								A_									= returncode
								A_									= stdout
								A_									= stderr





async def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_     )		->		Union[str, Any]:
			while True:
						A_									= await stream.readline()
						if line:
									callback(SCREAMING_SNAKE_CASE_     )
						else:
									break





async def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_=None       ,SCREAMING_SNAKE_CASE_=None       ,SCREAMING_SNAKE_CASE_=None       ,SCREAMING_SNAKE_CASE_=False       ,SCREAMING_SNAKE_CASE_=False     )		->		_RunOutput:
			if echo:
						print('\nRunning: '       ,' '.join(SCREAMING_SNAKE_CASE_     )     )

			A_									= await asyncio.create_subprocess_exec(
			    cmd[0]       ,*cmd[1:]       ,stdin=SCREAMING_SNAKE_CASE_       ,stdout=asyncio.subprocess.PIPE       ,stderr=asyncio.subprocess.PIPE       ,env=SCREAMING_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)

			A_									= []
			A_									= []

			def tee(SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_=""     ):
						A_									= line.decode('utf-8'     ).rstrip()
						sink.append(SCREAMING_SNAKE_CASE_     )
						if not quiet:
									print(SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_       ,file=SCREAMING_SNAKE_CASE_     )

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





def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_=None       ,SCREAMING_SNAKE_CASE_=None       ,SCREAMING_SNAKE_CASE_=180       ,SCREAMING_SNAKE_CASE_=False       ,SCREAMING_SNAKE_CASE_=True     )		->		_RunOutput:
			A_									= asyncio.get_event_loop()
			A_									= loop.run_until_complete(
			    _stream_subprocess(SCREAMING_SNAKE_CASE_       ,env=SCREAMING_SNAKE_CASE_       ,stdin=SCREAMING_SNAKE_CASE_       ,timeout=SCREAMING_SNAKE_CASE_       ,quiet=SCREAMING_SNAKE_CASE_       ,echo=SCREAMING_SNAKE_CASE_     )     )

			A_									= ' '.join(SCREAMING_SNAKE_CASE_     )
			if result.returncode > 0:
						A_									= '\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   __UpperCAmelCase				(     lowerCAmelCase				):



					'''simple docstring'''





					pass





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










'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


_SCREAMING_SNAKE_CASE			=						logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE			=						{
    "facebook/dpr-ctx_encoder-single-nq-base": (
        "https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json"
    ),
    "facebook/dpr-question_encoder-single-nq-base": (
        "https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json"
    ),
    "facebook/dpr-reader-single-nq-base": (
        "https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json"
    ),
    "facebook/dpr-ctx_encoder-multiset-base": (
        "https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json"
    ),
    "facebook/dpr-question_encoder-multiset-base": (
        "https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json"
    ),
    "facebook/dpr-reader-multiset-base": (
        "https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json"
    ),
}
class   __UpperCAmelCase				(     lowerCAmelCase				):



					'''simple docstring'''





					_UpperCamelCase							=		"""dpr"""



					def __init__(	self     :						Optional[Any]      ,       _lowercase     :						Dict=30_522      ,       _lowercase     :						Tuple=768      ,       _lowercase     :						int=12      ,       _lowercase     :						List[str]=12      ,       _lowercase     :						Union[str, Any]=3_072      ,       _lowercase     :						Dict="gelu"      ,       _lowercase     :						Dict=0.1      ,       _lowercase     :						Any=0.1      ,       _lowercase     :						Union[str, Any]=512      ,       _lowercase     :						Optional[int]=2      ,       _lowercase     :						Union[str, Any]=0.02      ,       _lowercase     :						List[Any]=1E-12      ,       _lowercase     :						List[str]=0      ,       _lowercase     :						Dict="absolute"      ,       _lowercase     :						int = 0      ,       **_lowercase     :						int      ,       )    ->							int:
								super().__init__(pad_token_id=_lowercase      ,       **_lowercase)

								A_									= vocab_size
								A_									= hidden_size
								A_									= num_hidden_layers
								A_									= num_attention_heads
								A_									= hidden_act
								A_									= intermediate_size
								A_									= hidden_dropout_prob
								A_									= attention_probs_dropout_prob
								A_									= max_position_embeddings
								A_									= type_vocab_size
								A_									= initializer_range
								A_									= layer_norm_eps
								A_									= projection_dim
								A_									= position_embedding_type




