
'''simple docstring'''


import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__lowercase							:   str					=     logging.get_logger(__name__)
__lowercase							:   List[str]					=     {'''vocab_file''': '''spiece.model'''}

__lowercase							:   List[str]					=     {
    '''vocab_file''': {
        '''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/spiece.model''',
        '''albert-large-v1''': '''https://huggingface.co/albert-large-v1/resolve/main/spiece.model''',
        '''albert-xlarge-v1''': '''https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model''',
        '''albert-xxlarge-v1''': '''https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model''',
        '''albert-base-v2''': '''https://huggingface.co/albert-base-v2/resolve/main/spiece.model''',
        '''albert-large-v2''': '''https://huggingface.co/albert-large-v2/resolve/main/spiece.model''',
        '''albert-xlarge-v2''': '''https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model''',
        '''albert-xxlarge-v2''': '''https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model''',
    }
}

__lowercase							:   List[str]					=     {
    '''albert-base-v1''': 512,
    '''albert-large-v1''': 512,
    '''albert-xlarge-v1''': 512,
    '''albert-xxlarge-v1''': 512,
    '''albert-base-v2''': 512,
    '''albert-large-v2''': 512,
    '''albert-xlarge-v2''': 512,
    '''albert-xxlarge-v2''': 512,
}

__lowercase							:   Optional[Any]					=     '''▁'''

class 	__lowercase				(  _lowercase    ):
			lowerCamelCase			:		Tuple	      =			VOCAB_FILES_NAMES
			lowerCamelCase			:		Union[str, Any]	      =			PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase			:		List[str]	      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES

			def __init__(self			,   A			,   A=True			,   A=True			,   A=False			,   A="[CLS]"			,   A="[SEP]"			,   A="<unk>"			,   A="[SEP]"			,   A="<pad>"			,   A="[CLS]"			,   A="[MASK]"			,   A = None			,   **A			,   ):
								# Mask token behave like a normal word, i.e. include the space before it and
								# is included in the raw text, there should be a match in a non-normalized sentence.
								lowerCamelCase_					:      Dict     =		(
								    AddedToken(A			,   lstrip=A			,   rstrip=A			,   normalized=A      )
								    if isinstance(A			,   A      )
								    else mask_token
								)

								lowerCamelCase_					:      Any     =		{} if sp_model_kwargs is None else sp_model_kwargs

								super().__init__(
								    do_lower_case=A			,   remove_space=A			,   keep_accents=A			,   bos_token=A			,   eos_token=A			,   unk_token=A			,   sep_token=A			,   pad_token=A			,   cls_token=A			,   mask_token=A			,   sp_model_kwargs=self.sp_model_kwargs			,   **A			,   )

								lowerCamelCase_					:      str     =		do_lower_case
								lowerCamelCase_					:      Dict     =		remove_space
								lowerCamelCase_					:      Union[str, Any]     =		keep_accents
								lowerCamelCase_					:      List[str]     =		vocab_file

								lowerCamelCase_					:      int     =		spm.SentencePieceProcessor(**self.sp_model_kwargs      )
								self.sp_model.Load(A      )

			@property
			def        UpperCAmelCase__ (self      ):
								return len(self.sp_model      )

			def        UpperCAmelCase__ (self      ):
								lowerCamelCase_					:      List[str]     =		{self.convert_ids_to_tokens(A      ): i for i in range(self.vocab_size      )}
								vocab.update(self.added_tokens_encoder      )
								return vocab

			def __getstate__(self      ):
								lowerCamelCase_					:      Any     =		self.__dict__.copy()
								lowerCamelCase_					:      int     =		None
								return state

			def __setstate__(self			,   A      ):
								lowerCamelCase_					:      Optional[int]     =		d

								# for backward compatibility
								if not hasattr(self			,   '''sp_model_kwargs'''      ):
													lowerCamelCase_					:      Optional[Any]     =		{}

								lowerCamelCase_					:      str     =		spm.SentencePieceProcessor(**self.sp_model_kwargs      )
								self.sp_model.Load(self.vocab_file      )

			def        UpperCAmelCase__ (self			,   A      ):
								if self.remove_space:
													lowerCamelCase_					:      Union[str, Any]     =		''' '''.join(inputs.strip().split()      )
								else:
													lowerCamelCase_					:      Tuple     =		inputs
								lowerCamelCase_					:      str     =		outputs.replace('''``'''			,   '''"'''      ).replace('''\'\''''			,   '''"'''      )

								if not self.keep_accents:
													lowerCamelCase_					:      int     =		unicodedata.normalize('''NFKD'''			,   A      )
													lowerCamelCase_					:      Optional[Any]     =		''''''.join([c for c in outputs if not unicodedata.combining(A      )]      )
								if self.do_lower_case:
													lowerCamelCase_					:      Union[str, Any]     =		outputs.lower()

								return outputs

			def        UpperCAmelCase__ (self			,   A      ):
								lowerCamelCase_					:      Optional[Any]     =		self.preprocess_text(A      )
								lowerCamelCase_					:      Dict     =		self.sp_model.encode(A			,   out_type=A      )
								lowerCamelCase_					:      Union[str, Any]     =		[]
								for piece in pieces:
													if len(A      ) > 1 and piece[-1] == str(''','''      ) and piece[-2].isdigit():
																		lowerCamelCase_					:      Tuple     =		self.sp_model.EncodeAsPieces(piece[:-1].replace(A			,   ''''''      )      )
																		if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																							if len(cur_pieces[0]      ) == 1:
																												lowerCamelCase_					:      Optional[int]     =		cur_pieces[1:]
																							else:
																												lowerCamelCase_					:      List[str]     =		cur_pieces[0][1:]
																		cur_pieces.append(piece[-1]      )
																		new_pieces.extend(A      )
													else:
																		new_pieces.append(A      )

								return new_pieces

			def        UpperCAmelCase__ (self			,   A      ):
								return self.sp_model.PieceToId(A      )

			def        UpperCAmelCase__ (self			,   A      ):
								return self.sp_model.IdToPiece(A      )

			def        UpperCAmelCase__ (self			,   A      ):
								lowerCamelCase_					:      Optional[int]     =		[]
								lowerCamelCase_					:      List[Any]     =		''''''
								lowerCamelCase_					:      str     =		False
								for token in tokens:
													# make sure that special tokens are not decoded using sentencepiece model
													if token in self.all_special_tokens:
																		if not prev_is_special:
																							out_string += " "
																		out_string += self.sp_model.decode(A      ) + token
																		lowerCamelCase_					:      Dict     =		True
																		lowerCamelCase_					:      List[str]     =		[]
													else:
																		current_sub_tokens.append(A      )
																		lowerCamelCase_					:      str     =		False
								out_string += self.sp_model.decode(A      )
								return out_string.strip()

			def        UpperCAmelCase__ (self			,   A			,   A = None      ):
								lowerCamelCase_					:      Optional[Any]     =		[self.sep_token_id]
								lowerCamelCase_					:      Optional[Any]     =		[self.cls_token_id]
								if token_ids_a is None:
													return cls + token_ids_a + sep
								return cls + token_ids_a + sep + token_ids_a + sep

			def        UpperCAmelCase__ (self			,   A			,   A = None			,   A = False      ):

								if already_has_special_tokens:
													return super().get_special_tokens_mask(
													    token_ids_a=A			,   token_ids_a=A			,   already_has_special_tokens=A      )

								if token_ids_a is not None:
													return [1] + ([0] * len(A      )) + [1] + ([0] * len(A      )) + [1]
								return [1] + ([0] * len(A      )) + [1]

			def        UpperCAmelCase__ (self			,   A			,   A = None      ):
								lowerCamelCase_					:      Tuple     =		[self.sep_token_id]
								lowerCamelCase_					:      Tuple     =		[self.cls_token_id]

								if token_ids_a is None:
													return len(cls + token_ids_a + sep      ) * [0]
								return len(cls + token_ids_a + sep      ) * [0] + len(token_ids_a + sep      ) * [1]






			def        UpperCAmelCase__ (self			,   A			,   A = None      ):
								if not os.path.isdir(A      ):
													logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""      )
													return
								lowerCamelCase_					:      Any     =		os.path.join(
								    A			,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )

								if os.path.abspath(self.vocab_file      ) != os.path.abspath(A      ) and os.path.isfile(self.vocab_file      ):
													copyfile(self.vocab_file			,   A      )
								elif not os.path.isfile(self.vocab_file      ):
													with open(A			,   '''wb'''      ) as fi:
																		lowerCamelCase_					:      Any     =		self.sp_model.serialized_model_proto()
																		fi.write(A      )

								return (out_vocab_file,)




'''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 lowercase_	(   _lowercase			,       _lowercase=False				)     ->							int:
					'''simple docstring'''

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


__lowercase							:   Union[str, Any]					=     parse_flag_from_env('''RUN_SLOW''', default=False)




def lowercase_	(   _lowercase				)     ->							Union[str, Any]:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							Optional[Any]:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							List[str]:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							str:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							str:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							List[str]:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							Tuple:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							Tuple:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							Union[str, Any]:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							Union[str, Any]:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							List[str]:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							Tuple:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							str:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							Tuple:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							int:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							Union[str, Any]:
					'''simple docstring'''

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




def lowercase_	(   _lowercase=None			,       _lowercase=None				)     ->							Any:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							str:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							Union[str, Any]:
					'''simple docstring'''

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




def lowercase_	(   _lowercase				)     ->							int:
					'''simple docstring'''

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


__lowercase							:   str					=     (
    any([is_wandb_available(), is_tensorboard_available()]) and not is_comet_ml_available()
)




def lowercase_	(   _lowercase				)     ->							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'''			,       )(_lowercase				)

class 	__lowercase				(  unittest.TestCase    ):
			lowerCamelCase			:		Optional[Any]	      =			True

			@classmethod
			def        UpperCAmelCase__ (cls      ):
								lowerCamelCase_					:      Optional[Any]     =		tempfile.mkdtemp()

			@classmethod
			def        UpperCAmelCase__ (cls      ):
								if os.path.exists(cls.tmpdir      ):
													shutil.rmtree(cls.tmpdir      )






			def        UpperCAmelCase__ (self      ):
								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 	__lowercase				(  unittest.TestCase    ):

			def        UpperCAmelCase__ (self      ):
								super().tearDown()
								# Reset the state of the AcceleratorState singleton.
								AcceleratorState._reset_state()
								PartialState._reset_state()

class 	__lowercase				(  unittest.TestCase    ):

			def        UpperCAmelCase__ (self			,   A      ):
								lowerCamelCase_					:      List[str]     =		mocks if isinstance(A			,   (tuple, list)      ) else [mocks]
								for m in self.mocks:
													m.start()
													self.addCleanup(m.stop      )




def lowercase_	(   _lowercase				)     ->							Optional[int]:
					'''simple docstring'''

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

class 	__lowercase				:

			def __init__(self			,   A			,   A			,   A      ):
								lowerCamelCase_					:      List[Any]     =		returncode
								lowerCamelCase_					:      Optional[int]     =		stdout
								lowerCamelCase_					:      List[str]     =		stderr




async def lowercase_	(   _lowercase			,       _lowercase				)     ->							Tuple:
					'''simple docstring'''

					while True:
										lowerCamelCase_					:      Any     =		await stream.readline()
										if line:
															callback(_lowercase				)
										else:
															break




async def lowercase_	(   _lowercase			,       _lowercase=None			,       _lowercase=None			,       _lowercase=None			,       _lowercase=False			,       _lowercase=False				)     ->							_RunOutput:
					'''simple docstring'''

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

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

					# 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)

					lowerCamelCase_					:      List[Any]     =		[]
					lowerCamelCase_					:      Optional[int]     =		[]

					def tee(_lowercase			,       _lowercase			,       _lowercase			,       _lowercase=""				):
										lowerCamelCase_					:      Union[str, Any]     =		line.decode('''utf-8'''				).rstrip()
										sink.append(_lowercase				)
										if not quiet:
															print(_lowercase			,       _lowercase			,       file=_lowercase				)

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




def lowercase_	(   _lowercase			,       _lowercase=None			,       _lowercase=None			,       _lowercase=180			,       _lowercase=False			,       _lowercase=True				)     ->							_RunOutput:
					'''simple docstring'''

					lowerCamelCase_					:      Any     =		asyncio.get_event_loop()
					lowerCamelCase_					:      List[str]     =		loop.run_until_complete(
					    _stream_subprocess(_lowercase			,       env=_lowercase			,       stdin=_lowercase			,       timeout=_lowercase			,       quiet=_lowercase			,       echo=_lowercase				)				)

					lowerCamelCase_					:      List[Any]     =		''' '''.join(_lowercase				)
					if result.returncode > 0:
										lowerCamelCase_					:      Optional[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 	__lowercase				(  _lowercase    ):
			pass




def lowercase_	(   _lowercase			,       _lowercase=False				)     ->							Dict:
					'''simple docstring'''

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


