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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowercase        =  logging.get_logger(__name__)

lowercase        =  '''▁'''

lowercase        =  {'''vocab_file''': '''sentencepiece.bpe.model'''}

lowercase        =  {
    '''vocab_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model''',
    }
}

lowercase        =  {
    '''facebook/xglm-564M''': 2_0_4_8,
}





class       __A(				lowercase__       ):
					SCREAMING_SNAKE_CASE			    =    VOCAB_FILES_NAMES
					SCREAMING_SNAKE_CASE			    =    PRETRAINED_VOCAB_FILES_MAP
					SCREAMING_SNAKE_CASE			    =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					SCREAMING_SNAKE_CASE			    =    ['''input_ids''', '''attention_mask''']

					def __init__(	self					:     Dict   ,					__UpperCamelCase					:     Optional[int]   ,					__UpperCamelCase					:     List[Any]="<s>"   ,					__UpperCamelCase					:     int="</s>"   ,					__UpperCamelCase					:     Optional[Any]="</s>"   ,					__UpperCamelCase					:     Optional[Any]="<s>"   ,					__UpperCamelCase					:     Any="<unk>"   ,					__UpperCamelCase					:     Any="<pad>"   ,					__UpperCamelCase					:     Optional[Dict[str, Any]] = None   ,					**__UpperCamelCase					:     Optional[int]   ,					):
												lowerCamelCase_							  =					{} if sp_model_kwargs is None else sp_model_kwargs

												# Compatibility with the original tokenizer
												lowerCamelCase_							  =					7
												lowerCamelCase_							  =					[F'''<madeupword{i}>''' for i in range(self.num_madeup_words   )]

												lowerCamelCase_							  =					kwargs.get("""additional_special_tokens"""   ,					[]   )
												kwargs["additional_special_tokens"] += [
												    word for word in madeup_words if word not in kwargs["additional_special_tokens"]
												]

												super().__init__(
												    bos_token=UpperCAmelCase__   ,					eos_token=UpperCAmelCase__   ,					unk_token=UpperCAmelCase__   ,					sep_token=UpperCAmelCase__   ,					cls_token=UpperCAmelCase__   ,					pad_token=UpperCAmelCase__   ,					sp_model_kwargs=self.sp_model_kwargs   ,					**UpperCAmelCase__   ,					)

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

												# Original fairseq vocab and spm vocab must be "aligned":
												# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
												# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
												# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
												# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

												# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
												lowerCamelCase_							  =					1

												# Mimic fairseq token-to-id alignment for the first 4 token
												lowerCamelCase_							  =					{'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

												lowerCamelCase_							  =					len(self.sp_model   )
												lowerCamelCase_							  =					{F'''<madeupword{i}>''': sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words   )}
												self.fairseq_tokens_to_ids.update(UpperCAmelCase__   )

												lowerCamelCase_							  =					{v: k for k, v in self.fairseq_tokens_to_ids.items()}

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

					def __setstate__(	self					:     Optional[Any]   ,					__UpperCamelCase					:     Any   ):
												lowerCamelCase_							  =					d

												# for backward compatibility
												if not hasattr(self   ,					"""sp_model_kwargs"""   ):
																			lowerCamelCase_							  =					{}

												lowerCamelCase_							  =					spm.SentencePieceProcessor(**self.sp_model_kwargs   )
												self.sp_model.LoadFromSerializedProto(self.sp_model_proto   )

					def    lowercase__      (	self					:     str   ,					__UpperCamelCase					:     List[int]   ,					__UpperCamelCase					:     Optional[List[int]] = None   ):

												if token_ids_a is None:
																			return [self.sep_token_id] + token_ids_a
												lowerCamelCase_							  =					[self.sep_token_id]
												return sep + token_ids_a + sep + sep + token_ids_a

					def    lowercase__      (	self					:     Any   ,					__UpperCamelCase					:     List[int]   ,					__UpperCamelCase					:     Optional[List[int]] = None   ,					__UpperCamelCase					:     bool = False   ):

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

												if token_ids_a is None:
																			return [1] + ([0] * len(UpperCAmelCase__   ))
												return [1] + ([0] * len(UpperCAmelCase__   )) + [1, 1] + ([0] * len(UpperCAmelCase__   ))

					def    lowercase__      (	self					:     Dict   ,					__UpperCamelCase					:     List[int]   ,					__UpperCamelCase					:     Optional[List[int]] = None   ):
												lowerCamelCase_							  =					[self.sep_token_id]

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

					@property
					def    lowercase__      (	self					:     Dict   ):
												return len(self.sp_model   ) + self.fairseq_offset + self.num_madeup_words

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

					def    lowercase__      (	self					:     Tuple   ,					__UpperCamelCase					:     str   ):
												return self.sp_model.encode(UpperCAmelCase__   ,					out_type=UpperCAmelCase__   )

					def    lowercase__      (	self					:     Dict   ,					__UpperCamelCase					:     Optional[Any]   ):
												if token in self.fairseq_tokens_to_ids:
																			return self.fairseq_tokens_to_ids[token]
												lowerCamelCase_							  =					self.sp_model.PieceToId(UpperCAmelCase__   )

												# Need to return unknown token if the SP model returned 0
												return spm_id + self.fairseq_offset if spm_id else self.unk_token_id

					def    lowercase__      (	self					:     Optional[Any]   ,					__UpperCamelCase					:     Any   ):
												if index in self.fairseq_ids_to_tokens:
																			return self.fairseq_ids_to_tokens[index]
												return self.sp_model.IdToPiece(index - self.fairseq_offset   )

					def    lowercase__      (	self					:     List[str]   ,					__UpperCamelCase					:     Optional[Any]   ):
												lowerCamelCase_							  =					''''''.join(UpperCAmelCase__   ).replace(UpperCAmelCase__   ,					""" """   ).strip()
												return out_string



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

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

												return (out_vocab_file,)







import os
import socket
from contextlib import contextmanager

import torch

from ..commands.config.default import write_basic_config  # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import convert_model
from .versions import is_torch_version


if is_deepspeed_available():
		from deepspeed import DeepSpeedEngine

if is_tpu_available(check_device=False):
		import torch_xla.core.xla_model as xm



def      __lowerCAmelCase						(							UpperCAmelCase__				:      Any       )  ->    List[str]:
							if is_torch_version("""<"""			,				"""2.0.0"""       ) or not hasattr(UpperCAmelCase__			,				"""_dynamo"""       ):
														return False
							return isinstance(UpperCAmelCase__			,				torch._dynamo.eval_frame.OptimizedModule       )



def      __lowerCAmelCase						(							UpperCAmelCase__				:      str			,				UpperCAmelCase__				:      bool = True       )  ->    str:
							lowerCamelCase_							  =					(torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

							lowerCamelCase_							  =					is_compiled_module(UpperCAmelCase__       )
							if is_compiled:
														lowerCamelCase_							  =					model
														lowerCamelCase_							  =					model._orig_mod

							if is_deepspeed_available():
														options += (DeepSpeedEngine,)

							while isinstance(UpperCAmelCase__			,				UpperCAmelCase__       ):
														lowerCamelCase_							  =					model.module

							if not keep_fpaa_wrapper:
														lowerCamelCase_							  =					getattr(UpperCAmelCase__			,				"""forward"""       )
														lowerCamelCase_							  =					model.__dict__.pop("""_original_forward"""			,				UpperCAmelCase__       )
														if original_forward is not None:
																					while hasattr(UpperCAmelCase__			,				"""__wrapped__"""       ):
																												lowerCamelCase_							  =					forward.__wrapped__
																												if forward == original_forward:
																																			break
																					lowerCamelCase_							  =					forward
														if getattr(UpperCAmelCase__			,				"""_converted_to_transformer_engine"""			,				UpperCAmelCase__       ):
																					convert_model(UpperCAmelCase__			,				to_transformer_engine=UpperCAmelCase__       )

							if is_compiled:
														lowerCamelCase_							  =					model
														lowerCamelCase_							  =					compiled_model

							return model



def      __lowerCAmelCase						(							)  ->    Any:
							PartialState().wait_for_everyone()



def      __lowerCAmelCase						(							UpperCAmelCase__				:      Union[str, Any]			,				UpperCAmelCase__				:      Tuple       )  ->    Dict:
							if PartialState().distributed_type == DistributedType.TPU:
														xm.save(UpperCAmelCase__			,				UpperCAmelCase__       )
							elif PartialState().local_process_index == 0:
														torch.save(UpperCAmelCase__			,				UpperCAmelCase__       )



@contextmanager
def      __lowerCAmelCase						(							**UpperCAmelCase__				:      Any       )  ->    Dict:
							for key, value in kwargs.items():
														lowerCamelCase_							  =					str(UpperCAmelCase__       )

							yield

							for key in kwargs:
														if key.upper() in os.environ:
																					del os.environ[key.upper()]



def      __lowerCAmelCase						(							UpperCAmelCase__				:      Union[str, Any]       )  ->    str:
							if not hasattr(UpperCAmelCase__			,				"""__qualname__"""       ) and not hasattr(UpperCAmelCase__			,				"""__name__"""       ):
														lowerCamelCase_							  =					getattr(UpperCAmelCase__			,				"""__class__"""			,				UpperCAmelCase__       )
							if hasattr(UpperCAmelCase__			,				"""__qualname__"""       ):
														return obj.__qualname__
							if hasattr(UpperCAmelCase__			,				"""__name__"""       ):
														return obj.__name__
							return str(UpperCAmelCase__       )



def      __lowerCAmelCase						(							UpperCAmelCase__				:      str			,				UpperCAmelCase__				:      Union[str, Any]       )  ->    Dict:
							for key, value in source.items():
														if isinstance(UpperCAmelCase__			,				UpperCAmelCase__       ):
																					lowerCamelCase_							  =					destination.setdefault(UpperCAmelCase__			,				{}       )
																					merge_dicts(UpperCAmelCase__			,				UpperCAmelCase__       )
														else:
																					lowerCamelCase_							  =					value

							return destination



def      __lowerCAmelCase						(							UpperCAmelCase__				:      int = None       )  ->    bool:
							if port is None:
														lowerCamelCase_							  =					2_9_5_0_0
							with socket.socket(socket.AF_INET			,				socket.SOCK_STREAM       ) as s:
														return s.connect_ex(("""localhost""", port)       ) == 0





