
'''simple docstring'''







import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

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


_snake_case				:   str     =				logging.get_logger(__name__)

_snake_case				:   Any     =				"""▁"""

_snake_case				:   Optional[Any]     =				{
    """vocab_file""": """vocab.json""",
    """spm_file""": """sentencepiece.bpe.model""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

_snake_case				:   List[Any]     =				{
    """vocab_file""": {
        """facebook/m2m100_418M""": """https://huggingface.co/facebook/m2m100_418M/resolve/main/vocab.json""",
        """facebook/m2m100_1.2B""": """https://huggingface.co/facebook/m2m100_1.2B/resolve/main/vocab.json""",
    },
    """spm_file""": {
        """facebook/m2m100_418M""": """https://huggingface.co/facebook/m2m100_418M/resolve/main/sentencepiece.bpe.model""",
        """facebook/m2m100_1.2B""": """https://huggingface.co/facebook/m2m100_1.2B/resolve/main/sentencepiece.bpe.model""",
    },
    """tokenizer_config_file""": {
        """facebook/m2m100_418M""": """https://huggingface.co/facebook/m2m100_418M/resolve/main/tokenizer_config.json""",
        """facebook/m2m100_1.2B""": """https://huggingface.co/facebook/m2m100_1.2B/resolve/main/tokenizer_config.json""",
    },
}

_snake_case				:   Optional[int]     =				{
    """facebook/m2m100_418M""": 1_024,
}

# fmt: off
_snake_case				:   Tuple     =				{
    """m2m100""": ["""af""", """am""", """ar""", """ast""", """az""", """ba""", """be""", """bg""", """bn""", """br""", """bs""", """ca""", """ceb""", """cs""", """cy""", """da""", """de""", """el""", """en""", """es""", """et""", """fa""", """ff""", """fi""", """fr""", """fy""", """ga""", """gd""", """gl""", """gu""", """ha""", """he""", """hi""", """hr""", """ht""", """hu""", """hy""", """id""", """ig""", """ilo""", """is""", """it""", """ja""", """jv""", """ka""", """kk""", """km""", """kn""", """ko""", """lb""", """lg""", """ln""", """lo""", """lt""", """lv""", """mg""", """mk""", """ml""", """mn""", """mr""", """ms""", """my""", """ne""", """nl""", """no""", """ns""", """oc""", """or""", """pa""", """pl""", """ps""", """pt""", """ro""", """ru""", """sd""", """si""", """sk""", """sl""", """so""", """sq""", """sr""", """ss""", """su""", """sv""", """sw""", """ta""", """th""", """tl""", """tn""", """tr""", """uk""", """ur""", """uz""", """vi""", """wo""", """xh""", """yi""", """yo""", """zh""", """zu"""],
    """wmt21""": ["""en""", """ha""", """is""", """ja""", """cs""", """ru""", """zh""", """de"""]
}


class 			lowerCAmelCase (				__UpperCAmelCase			):
		a							:					Union[str, Any]       =					VOCAB_FILES_NAMES
		a							:					Any       =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		a							:					Tuple       =					PRETRAINED_VOCAB_FILES_MAP
		a							:					List[Any]       =					["""input_ids""", """attention_mask"""]

		a							:					List[int]       =					[]
		a							:					List[int]       =					[]




		def __init__(				self					,						UpperCamelCase					,						UpperCamelCase					,						UpperCamelCase=None					,						UpperCamelCase=None					,						UpperCamelCase="<s>"					,						UpperCamelCase="</s>"					,						UpperCamelCase="</s>"					,						UpperCamelCase="<pad>"					,						UpperCamelCase="<unk>"					,						UpperCamelCase="m2m100"					,						UpperCamelCase = None					,						UpperCamelCase=8					,						**UpperCamelCase					,						):
								_SCREAMING_SNAKE_CASE				= {} if sp_model_kwargs is None else sp_model_kwargs

								_SCREAMING_SNAKE_CASE				= language_codes
								_SCREAMING_SNAKE_CASE				= FAIRSEQ_LANGUAGE_CODES[language_codes]
								_SCREAMING_SNAKE_CASE				= {lang_code: F'__{lang_code}__' for lang_code in fairseq_language_code}

								_SCREAMING_SNAKE_CASE				= kwargs.get("additional_special_tokens"					,						[]      )
								kwargs["additional_special_tokens"] += [
								    self.get_lang_token(UpperCamelCase      )
								    for lang_code in fairseq_language_code
								    if self.get_lang_token(UpperCamelCase      ) not in kwargs["additional_special_tokens"]
								]

								super().__init__(
								    src_lang=UpperCamelCase					,						tgt_lang=UpperCamelCase					,						bos_token=UpperCamelCase					,						eos_token=UpperCamelCase					,						sep_token=UpperCamelCase					,						unk_token=UpperCamelCase					,						pad_token=UpperCamelCase					,						language_codes=UpperCamelCase					,						sp_model_kwargs=self.sp_model_kwargs					,						num_madeup_words=UpperCamelCase					,						**UpperCamelCase					,						)

								_SCREAMING_SNAKE_CASE				= vocab_file
								_SCREAMING_SNAKE_CASE				= load_json(UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= {v: k for k, v in self.encoder.items()}
								_SCREAMING_SNAKE_CASE				= spm_file
								_SCREAMING_SNAKE_CASE				= load_spm(UpperCamelCase					,						self.sp_model_kwargs      )

								_SCREAMING_SNAKE_CASE				= len(self.encoder      )

								_SCREAMING_SNAKE_CASE				= {
								    self.get_lang_token(UpperCamelCase      ): self.encoder_size + i for i, lang_code in enumerate(UpperCamelCase      )
								}
								_SCREAMING_SNAKE_CASE				= {lang_code: self.encoder_size + i for i, lang_code in enumerate(UpperCamelCase      )}
								_SCREAMING_SNAKE_CASE				= {v: k for k, v in self.lang_token_to_id.items()}

								_SCREAMING_SNAKE_CASE				= src_lang if src_lang is not None else "en"
								_SCREAMING_SNAKE_CASE				= tgt_lang
								_SCREAMING_SNAKE_CASE				= self.get_lang_id(self._src_lang      )
								self.set_src_lang_special_tokens(self._src_lang      )

								_SCREAMING_SNAKE_CASE				= num_madeup_words




		@property
		def     lowercase       (				self      ):
								return len(self.encoder      ) + len(self.lang_token_to_id      )




		@property
		def     lowercase       (				self      ):
								return self._src_lang




		@src_lang.setter
		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= new_src_lang
								self.set_src_lang_special_tokens(self._src_lang      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								return self.sp_model.encode(UpperCamelCase					,						out_type=UpperCamelCase      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								if token in self.lang_token_to_id:
														return self.lang_token_to_id[token]
								return self.encoder.get(UpperCamelCase					,						self.encoder[self.unk_token]      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								if index in self.id_to_lang_token:
														return self.id_to_lang_token[index]
								return self.decoder.get(UpperCamelCase					,						self.unk_token      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= []
								_SCREAMING_SNAKE_CASE				= ""
								for token in tokens:
														# make sure that special tokens are not decoded using sentencepiece model
														if token in self.all_special_tokens:
																				out_string += self.sp_model.decode(UpperCamelCase      ) + token
																				_SCREAMING_SNAKE_CASE				= []
														else:
																				current_sub_tokens.append(UpperCamelCase      )
								out_string += self.sp_model.decode(UpperCamelCase      )
								return out_string.strip()




		def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase = None					,						UpperCamelCase = 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      )

								_SCREAMING_SNAKE_CASE				= [1] * len(self.prefix_tokens      )
								_SCREAMING_SNAKE_CASE				= [1] * len(self.suffix_tokens      )
								if token_ids_a is None:
														return prefix_ones + ([0] * len(UpperCamelCase      )) + suffix_ones
								return prefix_ones + ([0] * len(UpperCamelCase      )) + ([0] * len(UpperCamelCase      )) + suffix_ones




		def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase = None      ):
								if token_ids_a is None:
														return self.prefix_tokens + token_ids_a + self.suffix_tokens
								# We don't expect to process pairs, but leave the pair logic for API consistency
								return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= {self.convert_ids_to_tokens(UpperCamelCase      ): i for i in range(self.vocab_size      )}
								vocab.update(self.added_tokens_encoder      )
								return vocab




		def __getstate__(				self      ):
								_SCREAMING_SNAKE_CASE				= self.__dict__.copy()
								_SCREAMING_SNAKE_CASE				= None
								return state




		def __setstate__(				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= d

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

								_SCREAMING_SNAKE_CASE				= load_spm(self.spm_file					,						self.sp_model_kwargs      )




		def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase = None      ):
								_SCREAMING_SNAKE_CASE				= Path(UpperCamelCase      )
								if not save_dir.is_dir():
														raise OSError(F'{save_directory} should be a directory'      )
								_SCREAMING_SNAKE_CASE				= save_dir / (
								    (filename_prefix + "-" if filename_prefix else "") + self.vocab_files_names["vocab_file"]
								)
								_SCREAMING_SNAKE_CASE				= save_dir / (
								    (filename_prefix + "-" if filename_prefix else "") + self.vocab_files_names["spm_file"]
								)

								save_json(self.encoder					,						UpperCamelCase      )

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

								return (str(UpperCamelCase      ), str(UpperCamelCase      ))




		def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase = "en"					,						UpperCamelCase = None					,						UpperCamelCase = "ro"					,						**UpperCamelCase					,						):
								_SCREAMING_SNAKE_CASE				= src_lang
								_SCREAMING_SNAKE_CASE				= tgt_lang
								self.set_src_lang_special_tokens(self.src_lang      )
								return super().prepare_seqaseq_batch(UpperCamelCase					,						UpperCamelCase					,						**UpperCamelCase      )




		def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase					,						UpperCamelCase					,						**UpperCamelCase      ):
								if src_lang is None or tgt_lang is None:
														raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"      )
								_SCREAMING_SNAKE_CASE				= src_lang
								_SCREAMING_SNAKE_CASE				= self(UpperCamelCase					,						add_special_tokens=UpperCamelCase					,						**UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= self.get_lang_id(UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= tgt_lang_id
								return inputs




		def     lowercase       (				self      ):
								self.set_src_lang_special_tokens(self.src_lang      )




		def     lowercase       (				self      ):
								self.set_tgt_lang_special_tokens(self.tgt_lang      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= self.get_lang_token(UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= self.lang_token_to_id[lang_token]
								_SCREAMING_SNAKE_CASE				= [self.cur_lang_id]
								_SCREAMING_SNAKE_CASE				= [self.eos_token_id]




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= self.get_lang_token(UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= self.lang_token_to_id[lang_token]
								_SCREAMING_SNAKE_CASE				= [self.cur_lang_id]
								_SCREAMING_SNAKE_CASE				= [self.eos_token_id]




		def     lowercase       (				self					,						UpperCamelCase      ):
								return self.lang_code_to_token[lang]




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= self.get_lang_token(UpperCamelCase      )
								return self.lang_token_to_id[lang_token]



def 			_a		(	_SCREAMING_SNAKE_CASE		:   str	,			_SCREAMING_SNAKE_CASE		:   Dict[str, Any]  ):
						_SCREAMING_SNAKE_CASE				= sentencepiece.SentencePieceProcessor(**_SCREAMING_SNAKE_CASE  )
						spm.Load(str(_SCREAMING_SNAKE_CASE  )  )
						return spm



def 			_a		(	_SCREAMING_SNAKE_CASE		:   str  ):
						with open(_SCREAMING_SNAKE_CASE	,			"r"  ) as f:
												return json.load(_SCREAMING_SNAKE_CASE  )




def 			_a		(	_SCREAMING_SNAKE_CASE		:   Dict	,			_SCREAMING_SNAKE_CASE		:   str  ):
						with open(_SCREAMING_SNAKE_CASE	,			"w"  ) as f:
												json.dump(_SCREAMING_SNAKE_CASE	,			_SCREAMING_SNAKE_CASE	,			indent=2  )

'''simple docstring'''







import baseaa
import io
import json
import os
from copy import deepcopy

from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler


class 			lowerCAmelCase :




		def __init__(				self					,						UpperCamelCase      ):
								if isinstance(UpperCamelCase					,						UpperCamelCase      ):
														# Don't modify user's data should they want to reuse it (e.g. in tests), because once we
														# modified it, it will not be accepted here again, since `auto` values would have been overridden
														_SCREAMING_SNAKE_CASE				= deepcopy(UpperCamelCase      )
								elif os.path.exists(UpperCamelCase      ):
														with io.open(UpperCamelCase					,						"r"					,						encoding="utf-8"      ) as f:
																				_SCREAMING_SNAKE_CASE				= json.load(UpperCamelCase      )
								else:
														try:
																				_SCREAMING_SNAKE_CASE				= baseaa.urlsafe_baadecode(UpperCamelCase      ).decode("utf-8"      )
																				_SCREAMING_SNAKE_CASE				= json.loads(UpperCamelCase      )
														except (UnicodeDecodeError, AttributeError, ValueError):
																				raise ValueError(
																				    F'Expected a string path to an existing deepspeed config, or a dictionary, or a base64 encoded string. Received: {config_file_or_dict}'      )

								_SCREAMING_SNAKE_CASE				= config

								self.set_stage_and_offload()




		def     lowercase       (				self      ):
								# zero stage - this is done as early as possible, before model is created, to allow
								# ``is_deepspeed_zero3_enabled`` query and getting to the early deepspeed config object
								# during ``zero.Init()`` which needs to know the dtype, and some other hparams.
								_SCREAMING_SNAKE_CASE				= self.get_value("zero_optimization.stage"					,						-1      )

								# offload
								_SCREAMING_SNAKE_CASE				= False
								if self.is_zeroa() or self.is_zeroa():
														_SCREAMING_SNAKE_CASE				= set(["cpu", "nvme"]      )
														_SCREAMING_SNAKE_CASE				= set(
														    [
														        self.get_value("zero_optimization.offload_optimizer.device"      ),
														        self.get_value("zero_optimization.offload_param.device"      ),
														    ]      )
														if len(offload_devices & offload_devices_valid      ) > 0:
																				_SCREAMING_SNAKE_CASE				= True




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= self.config

								# find the config node of interest if it exists
								_SCREAMING_SNAKE_CASE				= ds_key_long.split("."      )
								_SCREAMING_SNAKE_CASE				= nodes.pop()
								for node in nodes:
														_SCREAMING_SNAKE_CASE				= config.get(UpperCamelCase      )
														if config is None:
																				return None, ds_key

								return config, ds_key




		def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase=None      ):
								_SCREAMING_SNAKE_CASE,							_SCREAMING_SNAKE_CASE				= self.find_config_node(UpperCamelCase      )
								if config is None:
														return default
								return config.get(UpperCamelCase					,						UpperCamelCase      )




		def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase=False      ):
								_SCREAMING_SNAKE_CASE				= self.config

								# find the config node of interest if it exists
								_SCREAMING_SNAKE_CASE				= ds_key_long.split("."      )
								for node in nodes:
														_SCREAMING_SNAKE_CASE				= config
														_SCREAMING_SNAKE_CASE				= config.get(UpperCamelCase      )
														if config is None:
																				if must_exist:
																										raise ValueError(F'Can\'t find {ds_key_long} entry in the config: {self.config}'      )
																				else:
																										return

        # if found remove it
								if parent_config is not None:
														parent_config.pop(UpperCamelCase      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= self.get_value(UpperCamelCase      )
								return False if value is None else bool(UpperCamelCase      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= self.get_value(UpperCamelCase      )
								return False if value is None else not bool(UpperCamelCase      )




		def     lowercase       (				self      ):
								return self._stage == 2




		def     lowercase       (				self      ):
								return self._stage == 3




		def     lowercase       (				self      ):
								return self._offload


class 			lowerCAmelCase :




		def __init__(				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= engine




		def     lowercase       (				self					,						UpperCamelCase					,						**UpperCamelCase      ):
								# runs backpropagation and handles mixed precision
								self.engine.backward(UpperCamelCase					,						**UpperCamelCase      )

								# Deepspeed's `engine.step` performs the following operations:
								# - gradient accumulation check
								# - gradient clipping
								# - optimizer step
								# - zero grad
								# - checking overflow
								# - lr_scheduler step (only if engine.lr_scheduler is not None)
								self.engine.step()
								# and this plugin overrides the above calls with no-ops when Accelerate runs under
								# Deepspeed, but allows normal functionality for non-Deepspeed cases thus enabling a simple
								# training loop that works transparently under many training regimes.


class 			lowerCAmelCase (				__UpperCAmelCase			):




		def __init__(				self					,						UpperCamelCase      ):
								super().__init__(UpperCamelCase					,						device_placement=UpperCamelCase					,						scaler=UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= hasattr(self.optimizer					,						"overflow"      )




		def     lowercase       (				self					,						UpperCamelCase=None      ):
								pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed




		def     lowercase       (				self      ):
								pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed




		@property
		def     lowercase       (				self      ):
								if self.__has_overflow__:
														return self.optimizer.overflow
								return False


class 			lowerCAmelCase (				__UpperCAmelCase			):




		def __init__(				self					,						UpperCamelCase					,						UpperCamelCase      ):
								super().__init__(UpperCamelCase					,						UpperCamelCase      )




		def     lowercase       (				self      ):
								pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed


class 			lowerCAmelCase :




		def __init__(				self					,						UpperCamelCase					,						UpperCamelCase=0.0_01					,						UpperCamelCase=0					,						**UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= params
								_SCREAMING_SNAKE_CASE				= lr
								_SCREAMING_SNAKE_CASE				= weight_decay
								_SCREAMING_SNAKE_CASE				= kwargs


class 			lowerCAmelCase :




		def __init__(				self					,						UpperCamelCase					,						UpperCamelCase=None					,						UpperCamelCase=0					,						**UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= optimizer
								_SCREAMING_SNAKE_CASE				= total_num_steps
								_SCREAMING_SNAKE_CASE				= warmup_num_steps
								_SCREAMING_SNAKE_CASE				= kwargs