






'''simple docstring'''




import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

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


lowerCamelCase_												=					logging.get_logger(__name__)


lowerCamelCase_												=					{
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

lowerCamelCase_												=					{
    '''vocab_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'''
    },
    '''merges_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'''
    },
    '''tokenizer_config_file''': {
        '''facebook/blenderbot_small-90M''': (
            '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'''
        )
    },
}

lowerCamelCase_												=					{'''facebook/blenderbot_small-90M''': 5_12}

def 					__lowercase						(			__lowercase       )       ->						List[str]:

      '''simple docstring'''


      _A			     =	set()
      _A			     =	word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)       )
            _A			     =	char

      _A			     =	set(__lowercase       )
      return pairs


class    _UpperCAmelCase			(     snake_case_						):




   """simple docstring"""

   snake_case    				=						VOCAB_FILES_NAMES
   snake_case    				=						PRETRAINED_VOCAB_FILES_MAP
   snake_case    				=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   snake_case    				=						['''input_ids''', '''attention_mask''']

   def __init__(		self :	List[Any]      ,      __UpperCAmelCase :	Optional[int]      ,      __UpperCAmelCase :	int      ,      __UpperCAmelCase :	str="__start__"      ,      __UpperCAmelCase :	Dict="__end__"      ,      __UpperCAmelCase :	str="__unk__"      ,      __UpperCAmelCase :	List[str]="__null__"      ,      **__UpperCAmelCase :	List[str]      ,      ):





         '''simple docstring'''





         super().__init__(unk_token=__UpperCAmelCase      ,      bos_token=__UpperCAmelCase      ,      eos_token=__UpperCAmelCase      ,      pad_token=__UpperCAmelCase      ,      **__UpperCAmelCase		)

         with open(__UpperCAmelCase      ,      encoding="utf-8"		) as vocab_handle:
               _A			     =	json.load(__UpperCAmelCase		)
         _A			     =	{v: k for k, v in self.encoder.items()}
         with open(__UpperCAmelCase      ,      encoding="utf-8"		) as merges_handle:
               _A			     =	merges_handle.read().split("\n"		)[1:-1]
         _A			     =	[tuple(merge.split()		) for merge in merges]
         _A			     =	dict(zip(__UpperCAmelCase      ,      range(len(__UpperCAmelCase		)		)		)		)
         _A			     =	{}

   @property
   def 						lowerCAmelCase (		self :	Any		):





         '''simple docstring'''





         return len(self.encoder		)

   def 						lowerCAmelCase (		self :	str		):





         '''simple docstring'''





         return dict(self.encoder      ,      **self.added_tokens_encoder		)

   def 						lowerCAmelCase (		self :	List[Any]      ,      __UpperCAmelCase :	str		):





         '''simple docstring'''





         if token in self.cache:
               return self.cache[token]
         _A			     =	re.sub("([.,!?()])"      ,      R" \1"      ,      __UpperCAmelCase		)
         _A			     =	re.sub("(')"      ,      R" \1 "      ,      __UpperCAmelCase		)
         _A			     =	re.sub(R"\s{2,}"      ,      " "      ,      __UpperCAmelCase		)
         if "\n" in token:
               _A			     =	token.replace("\n"      ,      " __newln__"		)

         _A			     =	token.split(" "		)
         _A			     =	[]
         for token in tokens:
               if not len(__UpperCAmelCase		):
                     continue

               _A			     =	token.lower()
               _A			     =	tuple(__UpperCAmelCase		)
               _A			     =	tuple(list(word[:-1]		) + [word[-1] + "</w>"]		)
               _A			     =	get_pairs(__UpperCAmelCase		)

               if not pairs:
                     words.append(__UpperCAmelCase		)
                     continue

               while True:
                     _A			     =	min(__UpperCAmelCase      ,      key=lambda __UpperCAmelCase		: self.bpe_ranks.get(__UpperCAmelCase      ,      float("inf"		)		)		)
                     if bigram not in self.bpe_ranks:
                           break
                     _A     ,	_A			     =	bigram
                     _A			     =	[]
                     _A			     =	0

                     while i < len(__UpperCAmelCase		):
                           try:
                                 _A			     =	word.index(__UpperCAmelCase      ,      __UpperCAmelCase		)
                                 new_word.extend(word[i:j]		)
                                 _A			     =	j
                           except ValueError:
                                 new_word.extend(word[i:]		)
                                 break

                           if word[i] == first and i < len(__UpperCAmelCase		) - 1 and word[i + 1] == second:
                                 new_word.append(first + second		)
                                 i += 2
                           else:
                                 new_word.append(word[i]		)
                                 i += 1
                     _A			     =	tuple(__UpperCAmelCase		)
                     _A			     =	new_word
                     if len(__UpperCAmelCase		) == 1:
                           break
                     else:
                           _A			     =	get_pairs(__UpperCAmelCase		)
               _A			     =	"@@ ".join(__UpperCAmelCase		)
               _A			     =	word[:-4]

               _A			     =	word
               words.append(__UpperCAmelCase		)
         return " ".join(__UpperCAmelCase		)

   def 						lowerCAmelCase (		self :	Union[str, Any]      ,      __UpperCAmelCase :	str		):





         '''simple docstring'''





         _A			     =	[]

         _A			     =	re.findall(R"\S+\n?"      ,      __UpperCAmelCase		)

         for token in words:
               split_tokens.extend(list(self.bpe(__UpperCAmelCase		).split(" "		)		)		)
         return split_tokens

   def 						lowerCAmelCase (		self :	Any      ,      __UpperCAmelCase :	str		):





         '''simple docstring'''





         _A			     =	token.lower()
         return self.encoder.get(__UpperCAmelCase      ,      self.encoder.get(self.unk_token		)		)

   def 						lowerCAmelCase (		self :	Optional[int]      ,      __UpperCAmelCase :	int		):





         '''simple docstring'''





         return self.decoder.get(__UpperCAmelCase      ,      self.unk_token		)

   def 						lowerCAmelCase (		self :	Tuple      ,      __UpperCAmelCase :	List[str]		):





         '''simple docstring'''





         _A			     =	" ".join(__UpperCAmelCase		).replace("@@ "      ,      ""		).strip()
         return out_string

   def 						lowerCAmelCase (		self :	Optional[Any]      ,      __UpperCAmelCase :	str      ,      __UpperCAmelCase :	Optional[str] = None		):





         '''simple docstring'''





         if not os.path.isdir(__UpperCAmelCase		):
               logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''		)
               return
         _A			     =	os.path.join(
             __UpperCAmelCase      ,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)
         _A			     =	os.path.join(
             __UpperCAmelCase      ,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]		)

         with open(__UpperCAmelCase      ,      "w"      ,      encoding="utf-8"		) as f:
               f.write(json.dumps(self.encoder      ,      indent=2      ,      sort_keys=__UpperCAmelCase      ,      ensure_ascii=__UpperCAmelCase		) + "\n"		)

         _A			     =	0
         with open(__UpperCAmelCase      ,      "w"      ,      encoding="utf-8"		) as writer:
               writer.write("#version: 0.2\n"		)
               for bpe_tokens, token_index in sorted(self.bpe_ranks.items()      ,      key=lambda __UpperCAmelCase		: kv[1]		):
                     if index != token_index:
                           logger.warning(
                               f'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
                               " Please check that the tokenizer is not corrupted!"		)
                           _A			     =	token_index
                     writer.write(" ".join(__UpperCAmelCase		) + "\n"		)
                     index += 1

         return vocab_file, merge_file






'''simple docstring'''




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

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





class     __magic_name__						:







			def __init__(	self				:  str				,			lowercase_				:  Dict    ):
										if isinstance(lowercase_				,			lowercase_    ):
																	# 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
																	lowercase_					:			List[Any]										=       deepcopy(lowercase_    )
										elif os.path.exists(lowercase_    ):
																	with io.open(lowercase_				,			"""r"""				,			encoding="""utf-8"""    ) as f:
																								lowercase_					:			Union[str, Any]										=       json.load(lowercase_    )
										else:
																	try:
																								lowercase_					:			int										=       baseaa.urlsafe_baadecode(lowercase_    ).decode("""utf-8"""    )
																								lowercase_					:			str										=       json.loads(lowercase_    )
																	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}'''    )

										lowercase_					:			Any										=       config

										self.set_stage_and_offload()







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Union[str, Any]    ):
										# 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.
										lowercase_					:			Tuple										=       self.get_value("""zero_optimization.stage"""				,			-1    )

										# offload
										lowercase_					:			str										=       False
										if self.is_zeroa() or self.is_zeroa():
																	lowercase_					:			Dict										=       set(["""cpu""", """nvme"""]    )
																	lowercase_					:			List[Any]										=       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:
																								lowercase_					:			Tuple										=       True







			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[Any]				,			lowercase_				:  Any    ):
										lowercase_					:			Optional[Any]										=       self.config

										# find the config node of interest if it exists
										lowercase_					:			Tuple										=       ds_key_long.split("""."""    )
										lowercase_					:			Union[str, Any]										=       nodes.pop()
										for node in nodes:
																	lowercase_					:			List[str]										=       config.get(lowercase_    )
																	if config is None:
																								return None, ds_key

										return config, ds_key







			def 	SCREAMING_SNAKE_CASE_     (	self				:  str				,			lowercase_				:  List[str]				,			lowercase_				:  List[str]=None    ):
										lowercase_						,						lowercase_					:			List[Any]										=       self.find_config_node(lowercase_    )
										if config is None:
																	return default
										return config.get(lowercase_				,			lowercase_    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[str]				,			lowercase_				:  Optional[int]				,			lowercase_				:  int=False    ):
										lowercase_					:			int										=       self.config

										# find the config node of interest if it exists
										lowercase_					:			Dict										=       ds_key_long.split("""."""    )
										for node in nodes:
																	lowercase_					:			List[Any]										=       config
																	lowercase_					:			Dict										=       config.get(lowercase_    )
																	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(lowercase_    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Optional[int]				,			lowercase_				:  Tuple    ):
										lowercase_					:			str										=       self.get_value(lowercase_    )
										return False if value is None else bool(lowercase_    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[str]				,			lowercase_				:  Union[str, Any]    ):
										lowercase_					:			Union[str, Any]										=       self.get_value(lowercase_    )
										return False if value is None else not bool(lowercase_    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Dict    ):
										return self._stage == 2







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Any    ):
										return self._stage == 3







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Union[str, Any]    ):
										return self._offload





class     __magic_name__						:







			def __init__(	self				:  Any				,			lowercase_				:  Union[str, Any]    ):
										lowercase_					:			Any										=       engine







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Tuple				,			lowercase_				:  int				,			**lowercase_				:  str    ):
										# runs backpropagation and handles mixed precision
										self.engine.backward(lowercase_				,			**lowercase_    )

										# 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     __magic_name__						(    _UpperCAmelCase):







			def __init__(	self				:  Optional[Any]				,			lowercase_				:  Tuple    ):
										super().__init__(lowercase_				,			device_placement=lowercase_				,			scaler=lowercase_    )
										lowercase_					:			Any										=       hasattr(self.optimizer				,			"""overflow"""    )







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







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







			@property
			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[Any]    ):
										if self.__has_overflow__:
																	return self.optimizer.overflow
										return False





class     __magic_name__						(    _UpperCAmelCase):







			def __init__(	self				:  Dict				,			lowercase_				:  Optional[Any]				,			lowercase_				:  Tuple    ):
										super().__init__(lowercase_				,			lowercase_    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Optional[Any]    ):
										pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed





class     __magic_name__						:







			def __init__(	self				:  Any				,			lowercase_				:  Union[str, Any]				,			lowercase_				:  List[str]=0.0_01				,			lowercase_				:  List[str]=0				,			**lowercase_				:  List[Any]    ):
										lowercase_					:			str										=       params
										lowercase_					:			List[Any]										=       lr
										lowercase_					:			int										=       weight_decay
										lowercase_					:			Union[str, Any]										=       kwargs





class     __magic_name__						:







			def __init__(	self				:  Tuple				,			lowercase_				:  Optional[Any]				,			lowercase_				:  List[str]=None				,			lowercase_				:  int=0				,			**lowercase_				:  int    ):
										lowercase_					:			Union[str, Any]										=       optimizer
										lowercase_					:			List[str]										=       total_num_steps
										lowercase_					:			Dict										=       warmup_num_steps
										lowercase_					:			Dict										=       kwargs





