"""simple docstring"""




import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
     from transformers.pipelines.conversational import Conversation


_a				:		Tuple	   =       logging.get_logger(__name__)

_a				:		Union[str, Any]	   =       {'''tokenizer_file''': '''tokenizer.json'''}

_a				:		int	   =       {
    '''tokenizer_file''': {
        '''bigscience/tokenizer''': '''https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json''',
        '''bigscience/bloom-560m''': '''https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json''',
        '''bigscience/bloom-1b1''': '''https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json''',
        '''bigscience/bloom-1b7''': '''https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json''',
        '''bigscience/bloom-3b''': '''https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json''',
        '''bigscience/bloom-7b1''': '''https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json''',
        '''bigscience/bloom''': '''https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json''',
    },
}
class 						__A							(			SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:      Optional[int]		 =		VOCAB_FILES_NAMES
     _UpperCamelCase							:      Dict		 =		PRETRAINED_VOCAB_FILES_MAP
     _UpperCamelCase							:      Optional[Any]		 =		["input_ids", "attention_mask"]
     _UpperCamelCase							:      Any		 =		None






     def __init__(		self    ,					a__=None    ,					a__=None    ,					a__=None    ,					a__="<unk>"    ,					a__="<s>"    ,					a__="</s>"    ,					a__="<pad>"    ,					a__=False    ,					a__=False    ,					**a__    ,					):
       super().__init__(
           __a    ,					__a    ,					tokenizer_file=__a    ,					unk_token=__a    ,					bos_token=__a    ,					eos_token=__a    ,					pad_token=__a    ,					add_prefix_space=__a    ,					clean_up_tokenization_spaces=__a    ,					**__a    ,					)
       _lowerCAmelCase						:	Union[str, Any]        =					json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()  )
       if pre_tok_state.get("""add_prefix_space"""    ,					__a  ) != add_prefix_space:
         _lowerCAmelCase						:	Tuple        =					getattr(__a    ,					pre_tok_state.pop("""type"""  )  )
         _lowerCAmelCase						:	Union[str, Any]        =					add_prefix_space
         _lowerCAmelCase						:	str        =					pre_tok_class(**__a  )

       _lowerCAmelCase						:	List[str]        =					add_prefix_space






     def    __A  (		self    ,					*a__    ,					**a__  ):
       _lowerCAmelCase						:	str        =					kwargs.get("""is_split_into_words"""    ,					__a  )
       if not (self.add_prefix_space or not is_split_into_words):
         raise Exception(
             F"You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"
             """ pretokenized inputs."""  )

       return super()._batch_encode_plus(*__a    ,					**__a  )






     def    __A  (		self    ,					*a__    ,					**a__  ):
       _lowerCAmelCase						:	Optional[Any]        =					kwargs.get("""is_split_into_words"""    ,					__a  )

       if not (self.add_prefix_space or not is_split_into_words):
         raise Exception(
             F"You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"
             """ pretokenized inputs."""  )

       return super()._encode_plus(*__a    ,					**__a  )






     def    __A  (		self    ,					a__    ,					a__ = None  ):
       _lowerCAmelCase						:	Any        =					self._tokenizer.model.save(__a    ,					name=__a  )
       return tuple(__a  )






     def    __A  (		self    ,					a__  ):
       _lowerCAmelCase						:	str        =					[]
       for is_user, text in conversation.iter_texts():
         input_ids.extend(self.encode(__a    ,					add_special_tokens=__a  ) + [self.eos_token_id]  )

       if len(__a  ) > self.model_max_length:
         _lowerCAmelCase						:	Tuple        =					input_ids[-self.model_max_length :]
       return input_ids





"""simple docstring"""




from manim import *
class 						__A							(			SCREAMING_SNAKE_CASE_		):






     def    __A  (		self  ):
       _lowerCAmelCase						:	Any        =					Rectangle(height=0.5    ,					width=0.5  )
       _lowerCAmelCase						:	List[Any]        =					Rectangle(height=0.4_6    ,					width=0.4_6  ).set_stroke(width=0  )

       _lowerCAmelCase						:	List[str]        =					[mem.copy() for i in range(6  )]
       _lowerCAmelCase						:	Any        =					[mem.copy() for i in range(6  )]
       _lowerCAmelCase						:	Optional[int]        =					VGroup(*a__  ).arrange(a__    ,					buff=0  )
       _lowerCAmelCase						:	Tuple        =					VGroup(*a__  ).arrange(a__    ,					buff=0  )
       _lowerCAmelCase						:	Optional[Any]        =					VGroup(a__    ,					a__  ).arrange(a__    ,					buff=0  )
       _lowerCAmelCase						:	Dict        =					Text("""CPU"""    ,					font_size=24  )
       _lowerCAmelCase						:	str        =					Group(a__    ,					a__  ).arrange(a__    ,					buff=0.5    ,					aligned_edge=a__  )
       cpu.move_to([-2.5, -0.5, 0]  )
       self.add(a__  )

       _lowerCAmelCase						:	Dict        =					[mem.copy() for i in range(4  )]
       _lowerCAmelCase						:	Any        =					VGroup(*a__  ).arrange(a__    ,					buff=0  )
       _lowerCAmelCase						:	Tuple        =					Text("""GPU"""    ,					font_size=24  )
       _lowerCAmelCase						:	Optional[int]        =					Group(a__    ,					a__  ).arrange(a__    ,					buff=0.5    ,					aligned_edge=a__  )
       gpu.move_to([-1, -1, 0]  )
       self.add(a__  )

       _lowerCAmelCase						:	Optional[int]        =					[mem.copy() for i in range(6  )]
       _lowerCAmelCase						:	Any        =					VGroup(*a__  ).arrange(a__    ,					buff=0  )

       _lowerCAmelCase						:	List[str]        =					Text("""Model"""    ,					font_size=24  )
       _lowerCAmelCase						:	Any        =					Group(a__    ,					a__  ).arrange(a__    ,					buff=0.5    ,					aligned_edge=a__  )
       model.move_to([3, -1.0, 0]  )
       self.add(a__  )

       _lowerCAmelCase						:	Tuple        =					[]
       for i, rect in enumerate(a__  ):
         rect.set_stroke(a__  )
         # target = fill.copy().set_fill(YELLOW, opacity=0.7)
         # target.move_to(rect)
         # self.add(target)

         _lowerCAmelCase						:	List[str]        =					Rectangle(height=0.4_6 / 4    ,					width=0.4_6 / 3  ).set_stroke(width=0.0  ).set_fill(a__    ,					opacity=0.7  )

         if i == 0:
           cpu_target.next_to(cpu_left_col_base[0].get_corner(DOWN + LEFT  )    ,					buff=0.0_2    ,					direction=a__  )
           cpu_target.set_x(cpu_target.get_x() + 0.1  )
         elif i == 3:
           cpu_target.next_to(cpu_targs[0]    ,					direction=a__    ,					buff=0.0  )
         else:
           cpu_target.next_to(cpu_targs[i - 1]    ,					direction=a__    ,					buff=0.0  )
         self.add(a__  )
         cpu_targs.append(a__  )

       _lowerCAmelCase						:	Any        =					[mem.copy() for i in range(6  )]
       _lowerCAmelCase						:	List[str]        =					VGroup(*a__  ).arrange(a__    ,					buff=0  )

       _lowerCAmelCase						:	int        =					Text("""Loaded Checkpoint"""    ,					font_size=24  )
       _lowerCAmelCase						:	Optional[int]        =					Group(a__    ,					a__  ).arrange(a__    ,					aligned_edge=a__    ,					buff=0.4  )
       checkpoint.move_to([3, 0.5, 0]  )

       _lowerCAmelCase						:	List[Any]        =					Square(side_length=2.2  )
       key.move_to([-5, 2, 0]  )

       _lowerCAmelCase						:	List[str]        =					MarkupText(
           F"<b>Key:</b>\n\n<span fgcolor='{YELLOW}'>●</span> Empty Model"    ,					font_size=18    ,					)

       key_text.move_to([-5, 2.4, 0]  )

       self.add(a__    ,					a__  )

       _lowerCAmelCase						:	int        =					MarkupText(
           F"<span fgcolor='{BLUE}'>●</span> Checkpoint"    ,					font_size=18    ,					)

       blue_text.next_to(a__    ,					DOWN * 2.4    ,					aligned_edge=key_text.get_left()  )

       _lowerCAmelCase						:	List[Any]        =					MarkupText(
           F"Next, a <i><span fgcolor=\"{BLUE}\">second</span></i> model is loaded into memory,\nwith the weights of a <span fgcolor=\"{BLUE}\">single shard</span>."    ,					font_size=24    ,					)
       step_a.move_to([2, 2, 0]  )
       self.play(Write(a__  )    ,					Write(a__  )  )

       self.play(Write(a__    ,					run_time=1  )    ,					Create(a__    ,					run_time=1  )  )

       _lowerCAmelCase						:	int        =					[]
       _lowerCAmelCase						:	List[Any]        =					[]
       for i, rect in enumerate(a__  ):
         _lowerCAmelCase						:	Tuple        =					fill.copy().set_fill(a__    ,					opacity=0.7  )
         target.move_to(a__  )
         first_animations.append(GrowFromCenter(a__    ,					run_time=1  )  )

         _lowerCAmelCase						:	Optional[Any]        =					target.copy()
         cpu_target.generate_target()
         if i < 5:
           cpu_target.target.move_to(cpu_left_col_base[i + 1]  )
         else:
           cpu_target.target.move_to(cpu_right_col_base[i - 5]  )
         second_animations.append(MoveToTarget(a__    ,					run_time=1.5  )  )

       self.play(*a__  )
       self.play(*a__  )
       self.wait()




