'''simple docstring'''

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


__a:			Optional[int]	       =       logging.get_logger(__name__)

__a:			List[str]	       =       {'vocab_file': 'spm_char.model'}

__a:			Tuple	       =       {
    'vocab_file': {
        'microsoft/speecht5_asr': 'https://huggingface.co/microsoft/speecht5_asr/resolve/main/spm_char.model',
        'microsoft/speecht5_tts': 'https://huggingface.co/microsoft/speecht5_tts/resolve/main/spm_char.model',
        'microsoft/speecht5_vc': 'https://huggingface.co/microsoft/speecht5_vc/resolve/main/spm_char.model',
    }
}

__a:			List[Any]	       =       {
    'microsoft/speecht5_asr': 10_24,
    'microsoft/speecht5_tts': 10_24,
    'microsoft/speecht5_vc': 10_24,
}



class       UpperCAmelCase  (						lowerCamelCase__ ):





       '''simple docstring'''



       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     ,       __lowerCAmelCase     ,       __lowerCAmelCase="<s>"     ,       __lowerCAmelCase="</s>"     ,       __lowerCAmelCase="<unk>"     ,       __lowerCAmelCase="<pad>"     ,       __lowerCAmelCase = None     ,       **__lowerCAmelCase     ,       )  ->  Tuple:
        lowercase__    :   Dict						= {} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            bos_token=__snake_case     ,       eos_token=__snake_case     ,       unk_token=__snake_case     ,       pad_token=__snake_case     ,       sp_model_kwargs=self.sp_model_kwargs     ,       **__snake_case     ,       )

        lowercase__    :   int						= vocab_file

        lowercase__    :   str						= spm.SentencePieceProcessor(**self.sp_model_kwargs			)
        self.sp_model.Load(__snake_case			)

       @property
       def _lowerCAmelCase(						self			)  ->  List[str]:
        return self.sp_model.get_piece_size()

       def _lowerCAmelCase(						self			)  ->  str:
        lowercase__    :   List[Any]						= {self.convert_ids_to_tokens(__snake_case			): i for i in range(self.vocab_size			)}
        vocab.update(self.added_tokens_encoder			)
        return vocab

       def __getstate__(						self			)  ->  Union[str, Any]:
        lowercase__    :   int						= self.__dict__.copy()
        lowercase__    :   str						= None
        return state

       def __setstate__(						self     ,       __lowerCAmelCase			)  ->  Tuple:
        lowercase__    :   Optional[int]						= d

        # for backward compatibility
        if not hasattr(self     ,       '''sp_model_kwargs'''			):
         lowercase__    :   Dict						= {}

        lowercase__    :   Union[str, Any]						= spm.SentencePieceProcessor(**self.sp_model_kwargs			)
        self.sp_model.Load(self.vocab_file			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  str:
        return self.sp_model.encode(__snake_case     ,       out_type=__snake_case			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  Tuple:
        return self.sp_model.piece_to_id(__snake_case			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  str:
        lowercase__    :   Optional[int]						= self.sp_model.IdToPiece(__snake_case			)
        return token

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  Dict:
        lowercase__    :   Any						= []
        lowercase__    :   int						= ''
        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(__snake_case			) + token
          lowercase__    :   str						= []
         else:
          current_sub_tokens.append(__snake_case			)
        out_string += self.sp_model.decode(__snake_case			)
        return out_string.strip()

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase=None			)  ->  str:
        if token_ids_a is None:
         return token_ids_a + [self.eos_token_id]
        # We don't expect to process pairs, but leave the pair logic for API consistency
        return token_ids_a + token_ids_a + [self.eos_token_id]

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase = None     ,       __lowerCAmelCase = False			)  ->  Union[str, Any]:
        if already_has_special_tokens:
         return super().get_special_tokens_mask(
             token_ids_a=__snake_case     ,       token_ids_a=__snake_case     ,       already_has_special_tokens=__snake_case			)

        lowercase__    :   Optional[Any]						= [1]
        if token_ids_a is None:
         return ([0] * len(__snake_case			)) + suffix_ones
        return ([0] * len(__snake_case			)) + ([0] * len(__snake_case			)) + suffix_ones


       def _lowerCAmelCase(						self     ,       __lowerCAmelCase     ,       __lowerCAmelCase = None			)  ->  Union[str, Any]:
        if not os.path.isdir(__snake_case			):
         logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""			)
         return
        lowercase__    :   Union[str, Any]						= os.path.join(
            __snake_case     ,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']			)

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

        return (out_vocab_file,)


'''simple docstring'''

from manim import *



class       UpperCAmelCase  (						a__ ):





       '''simple docstring'''



       def _lowerCAmelCase(						self			)  ->  List[Any]:
        lowercase__    :   int						= Rectangle(height=0.5     ,       width=0.5			)
        lowercase__    :   Optional[int]						= Rectangle(height=0.2_5     ,       width=0.2_5			)
        lowercase__    :   Tuple						= Rectangle(height=0.4_6     ,       width=0.4_6			).set_stroke(width=0			)

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

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

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

        lowercase__    :   Any						= Text('''Model'''     ,       font_size=24			)
        lowercase__    :   Optional[Any]						= Group(__lowerCAmelCase     ,       __lowerCAmelCase			).arrange(__lowerCAmelCase     ,       buff=0.5     ,       aligned_edge=__lowerCAmelCase			)
        model.move_to([3, -1.0, 0]			)
        self.add(__lowerCAmelCase			)

        lowercase__    :   int						= []
        lowercase__    :   int						= []
        lowercase__    :   Any						= []

        for i, rect in enumerate(__lowerCAmelCase			):
         rect.set_stroke(__lowerCAmelCase			)

         lowercase__    :   Optional[int]						= Rectangle(height=0.4_6 / 4     ,       width=0.4_6 / 3			).set_stroke(width=0.0			).set_fill(__lowerCAmelCase     ,       opacity=0.7			)

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

        self.add(*__lowerCAmelCase     ,       *__lowerCAmelCase     ,       *__lowerCAmelCase			)

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

        lowercase__    :   Optional[Any]						= Text('''Loaded Checkpoint'''     ,       font_size=24			)
        lowercase__    :   Dict						= Group(__lowerCAmelCase     ,       __lowerCAmelCase			).arrange(__lowerCAmelCase     ,       buff=0.5     ,       aligned_edge=__lowerCAmelCase			)
        checkpoint.move_to([3, 0.5, 0]			)

        self.add(__lowerCAmelCase			)

        lowercase__    :   str						= []
        lowercase__    :   List[str]						= []

        for i, rect in enumerate(__lowerCAmelCase			):
         lowercase__    :   List[str]						= fill.copy().set_fill(__lowerCAmelCase     ,       opacity=0.7			)
         target.move_to(__lowerCAmelCase			)
         ckpt_arr.append(__lowerCAmelCase			)

         lowercase__    :   Any						= target.copy()
         if i < 5:
          cpu_target.move_to(cpu_left_col_base[i + 1]			)
         else:
          cpu_target.move_to(cpu_right_col_base[i - 5]			)
         ckpt_cpu_arr.append(__lowerCAmelCase			)
        self.add(*__lowerCAmelCase     ,       *__lowerCAmelCase			)

        lowercase__    :   Optional[int]						= Square(side_length=2.2			)
        key.move_to([-5, 2, 0]			)

        lowercase__    :   Optional[Any]						= 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(__lowerCAmelCase     ,       __lowerCAmelCase			)

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

        blue_text.next_to(__lowerCAmelCase     ,       DOWN * 2.4     ,       aligned_edge=key_text.get_left()			)
        self.add(__lowerCAmelCase			)

        lowercase__    :   Union[str, Any]						= MarkupText(
            F"""Based on the passed in configuration, weights are stored in\na variety of np.memmaps on disk or to a particular device."""     ,       font_size=24     ,       )
        step_a.move_to([2, 2, 0]			)

        lowercase__    :   Tuple						= [meta_mem.copy() for i in range(6			)]
        lowercase__    :   Any						= [meta_mem.copy() for i in range(6			)]
        lowercase__    :   str						= VGroup(*__lowerCAmelCase			).arrange(__lowerCAmelCase     ,       buff=0			)
        lowercase__    :   Any						= VGroup(*__lowerCAmelCase			).arrange(__lowerCAmelCase     ,       buff=0			)
        lowercase__    :   Union[str, Any]						= VGroup(__lowerCAmelCase     ,       __lowerCAmelCase			).arrange(__lowerCAmelCase     ,       buff=0			)
        lowercase__    :   Union[str, Any]						= Text('''Disk'''     ,       font_size=24			)
        lowercase__    :   Tuple						= Group(__lowerCAmelCase     ,       __lowerCAmelCase			).arrange(__lowerCAmelCase     ,       buff=0.5     ,       aligned_edge=__lowerCAmelCase			)
        disk.move_to([-4.0, -1.2_5, 0]			)
        self.play(Write(__lowerCAmelCase     ,       run_time=3			)     ,       Write(__lowerCAmelCase     ,       run_time=1			)     ,       Create(__lowerCAmelCase     ,       run_time=1			)			)

        lowercase__    :   Tuple						= []
        for i, rect in enumerate(__lowerCAmelCase			):
         lowercase__    :   Dict						= rect.copy()
         target.generate_target()
         target.target.move_to(disk_left_col_base[i]			).scale(0.5			)
         animations.append(MoveToTarget(__lowerCAmelCase     ,       run_time=1.5			)			)
        self.play(*__lowerCAmelCase			)

        self.play(FadeOut(__lowerCAmelCase			)			)

        lowercase__    :   Dict						= MarkupText(F"""Then, the checkpoint is removed from memory\nthrough garbage collection."""     ,       font_size=24			)
        step_a.move_to([2, 2, 0]			)

        self.play(Write(__lowerCAmelCase     ,       run_time=3			)			)

        self.play(
            FadeOut(__lowerCAmelCase     ,       __lowerCAmelCase     ,       *__lowerCAmelCase     ,       *__lowerCAmelCase			)     ,       )

        self.wait()

