
'''simple docstring'''





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

from ...tokenization_utils_fast import AddedToken, PreTrainedTokenizerFast
from ...utils import logging


a__						:				str           =    logging.get_logger(__name__)

a__						:				int           =    {"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

a__						:				Union[str, Any]           =    {
    "vocab_file": {
        "TsinghuaAI/CPM-Generate": "https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model",
    },
    "tokenizer_file": {
        "TsinghuaAI/CPM-Generate": "https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/tokenizer.json",
    },
}


class 	UpperCamelCase__					(      lowerCAmelCase_):






 def __init__(     self					:Tuple		,			_A					:Union[str, Any]=None		,			_A					:int=None		,			_A					:Tuple=False		,			_A					:List[str]=True		,			_A					:Tuple=False		,			_A					:Union[str, Any]="<s>"		,			_A					:Optional[int]="</s>"		,			_A					:Any="<unk>"		,			_A					:Optional[Any]="<sep>"		,			_A					:Optional[Any]="<pad>"		,			_A					:Optional[int]="<cls>"		,			_A					:int="<mask>"		,			_A					:Optional[Any]=["<eop>", "<eod>"]		,			**_A					:Dict		,			)			->     Tuple:







       '''simple docstring'''



       __A    		=     AddedToken(_snake_case		,			lstrip=_snake_case		,			rstrip=_snake_case     ) if isinstance(_snake_case		,			_snake_case     ) else mask_token

       super().__init__(
           vocab_file=_snake_case		,			tokenizer_file=_snake_case		,			do_lower_case=_snake_case		,			remove_space=_snake_case		,			keep_accents=_snake_case		,			bos_token=_snake_case		,			eos_token=_snake_case		,			unk_token=_snake_case		,			sep_token=_snake_case		,			pad_token=_snake_case		,			cls_token=_snake_case		,			mask_token=_snake_case		,			additional_special_tokens=_snake_case		,			**_snake_case		,			)

       __A    		=     3
       __A    		=     do_lower_case
       __A    		=     remove_space
       __A    		=     keep_accents
       __A    		=     vocab_file
       __A    		=     False if not self.vocab_file else True

       try:
             import jieba
       except ModuleNotFoundError as error:
             raise error.__class__(
                 'You need to install jieba to use CpmTokenizer or CpmTokenizerFast. '
                 'See https://pypi.org/project/jieba/ for installation.'     )
       __A    		=     jieba
       __A    		=     str.maketrans(' \n'		,			'\u2582\u2583'     )






 def 		lowercase_  (     self					:List[Any]		,			_A					:List[int]		,			_A					:Optional[List[int]] = None     )			->     List[int]:







       '''simple docstring'''



       __A    		=     [self.sep_token_id]
       __A    		=     [self.cls_token_id]
       if token_ids_a is None:
             return token_ids_a + sep + cls
       return token_ids_a + sep + token_ids_a + sep + cls






 def 		lowercase_  (     self					:List[Any]		,			_A					:List[int]		,			_A					:Optional[List[int]] = None     )			->     List[int]:







       '''simple docstring'''



       __A    		=     [self.sep_token_id]
       __A    		=     [2]

       if token_ids_a is None:
             return len(token_ids_a + sep     ) * [0] + cls_segment_id
       return len(token_ids_a + sep     ) * [0] + len(token_ids_a + sep     ) * [1] + cls_segment_id






 def 		lowercase_  (     self					:str		,			_A					:str		,			_A					:Optional[str] = None     )			->     Tuple[str]:







       '''simple docstring'''



       if not self.can_save_slow_tokenizer:
             raise ValueError(
                 'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
                 'tokenizer.'     )

       if not os.path.isdir(_snake_case     ):
             logger.error(F'Vocabulary path ({save_directory}) should be a directory'     )
             return
       __A    		=     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     ):
             copyfile(self.vocab_file		,			_snake_case     )

       return (out_vocab_file,)






 def 		lowercase_  (     self					:str		,			_A					:Union[str, Any]		,			*_A					:Optional[int]		,			**_A					:Tuple     )			->     List[Any]:







       '''simple docstring'''



       __A    		=     [
           ' '.join([x.translate(self.translator     ) for x in self.jieba.cut(_snake_case		,			cut_all=_snake_case     )]     )
           for text in batch_text_or_text_pairs
       ]
       return super()._batch_encode_plus(_snake_case		,			*_snake_case		,			**_snake_case     )






 def 		lowercase_  (     self					:str		,			*_A					:str		,			**_A					:Dict     )			->     List[Any]:







       '''simple docstring'''



       __A    		=     super()._decode(*_snake_case		,			**_snake_case     )
       __A    		=     text.replace(' '		,			''     ).replace('\u2582'		,			' '     ).replace('\u2583'		,			'\n'     )
       return text








'''simple docstring'''





import unittest

import torch

from diffusers import DDIMScheduler, TextToVideoZeroPipeline
from diffusers.utils import load_pt, require_torch_gpu, slow

from ..test_pipelines_common import assert_mean_pixel_difference


@slow
@require_torch_gpu
class 	UpperCamelCase__					(      unittest.TestCase):






 def 		lowercase_  (     self					:Optional[int]     )			->     List[Any]:







       '''simple docstring'''



       __A    		=     'runwayml/stable-diffusion-v1-5'
       __A    		=     TextToVideoZeroPipeline.from_pretrained(_A		,			torch_dtype=torch.floataa     ).to('cuda'     )
       __A    		=     DDIMScheduler.from_config(pipe.scheduler.config     )
       __A    		=     torch.Generator(device='cuda'     ).manual_seed(0     )

       __A    		=     'A bear is playing a guitar on Times Square'
       __A    		=     pipe(prompt=_A		,			generator=_A     ).images

       __A    		=     load_pt(
           'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text-to-video/A bear is playing a guitar on Times Square.pt'     )

       assert_mean_pixel_difference(_A		,			_A     )






