'''simple docstring'''





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mpnet import MPNetTokenizer


a		:  List[Any]   			=			logging.get_logger(__name__)

a		:  List[str]   			=			{'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

a		:  Union[str, Any]   			=			{
    '''vocab_file''': {
        '''microsoft/mpnet-base''': '''https://huggingface.co/microsoft/mpnet-base/resolve/main/vocab.txt''',
    },
    '''tokenizer_file''': {
        '''microsoft/mpnet-base''': '''https://huggingface.co/microsoft/mpnet-base/resolve/main/tokenizer.json''',
    },
}

a		:  List[str]   			=			{
    '''microsoft/mpnet-base''': 5_1_2,
}

a		:  Dict   			=			{
    '''microsoft/mpnet-base''': {'''do_lower_case''': True},
}




class     UpperCamelCase					(  snake_case__					):
  a    :str      					=				VOCAB_FILES_NAMES
  a    :Tuple      					=				PRETRAINED_VOCAB_FILES_MAP
  a    :Optional[Any]      					=				PRETRAINED_INIT_CONFIGURATION
  a    :List[str]      					=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  a    :Optional[Any]      					=				MPNetTokenizer
  a    :Optional[int]      					=				['input_ids', 'attention_mask']



  def __init__( self		,    __lowerCAmelCase=None		,    __lowerCAmelCase=None		,    __lowerCAmelCase=True		,    __lowerCAmelCase="<s>"		,    __lowerCAmelCase="</s>"		,    __lowerCAmelCase="</s>"		,    __lowerCAmelCase="<s>"		,    __lowerCAmelCase="[UNK]"		,    __lowerCAmelCase="<pad>"		,    __lowerCAmelCase="<mask>"		,    __lowerCAmelCase=True		,    __lowerCAmelCase=None		,    **__lowerCAmelCase		,    ):







      '''simple docstring'''


      super().__init__(
          __lowerCAmelCase		,    tokenizer_file=__lowerCAmelCase		,    do_lower_case=__lowerCAmelCase		,    bos_token=__lowerCAmelCase		,    eos_token=__lowerCAmelCase		,    sep_token=__lowerCAmelCase		,    cls_token=__lowerCAmelCase		,    unk_token=__lowerCAmelCase		,    pad_token=__lowerCAmelCase		,    mask_token=__lowerCAmelCase		,    tokenize_chinese_chars=__lowerCAmelCase		,    strip_accents=__lowerCAmelCase		,    **__lowerCAmelCase		,    )

      _a							:       int       					=			json.loads(self.backend_tokenizer.normalizer.__getstate__()   )
      if (
          pre_tok_state.get("""lowercase"""		,    __lowerCAmelCase   ) != do_lower_case
          or pre_tok_state.get("""strip_accents"""		,    __lowerCAmelCase   ) != strip_accents
      ):
          _a							:       Optional[int]       					=			getattr(__lowerCAmelCase		,    pre_tok_state.pop("""type"""   )   )
          _a							:       Optional[Any]       					=			do_lower_case
          _a							:       int       					=			strip_accents
          _a							:       str       					=			pre_tok_class(**__lowerCAmelCase   )

      _a							:       Tuple       					=			do_lower_case



  @property
  def 						a_       ( self   ):







      '''simple docstring'''


      if self._mask_token is None:
          if self.verbose:
              logger.error("""Using mask_token, but it is not set yet."""   )
          return None
      return str(self._mask_token   )



  @mask_token.setter
  def 						a_       ( self		,    __lowerCAmelCase   ):







      '''simple docstring'''


      _a							:       Optional[int]       					=			AddedToken(__lowerCAmelCase		,    lstrip=__lowerCAmelCase		,    rstrip=__lowerCAmelCase   ) if isinstance(__lowerCAmelCase		,    __lowerCAmelCase   ) else value
      _a							:       Tuple       					=			value



  def 						a_       ( self		,    __lowerCAmelCase		,    __lowerCAmelCase=None   ):







      '''simple docstring'''


      _a							:       List[str]       					=			[self.bos_token_id] + token_ids_a + [self.eos_token_id]
      if token_ids_a is None:
          return output

      return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]



  def 						a_       ( self		,    __lowerCAmelCase		,    __lowerCAmelCase = None   ):







      '''simple docstring'''


      _a							:       Any       					=			[self.sep_token_id]
      _a							:       Union[str, Any]       					=			[self.cls_token_id]

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



  def 						a_       ( self		,    __lowerCAmelCase		,    __lowerCAmelCase = None   ):







      '''simple docstring'''


      _a							:       Optional[Any]       					=			self._tokenizer.model.save(__lowerCAmelCase		,    name=__lowerCAmelCase   )
      return tuple(__lowerCAmelCase   )








'''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 						a_       ( self   ):







      '''simple docstring'''


      _a							:       List[Any]       					=			"""runwayml/stable-diffusion-v1-5"""
      _a							:       Tuple       					=			TextToVideoZeroPipeline.from_pretrained(__lowerCAmelCase		,    torch_dtype=torch.floataa   ).to("""cuda"""   )
      _a							:       Dict       					=			DDIMScheduler.from_config(pipe.scheduler.config   )
      _a							:       int       					=			torch.Generator(device="""cuda"""   ).manual_seed(0   )

      _a							:       Union[str, Any]       					=			"""A bear is playing a guitar on Times Square"""
      _a							:       List[Any]       					=			pipe(prompt=__lowerCAmelCase		,    generator=__lowerCAmelCase   ).images

      _a							:       Any       					=			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(__lowerCAmelCase		,    __lowerCAmelCase   )


