
'''simple docstring'''






from manim import *

class 			UpperCAmelCase__    (							A			):



    def 	lowerCamelCase_	(						self   :							Any  ):
          _lowerCamelCase					: Optional[int]		    = Rectangle(height=0.5,width=0.5  )
          _lowerCamelCase					: Tuple		    = Rectangle(height=0.46,width=0.46  ).set_stroke(width=0  )

          _lowerCamelCase					: Union[str, Any]		    = [mem.copy() for i in range(6  )]
          _lowerCamelCase					: Tuple		    = [mem.copy() for i in range(6  )]
          _lowerCamelCase					: Tuple		    = VGroup(*__A  ).arrange(__A,buff=0  )
          _lowerCamelCase					: Optional[Any]		    = VGroup(*__A  ).arrange(__A,buff=0  )
          _lowerCamelCase					: str		    = VGroup(__A,__A  ).arrange(__A,buff=0  )
          _lowerCamelCase					: str		    = Text("CPU",font_size=2_4  )
          _lowerCamelCase					: Any		    = Group(__A,__A  ).arrange(__A,buff=0.5,aligned_edge=__A  )
          cpu.move_to([-2.5, -0.5, 0]  )
          self.add(__A  )

          _lowerCamelCase					: Union[str, Any]		    = [mem.copy() for i in range(1  )]
          _lowerCamelCase					: List[Any]		    = VGroup(*__A  ).arrange(__A,buff=0  )
          _lowerCamelCase					: Union[str, Any]		    = Text("GPU",font_size=2_4  )
          _lowerCamelCase					: Tuple		    = Group(__A,__A  ).arrange(__A,buff=0.5,aligned_edge=__A  )
          gpu.align_to(__A,__A  )
          gpu.set_x(gpu.get_x() - 1  )

          self.add(__A  )

          _lowerCamelCase					: Union[str, Any]		    = [mem.copy() for i in range(6  )]
          _lowerCamelCase					: Optional[int]		    = VGroup(*__A  ).arrange(__A,buff=0  )

          _lowerCamelCase					: Optional[Any]		    = Text("Model",font_size=2_4  )
          _lowerCamelCase					: Optional[Any]		    = Group(__A,__A  ).arrange(__A,buff=0.5,aligned_edge=__A  )
          model.move_to([3, -1.0, 0]  )

          self.play(
              Create(__A,run_time=1  ),Create(__A,run_time=1  ),Create(__A,run_time=1  ),)

          _lowerCamelCase					: List[Any]		    = MarkupText(
              f'First, an empty model skeleton is loaded\ninto <span fgcolor=\'{YELLOW}\'>memory</span> without using much RAM.',font_size=2_4,)

          _lowerCamelCase					: Tuple		    = Square(side_length=2.2  )
          key.move_to([-5, 2, 0]  )

          _lowerCamelCase					: Dict		    = MarkupText(
              f'<b>Key:</b>\n\n<span fgcolor=\'{YELLOW}\'>●</span> Empty Model',font_size=1_8,)

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

          step_a.move_to([2, 2, 0]  )
          self.play(Write(__A,run_time=2.5  ),Write(__A  ),Write(__A  )  )

          self.add(__A  )

          _lowerCamelCase					: Union[str, Any]		    = []
          _lowerCamelCase					: Dict		    = []
          _lowerCamelCase					: int		    = []
          for i, rect in enumerate(__A  ):
                _lowerCamelCase					: Any		    = Rectangle(height=0.46,width=0.46  ).set_stroke(width=0.0  ).set_fill(__A,opacity=0.7  )
                cpu_target.move_to(__A  )
                cpu_target.generate_target()
                _lowerCamelCase					: Union[str, Any]		    = 0.46 / 4
                _lowerCamelCase					: Optional[int]		    = 0.46 / 3

                if i == 0:
                      cpu_target.target.next_to(cpu_left_col_base[0].get_corner(DOWN + LEFT  ),buff=0.02,direction=__A  )
                      cpu_target.target.set_x(cpu_target.target.get_x() + 0.1  )
                elif i == 3:
                      cpu_target.target.next_to(cpu_targs[0].target,direction=__A,buff=0.0  )
                else:
                      cpu_target.target.next_to(cpu_targs[i - 1].target,direction=__A,buff=0.0  )
                cpu_targs.append(__A  )

                first_animations.append(rect.animate(run_time=0.5  ).set_stroke(__A  )  )
                second_animations.append(MoveToTarget(__A,run_time=1.5  )  )

          self.play(*__A  )
          self.play(*__A  )

          self.wait()



from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest


@require_tokenizers
class      __lowerCAmelCase  (			a       ):






  """simple docstring"""





  _SCREAMING_SNAKE_CASE		     =							DistilBertTokenizer
  _SCREAMING_SNAKE_CASE		     =							DistilBertTokenizerFast
  _SCREAMING_SNAKE_CASE		     =							True



  @slow
  def        lowerCAmelCase__	(  self							:							Tuple	) ->			Optional[Any]:




     """simple docstring"""
     snake_case_            =       DistilBertTokenizer.from_pretrained("distilbert-base-uncased"	)

     snake_case_            =       tokenizer.encode("sequence builders"     ,					add_special_tokens=_lowerCAmelCase	)
     snake_case_            =       tokenizer.encode("multi-sequence build"     ,					add_special_tokens=_lowerCAmelCase	)

     snake_case_            =       tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase	)
     snake_case_            =       tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase     ,					_lowerCAmelCase	)

     assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
     assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
         tokenizer.sep_token_id
     ]




