






from manim import *






class 					SCREAMING_SNAKE_CASE_  (       _a ):
       """simple docstring"""


       def 				UpperCamelCase__						(				self	:List[str]):



          """simple docstring"""

          _lowercase              =Rectangle(height=0.5,      width=0.5)
          _lowercase              =Rectangle(height=0.4_6,      width=0.4_6).set_stroke(width=0)

          _lowercase              =[mem.copy() for i in range(6)]
          _lowercase              =[mem.copy() for i in range(6)]
          _lowercase              =VGroup(*snake_case).arrange(snake_case,      buff=0)
          _lowercase              =VGroup(*snake_case).arrange(snake_case,      buff=0)
          _lowercase              =VGroup(snake_case,      snake_case).arrange(snake_case,      buff=0)
          _lowercase              =Text('CPU',      font_size=24)
          _lowercase              =Group(snake_case,      snake_case).arrange(snake_case,      buff=0.5,      aligned_edge=snake_case)
          cpu.move_to([-2.5, -0.5, 0])
          self.add(snake_case)

          _lowercase              =[mem.copy() for i in range(1)]
          _lowercase              =VGroup(*snake_case).arrange(snake_case,      buff=0)
          _lowercase              =Text('GPU',      font_size=24)
          _lowercase              =Group(snake_case,      snake_case).arrange(snake_case,      buff=0.5,      aligned_edge=snake_case)
          gpu.align_to(snake_case,      snake_case)
          gpu.set_x(gpu.get_x() - 1)

          self.add(snake_case)

          _lowercase              =[mem.copy() for i in range(6)]
          _lowercase              =VGroup(*snake_case).arrange(snake_case,      buff=0)

          _lowercase              =Text('Model',      font_size=24)
          _lowercase              =Group(snake_case,      snake_case).arrange(snake_case,      buff=0.5,      aligned_edge=snake_case)
          model.move_to([3, -1.0, 0])

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

          _lowercase              =MarkupText(
              f'''First, an empty model skeleton is loaded\ninto <span fgcolor=\'{YELLOW}\'>memory</span> without using much RAM.''',      font_size=24,      )

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

          _lowercase              =MarkupText(
              f'''<b>Key:</b>\n\n<span fgcolor=\'{YELLOW}\'>●</span> Empty Model''',      font_size=18,      )

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

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

          self.add(snake_case)

          _lowercase              =[]
          _lowercase              =[]
          _lowercase              =[]
          for i, rect in enumerate(snake_case):
             _lowercase              =Rectangle(height=0.4_6,      width=0.4_6).set_stroke(width=0.0).set_fill(snake_case,      opacity=0.7)
             cpu_target.move_to(snake_case)
             cpu_target.generate_target()
             _lowercase              =0.4_6 / 4
             _lowercase              =0.4_6 / 3

             if i == 0:
                cpu_target.target.next_to(cpu_left_col_base[0].get_corner(DOWN + LEFT),      buff=0.0_2,      direction=snake_case)
                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=snake_case,      buff=0.0)
             else:
                cpu_target.target.next_to(cpu_targs[i - 1].target,      direction=snake_case,      buff=0.0)
             cpu_targs.append(snake_case)

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

          self.play(*snake_case)
          self.play(*snake_case)

          self.wait()










import torch

from transformers import AutoModel






class 					SCREAMING_SNAKE_CASE_  (       torch.nn.Module ):
       """simple docstring"""


       def __init__(				self	:Dict,      snake_case	:str="sayef/fsner-bert-base-uncased"):



          """simple docstring"""

          super(snake_case,      self).__init__()

          _lowercase              =AutoModel.from_pretrained(snake_case,      return_dict=snake_case)
          _lowercase              =torch.nn.CosineSimilarity(3,      1e-0_8)
          _lowercase              =torch.nn.Softmax(dim=1)





       def 				UpperCamelCase__						(				self	:str,      **snake_case	:int):



          """simple docstring"""

          return self.bert(**snake_case).last_hidden_state





       def 				UpperCamelCase__						(				self	:Union[str, Any],      snake_case	:Optional[Any]):



          """simple docstring"""

          return token_embeddings.sum(2,      keepdim=snake_case)





       def 				UpperCamelCase__						(				self	:List[Any],      snake_case	:int,      snake_case	:Dict,      snake_case	:Dict=1):



          """simple docstring"""

          return self.softmax(T * self.cos(snake_case,      snake_case))





       def 				UpperCamelCase__						(				self	:List[str],      snake_case	:int,      snake_case	:List[str]):



          """simple docstring"""

          _lowercase              =W_supports['sizes'].tolist()
          _lowercase              =W_supports['start_token_id'].item()
          _lowercase              =W_supports['end_token_id'].item()

          del W_supports["sizes"]
          del W_supports["start_token_id"]
          del W_supports["end_token_id"]

          _lowercase              =self.BERT(**snake_case)
          _lowercase              =self.BERT(**snake_case)

          _lowercase              =None
          _lowercase              =None

          _lowercase              =W_supports['input_ids'] == start_token_id
          _lowercase              =W_supports['input_ids'] == end_token_id

          for i, size in enumerate(snake_case):
             if i == 0:
                _lowercase              =0
             else:
                _lowercase              =support_sizes[i - 1]

             _lowercase              =S[s : s + size][start_token_masks[s : s + size]]
             _lowercase              =S[s : s + size][end_token_masks[s : s + size]]

             _lowercase              =torch.matmul(q[i],      s_start.T).sum(1).softmax(0)
             _lowercase              =torch.matmul(q[i],      s_end.T).sum(1).softmax(0)

             if p_starts is not None:
                _lowercase              =torch.vstack((p_starts, p_start))
                _lowercase              =torch.vstack((p_ends, p_end))
             else:
                _lowercase              =p_start
                _lowercase              =p_end

          return p_starts, p_ends


