

import os
from collections import deque

import torch
from torch.utils.data import Dataset



class 		a_       (							A__     ):



      """simple docstring"""







      def __init__(      self     :							Optional[int]			,snake_case     :							Optional[int]=""			,snake_case     :							List[Any]="train"				):
           assert os.path.isdir(__snake_case				)

           SCREAMING_SNAKE_CASE      						=[]
           SCREAMING_SNAKE_CASE      						=os.listdir(__snake_case				)
           for story_filename in story_filenames_list:
                if "summary" in story_filename:
                     continue
                SCREAMING_SNAKE_CASE      						=os.path.join(__snake_case			,__snake_case				)
                if not os.path.isfile(__snake_case				):
                     continue
                self.documents.append(__snake_case				)
      def __len__(      self     :							Dict				):
           return len(self.documents				)


      def __getitem__(      self     :							Union[str, Any]			,snake_case     :							List[str]				):
           SCREAMING_SNAKE_CASE      						=self.documents[idx]
           SCREAMING_SNAKE_CASE      						=document_path.split('/'				)[-1]
           with open(__snake_case			,encoding='utf-8'				) as source:
                SCREAMING_SNAKE_CASE      						=source.read()
                SCREAMING_SNAKE_CASE      						=process_story(__snake_case				)
           return document_name, story_lines, summary_lines







def 			snake_case__				(   lowerCAmelCase_			):





     """simple docstring"""







     SCREAMING_SNAKE_CASE      						=list(filter(lambda lowerCAmelCase_			: len(_lowerCAmelCase			) != 0,    [line.strip() for line in raw_story.split('\n'			)]			)			)

     # for some unknown reason some lines miss a period, add it
     SCREAMING_SNAKE_CASE      						=[_add_missing_period(_lowerCAmelCase			) for line in nonempty_lines]

     # gather article lines
     SCREAMING_SNAKE_CASE      						=[]
     SCREAMING_SNAKE_CASE      						=deque(_lowerCAmelCase			)
     while True:
          try:
               SCREAMING_SNAKE_CASE      						=lines.popleft()
               if element.startswith('@highlight'			):
                    break
               story_lines.append(_lowerCAmelCase			)
          except IndexError:
               # if "@highlight" is absent from the file we pop
               # all elements until there is None, raising an exception.
               return story_lines, []

    # gather summary lines
     SCREAMING_SNAKE_CASE      						=list(filter(lambda lowerCAmelCase_			: not t.startswith('@highlight'			),    _lowerCAmelCase			)			)

     return story_lines, summary_lines







def 			snake_case__				(   lowerCAmelCase_			):





     """simple docstring"""







     SCREAMING_SNAKE_CASE      						=['''.''', '''!''', '''?''', '''...''', '''\'''', '''`''', '''"''', '''\u2019''', '''\u2019''', ''')''']
     if line.startswith('@highlight'			):
          return line
     if line[-1] in END_TOKENS:
          return line
     return line + "."







def 			snake_case__				(   lowerCAmelCase_,    lowerCAmelCase_,    lowerCAmelCase_			):





     """simple docstring"""







     if len(_lowerCAmelCase			) > block_size:
          return sequence[:block_size]
     else:
          sequence.extend([pad_token_id] * (block_size - len(_lowerCAmelCase			))			)
          return sequence







def 			snake_case__				(   lowerCAmelCase_,    lowerCAmelCase_			):





     """simple docstring"""







     SCREAMING_SNAKE_CASE      						=torch.ones_like(_lowerCAmelCase			)
     SCREAMING_SNAKE_CASE      						=sequence == pad_token_id
     SCREAMING_SNAKE_CASE      						=0
     return mask







def 			snake_case__				(   lowerCAmelCase_,    lowerCAmelCase_,    lowerCAmelCase_			):





     """simple docstring"""







     SCREAMING_SNAKE_CASE      						=[tokenizer.encode(_lowerCAmelCase			) for line in story_lines]
     SCREAMING_SNAKE_CASE      						=[token for sentence in story_lines_token_ids for token in sentence]
     SCREAMING_SNAKE_CASE      						=[tokenizer.encode(_lowerCAmelCase			) for line in summary_lines]
     SCREAMING_SNAKE_CASE      						=[token for sentence in summary_lines_token_ids for token in sentence]

     return story_token_ids, summary_token_ids







def 			snake_case__				(   lowerCAmelCase_,    lowerCAmelCase_			):





     """simple docstring"""







     SCREAMING_SNAKE_CASE      						=[]
     for sequence in batch:
          SCREAMING_SNAKE_CASE      						=-1
          SCREAMING_SNAKE_CASE      						=[]
          for s in sequence:
               if s == separator_token_id:
                    sentence_num += 1
               embeddings.append(sentence_num % 2			)
          batch_embeddings.append(_lowerCAmelCase			)
     return torch.tensor(_lowerCAmelCase			)






'''simple docstring'''






from manim import *

class 				SCREAMING_SNAKE_CASE(							A__			):







	"""simple docstring"""






	def      A	(						self			:     Union[str, Any]		)			->		List[str]:
								UpperCAmelCase :       Optional[Any] 							=		Rectangle(height=0.5		,			width=0.5		)
								UpperCAmelCase :       str 							=		Rectangle(height=0.46		,			width=0.46		).set_stroke(width=0		)

								UpperCAmelCase :       Tuple 							=		[mem.copy() for i in range(6		)]
								UpperCAmelCase :       Optional[int] 							=		[mem.copy() for i in range(6		)]
								UpperCAmelCase :       Dict 							=		VGroup(*__snake_case		).arrange(__snake_case		,			buff=0		)
								UpperCAmelCase :       Any 							=		VGroup(*__snake_case		).arrange(__snake_case		,			buff=0		)
								UpperCAmelCase :       Union[str, Any] 							=		VGroup(__snake_case		,			__snake_case		).arrange(__snake_case		,			buff=0		)
								UpperCAmelCase :       Optional[Any] 							=		Text('''CPU'''		,			font_size=24		)
								UpperCAmelCase :       Union[str, Any] 							=		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		)

								UpperCAmelCase :       Optional[Any] 							=		[mem.copy() for i in range(4		)]
								UpperCAmelCase :       Union[str, Any] 							=		VGroup(*__snake_case		).arrange(__snake_case		,			buff=0		)
								UpperCAmelCase :       List[str] 							=		Text('''GPU'''		,			font_size=24		)
								UpperCAmelCase :       Dict 							=		Group(__snake_case		,			__snake_case		).arrange(__snake_case		,			buff=0.5		,			aligned_edge=__snake_case		)
								gpu.move_to([-1, -1, 0]		)
								self.add(__snake_case		)

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

								UpperCAmelCase :       List[str] 							=		Text('''Model'''		,			font_size=24		)
								UpperCAmelCase :       Tuple 							=		Group(__snake_case		,			__snake_case		).arrange(__snake_case		,			buff=0.5		,			aligned_edge=__snake_case		)
								model.move_to([3, -1.0, 0]		)
								self.add(__snake_case		)

								UpperCAmelCase :       Any 							=		[]
								for i, rect in enumerate(__snake_case		):
															rect.set_stroke(__snake_case		)
															# target = fill.copy().set_fill(YELLOW, opacity=0.7)
															# target.move_to(rect)
															# self.add(target)

															UpperCAmelCase :       Dict 							=		Rectangle(height=0.46 / 4		,			width=0.46 / 3		).set_stroke(width=0.0		).set_fill(__snake_case		,			opacity=0.7		)

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

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

								UpperCAmelCase :       Any 							=		Text('''Loaded Checkpoint'''		,			font_size=24		)
								UpperCAmelCase :       Union[str, Any] 							=		Group(__snake_case		,			__snake_case		).arrange(__snake_case		,			aligned_edge=__snake_case		,			buff=0.4		)
								checkpoint.move_to([3, 0.5, 0]		)

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

								UpperCAmelCase :       str 							=		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(__snake_case		,			__snake_case		)

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

								blue_text.next_to(__snake_case		,			DOWN * 2.4		,			aligned_edge=key_text.get_left()		)

								UpperCAmelCase :       List[Any] 							=		MarkupText(
								    F"""Next, a <i><span fgcolor=\"{BLUE}\">second</span></i> model is loaded into memory,\nwith the weights of a <span fgcolor=\"{BLUE}\">single shard</span>."""		,			font_size=24		,			)
								step_a.move_to([2, 2, 0]		)
								self.play(Write(__snake_case		)		,			Write(__snake_case		)		)

								self.play(Write(__snake_case		,			run_time=1		)		,			Create(__snake_case		,			run_time=1		)		)

								UpperCAmelCase :       Tuple 							=		[]
								UpperCAmelCase :       int 							=		[]
								for i, rect in enumerate(__snake_case		):
															UpperCAmelCase :       Any 							=		fill.copy().set_fill(__snake_case		,			opacity=0.7		)
															target.move_to(__snake_case		)
															first_animations.append(GrowFromCenter(__snake_case		,			run_time=1		)		)

															UpperCAmelCase :       List[str] 							=		target.copy()
															cpu_target.generate_target()
															if i < 5:
																						cpu_target.target.move_to(cpu_left_col_base[i + 1]		)
															else:
																						cpu_target.target.move_to(cpu_right_col_base[i - 5]		)
															second_animations.append(MoveToTarget(__snake_case		,			run_time=1.5		)		)

								self.play(*__snake_case		)
								self.play(*__snake_case		)
								self.wait()





