

'''simple docstring'''
from manim import *







class 				A__       (			__snake_case    ):





  def 		A    (						self :      Dict					)      ->       Dict:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE				       =Rectangle(height=0.5				,   width=0.5					)
       _SCREAMING_SNAKE_CASE				       =Rectangle(height=0.46				,   width=0.46					).set_stroke(width=0					)

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

       _SCREAMING_SNAKE_CASE				       =[mem.copy() for i in range(4					)]
       _SCREAMING_SNAKE_CASE				       =VGroup(*A__					).arrange(A__				,   buff=0					)
       _SCREAMING_SNAKE_CASE				       =Text('GPU'				,   font_size=24					)
       _SCREAMING_SNAKE_CASE				       =Group(A__				,   A__					).arrange(A__				,   buff=0.5				,   aligned_edge=A__					)
       gpu.move_to([-1, -1, 0]					)
       self.add(A__					)

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

       _SCREAMING_SNAKE_CASE				       =Text('Model'				,   font_size=24					)
       _SCREAMING_SNAKE_CASE				       =Group(A__				,   A__					).arrange(A__				,   buff=0.5				,   aligned_edge=A__					)
       model.move_to([3, -1.0, 0]					)
       self.add(A__					)

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

            _SCREAMING_SNAKE_CASE				       =Rectangle(height=0.46 / 4				,   width=0.46 / 3					).set_stroke(width=0.0					).set_fill(A__				,   opacity=0.7					)

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

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

       _SCREAMING_SNAKE_CASE				       =Text('Loaded Checkpoint'				,   font_size=24					)
       _SCREAMING_SNAKE_CASE				       =Group(A__				,   A__					).arrange(A__				,   aligned_edge=A__				,   buff=0.4					)
       checkpoint.move_to([3, 0.5, 0]					)

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

       _SCREAMING_SNAKE_CASE				       =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(A__				,   A__					)

       _SCREAMING_SNAKE_CASE				       =MarkupText(
           f"<span fgcolor='{BLUE}'>●</span> Checkpoint"				,   font_size=18				,   )

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

       _SCREAMING_SNAKE_CASE				       =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(A__					)				,   Write(A__					)					)

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

       _SCREAMING_SNAKE_CASE				       =[]
       _SCREAMING_SNAKE_CASE				       =[]
       for i, rect in enumerate(A__					):
            _SCREAMING_SNAKE_CASE				       =fill.copy().set_fill(A__				,   opacity=0.7					)
            target.move_to(A__					)
            first_animations.append(GrowFromCenter(A__				,   run_time=1					)					)

            _SCREAMING_SNAKE_CASE				       =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(A__				,   run_time=1.5					)					)

       self.play(*A__					)
       self.play(*A__					)
       self.wait()








from arguments import InitializationArguments

from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser


# Configuration
_UpperCamelCase			:	List[str]								=HfArgumentParser(InitializationArguments)
_UpperCamelCase			:	Dict								=parser.parse_args()

# Load codeparrot tokenizer trained for Python code tokenization
_UpperCamelCase			:	List[Any]								=AutoTokenizer.from_pretrained(args.tokenizer_name)

# Config: "scale_attn_by_layer_idx" and "reorder_and_upcast_attn" are Mistral stability tweaks
_UpperCamelCase			:	str								={
    'vocab_size': len(tokenizer),
    'scale_attn_by_inverse_layer_idx': True,
    'reorder_and_upcast_attn': True,
}

# Load model config (GPT-2 large in this case)
_UpperCamelCase			:	int								=AutoConfig.from_pretrained(args.config_name, **config_kwargs)

# Initialize new model with config
_UpperCamelCase			:	List[str]								=AutoModelForCausalLM.from_config(config)

# Save model to the hub
model.save_pretrained(args.model_name, push_to_hub=args.push_to_hub)



