feat: 增加不同阶段的基础动画
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commit
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*
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!.gitignore
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!*.py
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!*.md
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@ -1,5 +1,5 @@
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"""
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AstrAI项目介绍视频 - 第一部分：开场白与项目定位
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AstrAI项目介绍视频 - Part 1: 开场白与项目定位
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"""
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from manim import *
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@ -22,14 +22,12 @@ class Part1_Intro(Scene):
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def play_logo_intro(self):
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"""Logo动画展示"""
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# 创建AstrAI Logo样式
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logo_text = Text(
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"AstrAI",
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font_size=72,
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font="SimHei",
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)
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# 创建副标题
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subtitle = Text(
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"轻量级 Transformer 训练推理框架",
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font_size=28,
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@ -37,40 +35,33 @@ class Part1_Intro(Scene):
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color=GRAY
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)
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# 居中排列
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logo_text.next_to(subtitle, UP, buff=0.3)
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subtitle.next_to(logo_text, DOWN, buff=0.3)
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# 初始状态
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logo_text.set_opacity(0)
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subtitle.set_opacity(0)
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# 动画：淡入Logo
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self.play(
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FadeIn(logo_text, shift=UP * 0.5, scale=1.2),
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run_time=1.5
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)
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# 动画：淡入副标题
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self.play(
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FadeIn(subtitle, shift=UP * 0.3),
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run_time=1.0
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)
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# 短暂停留
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self.wait(0.8)
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# 淡出
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self.play(
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FadeOut(logo_text),
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FadeOut(subtitle),
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run_time=0.8
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)
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self.wait(0.5)
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self.wait(0.3)
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def play_opening_speech(self):
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"""开场白"""
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# 第一段文字
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line1 = Text(
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"在当下的大语言模型时代，",
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font_size=32,
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@ -79,9 +70,8 @@ class Part1_Intro(Scene):
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line1.to_edge(UP, buff=1.0)
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self.play(Write(line1), run_time=1.0)
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self.wait(0.5)
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self.wait(0.3)
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# 第二段文字
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line2 = Text(
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"我们见证了GPT、LLaMA等庞然大物。",
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font_size=32,
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@ -90,9 +80,8 @@ class Part1_Intro(Scene):
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line2.next_to(line1, DOWN, buff=0.3)
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self.play(Write(line2), run_time=1.0)
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self.wait(0.5)
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self.wait(0.3)
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# 第三段文字
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line3 = Text(
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"然而，这些模型对硬件要求极高，",
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font_size=32,
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@ -101,9 +90,8 @@ class Part1_Intro(Scene):
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line3.next_to(line2, DOWN, buff=0.3)
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self.play(Write(line3), run_time=1.0)
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self.wait(0.5)
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self.wait(0.3)
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# 第四段文字（关键问题）
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line4 = Text(
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"对于普通开发者来说往往遥不可及。",
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font_size=32,
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@ -115,7 +103,6 @@ class Part1_Intro(Scene):
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self.play(Write(line4), run_time=1.0)
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self.wait(0.8)
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# 思考问题
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question = Text(
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"我们能否创建一个既有用又能运行在普通电脑上的模型？",
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font_size=28,
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@ -127,7 +114,6 @@ class Part1_Intro(Scene):
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self.play(Write(question), run_time=1.5)
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self.wait(1.0)
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# 清除场景
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self.play(
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FadeOut(line1),
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FadeOut(line2),
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@ -136,11 +122,10 @@ class Part1_Intro(Scene):
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FadeOut(question),
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run_time=0.8
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)
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self.wait(0.5)
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self.wait(0.3)
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def play_key_points(self):
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"""核心要点展示"""
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# 标题
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title = Text(
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"AstrAI 的核心特点",
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font_size=40,
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@ -150,9 +135,8 @@ class Part1_Intro(Scene):
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title.to_edge(UP, buff=0.8)
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self.play(Write(title), run_time=1.0)
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self.wait(0.5)
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self.wait(0.3)
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# 要点1：轻量级
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point1_title = Text(
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"轻量级",
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font_size=36,
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@ -175,9 +159,8 @@ class Part1_Intro(Scene):
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Write(point1_content),
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run_time=1.0
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)
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self.wait(0.8)
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self.wait(0.5)
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# 要点2：完全自研
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point2_title = Text(
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"完全自研",
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font_size=36,
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@ -201,9 +184,8 @@ class Part1_Intro(Scene):
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Write(point2_content),
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run_time=1.0
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)
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self.wait(0.8)
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self.wait(0.5)
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# 要点3：训练推理一体化
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point3_title = Text(
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"训练推理一体化",
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font_size=36,
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@ -229,7 +211,6 @@ class Part1_Intro(Scene):
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)
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self.wait(1.0)
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# 清除场景（保留标题）
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self.play(
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FadeOut(point1_title),
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FadeOut(point1_content),
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@ -243,7 +224,6 @@ class Part1_Intro(Scene):
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def play_project_name(self):
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"""项目名称与总结"""
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# 项目名称 - 使用普通颜色避免兼容性问题
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project_name = Text(
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"AstrAI",
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font_size=80,
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@ -252,14 +232,12 @@ class Part1_Intro(Scene):
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)
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project_name.center()
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# 动画：放大出现
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self.play(
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project_name.animate.scale(1.2),
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run_time=1.5
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)
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self.wait(1.0)
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self.wait(0.8)
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# 补充说明
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tagline = Text(
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"1B参数 · 中英双语 · 完全自研 · 训练推理一体化",
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font_size=24,
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@ -271,35 +249,9 @@ class Part1_Intro(Scene):
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self.play(Write(tagline), run_time=1.0)
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self.wait(1.0)
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# 淡出结束
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self.play(
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FadeOut(project_name),
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FadeOut(tagline),
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run_time=1.0
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)
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self.wait(0.5)
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# 配置类
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class AstrAIVideoConfig:
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"""视频配置"""
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video_quality = "high_quality" # high_quality, production_quality
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preview = True # 是否预览
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save_last_frame = True # 保存最后一帧
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if __name__ == "__main__":
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# 运行配置
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config = AstrAIVideoConfig()
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# 渲染视频
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if config.preview:
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# 预览模式
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from manim import *
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scene = Part1_Intro()
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scene.render()
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else:
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# 渲染视频文件
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# manim -pql main.py Part1_Intro
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# manim -pqh main.py Part1_Intro
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pass
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self.wait(0.3)
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"""
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AstrAI项目介绍视频 - Part 2: AstrAI的核心设计
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"""
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from manim import *
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class Part2_CoreDesign(Scene):
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"""第二部分：AstrAI的核心设计"""
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def construct(self):
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# 2.1 整体架构
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self.play_architecture()
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# 2.2 推理流程
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self.play_inference_flow()
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# 2.3 调度策略
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self.play_scheduler()
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# 2.4 内存优化
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self.play_memory_optimization()
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# 2.5 分布式支持
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self.play_distributed_support()
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def play_architecture(self):
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"""整体架构展示"""
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# 标题
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title = Text(
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"AstrAI 核心设计",
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font_size=48,
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font="SimHei",
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color=WHITE
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)
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title.to_edge(UP, buff=0.8)
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self.play(Write(title), run_time=1.0)
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self.wait(0.5)
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# 模块表格
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modules = [
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("astrai.config", "配置管理"),
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("astrai.dataset", "数据集加载"),
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("astrai.model", "神经网络模型"),
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("astrai.tokenize", "分词器和聊天模板"),
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("astrai.trainer", "训练工作流管理"),
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("astrai.inference", "推理调度"),
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("astrai.parallel", "分布式并行支持"),
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]
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# 创建模块列表
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module_objects = []
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for i, (module, desc) in enumerate(modules):
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module_text = Text(
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module,
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font_size=28,
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font="SimHei",
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color=BLUE
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)
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desc_text = Text(
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desc,
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font_size=20,
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font="SimHei",
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color=GRAY
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)
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module_text.shift(LEFT * 3)
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desc_text.next_to(module_text, RIGHT, buff=0.5)
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if i == 0:
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module_text.to_edge(UP, buff=2.5)
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else:
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module_text.next_to(module_objects[-1][0], DOWN, buff=0.4)
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desc_text.next_to(module_text, RIGHT, buff=0.5)
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self.play(Write(module_text), run_time=0.5)
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self.play(Write(desc_text), run_time=0.3)
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module_objects.append((module_text, desc_text))
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if i < len(modules) - 1:
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self.wait(0.2)
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self.wait(2.0)
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# 淡出
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self.play(
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FadeOut(title),
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*[FadeOut(m) for m, d in module_objects],
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*[FadeOut(d) for m, d in module_objects],
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run_time=0.8
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)
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self.wait(0.3)
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def play_inference_flow(self):
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"""推理流程：Prefill → Decode"""
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title = Text(
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"推理流程：Prefill → Decode",
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font_size=40,
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font="SimHei",
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color=WHITE
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)
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title.to_edge(UP, buff=0.8)
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self.play(Write(title), run_time=1.0)
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self.wait(0.3)
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# Pre-fill阶段
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prefill_box = RoundedRectangle(
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width=3.5,
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height=1.5,
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corner_radius=0.2,
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color=BLUE,
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fill_opacity=0.3
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)
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prefill_box.to_edge(LEFT, buff=2.0)
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prefill_title = Text(
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"Pre-fill",
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font_size=28,
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font="SimHei",
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color=BLUE
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)
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prefill_title.next_to(prefill_box, UP, buff=0.2)
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prefill_desc = Text(
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"一次性处理输入序列\n计算所有Token的K和V",
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font_size=16,
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font="SimHei",
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color=GRAY
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)
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prefill_desc.move_to(prefill_box)
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self.play(
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Create(prefill_box),
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Write(prefill_title),
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Write(prefill_desc),
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run_time=1.0
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)
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self.wait(0.5)
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# Decode阶段
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decode_box = RoundedRectangle(
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width=3.5,
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height=1.5,
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corner_radius=0.2,
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color=GREEN,
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fill_opacity=0.3
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)
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decode_box.to_edge(RIGHT, buff=2.0)
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decode_title = Text(
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"Decode",
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font_size=28,
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font="SimHei",
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color=GREEN
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)
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decode_title.next_to(decode_box, UP, buff=0.2)
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decode_desc = Text(
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"生成新Token\n从KV Cache读取K和V",
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font_size=16,
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font="SimHei",
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color=GRAY
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)
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decode_desc.move_to(decode_box)
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self.play(
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Create(decode_box),
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Write(decode_title),
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Write(decode_desc),
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run_time=1.0
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)
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self.wait(0.5)
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# 箭头
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arrow = Arrow(
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prefill_box.get_right(),
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decode_box.get_left(),
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buff=0.5,
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color=YELLOW
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)
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self.play(Create(arrow), run_time=0.5)
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self.wait(1.5)
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# 关键点说明
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key_point = Text(
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"KV Cache：避免重复计算，大幅提升效率",
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font_size=24,
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font="SimHei",
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color=YELLOW
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)
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key_point.to_edge(DOWN, buff=1.5)
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self.play(Write(key_point), run_time=1.0)
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self.wait(2.0)
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# 淡出
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self.play(
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FadeOut(title),
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FadeOut(prefill_box),
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FadeOut(prefill_title),
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FadeOut(prefill_desc),
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FadeOut(decode_box),
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FadeOut(decode_title),
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FadeOut(decode_desc),
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FadeOut(arrow),
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FadeOut(key_point),
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run_time=0.8
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)
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self.wait(0.3)
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def play_scheduler(self):
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"""调度策略"""
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title = Text(
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"调度策略：高效管理KV Cache",
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font_size=40,
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font="SimHei",
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color=WHITE
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)
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title.to_edge(UP, buff=0.8)
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self.play(Write(title), run_time=1.0)
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self.wait(0.3)
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# 连续批处理说明
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batch_title = Text(
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"连续批处理 (Continuous Batching)",
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font_size=32,
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font="SimHei",
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color=BLUE
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)
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batch_title.to_edge(LEFT, buff=1.5).shift(UP * 1.5)
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self.play(Write(batch_title), run_time=1.0)
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self.wait(0.3)
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features = [
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"动态批处理：新的请求可以随时加入",
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"立即释放：完成的任务立即释放资源",
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"大幅提高GPU利用率",
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]
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feature_texts = []
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for i, feature in enumerate(features):
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feature_text = Text(
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feature,
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font_size=22,
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font="SimHei",
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color=GRAY
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)
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feature_text.next_to(batch_title, DOWN, buff=0.4 + i * 0.5)
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feature_text.align_to(batch_title, LEFT)
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self.play(Write(feature_text), run_time=0.8)
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self.wait(0.3)
|
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feature_texts.append(feature_text)
|
||||
|
||||
self.wait(1.0)
|
||||
|
||||
# 前缀缓存
|
||||
prefix_title = Text(
|
||||
"前缀缓存 (Prefix Caching)",
|
||||
font_size=32,
|
||||
font="SimHei",
|
||||
color=GREEN
|
||||
)
|
||||
prefix_title.to_edge(RIGHT, buff=1.5).shift(UP * 1.5)
|
||||
|
||||
self.play(Write(prefix_title), run_time=1.0)
|
||||
self.wait(0.3)
|
||||
|
||||
prefix_desc = Text(
|
||||
"使用Radix Tree实现\n智能前缀提示加速",
|
||||
font_size=20,
|
||||
font="SimHei",
|
||||
color=GRAY
|
||||
)
|
||||
prefix_desc.next_to(prefix_title, DOWN, buff=0.4)
|
||||
prefix_desc.align_to(prefix_title, LEFT)
|
||||
|
||||
self.play(Write(prefix_desc), run_time=0.8)
|
||||
self.wait(2.0)
|
||||
|
||||
# 淡出 - 简化版本
|
||||
self.play(
|
||||
FadeOut(title),
|
||||
FadeOut(batch_title),
|
||||
FadeOut(prefix_title),
|
||||
FadeOut(prefix_desc),
|
||||
run_time=0.8
|
||||
)
|
||||
|
||||
for ft in feature_texts:
|
||||
self.play(FadeOut(ft), run_time=0.3)
|
||||
|
||||
self.wait(0.3)
|
||||
|
||||
def play_memory_optimization(self):
|
||||
"""内存优化"""
|
||||
title = Text(
|
||||
"内存优化：Radix Tree vs PagedAttention",
|
||||
font_size=40,
|
||||
font="SimHei",
|
||||
color=WHITE
|
||||
)
|
||||
title.to_edge(UP, buff=0.8)
|
||||
|
||||
self.play(Write(title), run_time=1.0)
|
||||
self.wait(0.3)
|
||||
|
||||
# Radix Tree 优势
|
||||
radix_title = Text(
|
||||
"Radix Tree 优势",
|
||||
font_size=28,
|
||||
font="SimHei",
|
||||
color=BLUE
|
||||
)
|
||||
radix_title.to_edge(LEFT, buff=2.0).shift(UP * 1.0)
|
||||
|
||||
self.play(Write(radix_title), run_time=1.0)
|
||||
|
||||
radix_features = [
|
||||
"自动合并共享前缀的请求",
|
||||
"智能复用已计算的KV Cache",
|
||||
"支持前缀提示加速",
|
||||
"基于LRU的缓存淘汰策略",
|
||||
]
|
||||
|
||||
radix_texts = []
|
||||
for i, feature in enumerate(radix_features):
|
||||
feature_text = Text(
|
||||
f"• {feature}",
|
||||
font_size=20,
|
||||
font="SimHei",
|
||||
color=GRAY
|
||||
)
|
||||
feature_text.next_to(radix_title, DOWN, buff=0.3 + i * 0.4)
|
||||
feature_text.align_to(radix_title, LEFT)
|
||||
|
||||
self.play(Write(feature_text), run_time=0.5)
|
||||
radix_texts.append(feature_text)
|
||||
|
||||
self.wait(1.0)
|
||||
|
||||
# 对比vLLM
|
||||
compare_title = Text(
|
||||
"对比 vLLM",
|
||||
font_size=28,
|
||||
font="SimHei",
|
||||
color=GREEN
|
||||
)
|
||||
compare_title.to_edge(RIGHT, buff=2.0).shift(UP * 1.0)
|
||||
|
||||
self.play(Write(compare_title), run_time=1.0)
|
||||
|
||||
compare_text = Text(
|
||||
"vLLM使用PagedAttention\nAstrAI使用Radix Tree\n\n两者都能减少内存碎片\n实现方式不同",
|
||||
font_size=18,
|
||||
font="SimHei",
|
||||
color=GRAY
|
||||
)
|
||||
compare_text.next_to(compare_title, DOWN, buff=0.3)
|
||||
compare_text.align_to(compare_title, LEFT)
|
||||
|
||||
self.play(Write(compare_text), run_time=1.0)
|
||||
self.wait(2.0)
|
||||
|
||||
# 淡出
|
||||
self.play(
|
||||
FadeOut(title),
|
||||
FadeOut(radix_title),
|
||||
FadeOut(compare_title),
|
||||
FadeOut(compare_text),
|
||||
run_time=0.8
|
||||
)
|
||||
|
||||
for rt in radix_texts:
|
||||
self.play(FadeOut(rt), run_time=0.3)
|
||||
|
||||
self.wait(0.3)
|
||||
|
||||
def play_distributed_support(self):
|
||||
"""分布式支持"""
|
||||
title = Text(
|
||||
"分布式支持：多卡推理",
|
||||
font_size=40,
|
||||
font="SimHei",
|
||||
color=WHITE
|
||||
)
|
||||
title.to_edge(UP, buff=0.8)
|
||||
|
||||
self.play(Write(title), run_time=1.0)
|
||||
self.wait(0.3)
|
||||
|
||||
# 并行方式
|
||||
parallel_title = Text(
|
||||
"支持的并行方式",
|
||||
font_size=32,
|
||||
font="SimHei",
|
||||
color=BLUE
|
||||
)
|
||||
parallel_title.to_edge(LEFT, buff=1.5).shift(UP * 1.5)
|
||||
|
||||
self.play(Write(parallel_title), run_time=1.0)
|
||||
|
||||
parallel_methods = [
|
||||
("数据并行", "多卡处理不同数据"),
|
||||
("模型并行", "将模型分片到不同卡"),
|
||||
("流水并行", "按层划分Pipeline"),
|
||||
]
|
||||
|
||||
method_texts = []
|
||||
for i, (method, desc) in enumerate(parallel_methods):
|
||||
method_text = Text(
|
||||
method,
|
||||
font_size=24,
|
||||
font="SimHei",
|
||||
color=GREEN
|
||||
)
|
||||
method_text.next_to(parallel_title, DOWN, buff=0.4 + i * 0.5)
|
||||
method_text.align_to(parallel_title, LEFT)
|
||||
|
||||
desc_text = Text(
|
||||
f" - {desc}",
|
||||
font_size=18,
|
||||
font="SimHei",
|
||||
color=GRAY
|
||||
)
|
||||
desc_text.next_to(method_text, RIGHT, buff=0.3)
|
||||
|
||||
self.play(Write(method_text), Write(desc_text), run_time=0.8)
|
||||
method_texts.append((method_text, desc_text))
|
||||
|
||||
self.wait(1.5)
|
||||
|
||||
# 代码示例
|
||||
code_title = Text(
|
||||
"分布式初始化",
|
||||
font_size=28,
|
||||
font="SimHei",
|
||||
color=ORANGE
|
||||
)
|
||||
code_title.to_edge(RIGHT, buff=1.5).shift(UP * 1.5)
|
||||
|
||||
self.play(Write(code_title), run_time=1.0)
|
||||
|
||||
code_text = Text(
|
||||
"setup_parallel()\nspawn_parallel_fn()\n\n支持NCCL后端",
|
||||
font_size=16,
|
||||
font="SimHei",
|
||||
color=GRAY
|
||||
)
|
||||
code_text.next_to(code_title, DOWN, buff=0.3)
|
||||
code_text.align_to(code_title, LEFT)
|
||||
|
||||
self.play(Write(code_text), run_time=1.0)
|
||||
self.wait(2.0)
|
||||
|
||||
# 淡出
|
||||
self.play(
|
||||
FadeOut(title),
|
||||
FadeOut(parallel_title),
|
||||
FadeOut(code_title),
|
||||
FadeOut(code_text),
|
||||
run_time=0.8
|
||||
)
|
||||
|
||||
for mt, dt in method_texts:
|
||||
self.play(FadeOut(mt), FadeOut(dt), run_time=0.3)
|
||||
|
||||
self.wait(0.5)
|
||||
Loading…
Reference in New Issue