Update ToC

Author: mikebo93

chapter_compiler_frontend/Index.md

@@ -23,3 +23,16 @@ The learning objectives of this chapter include:
 
 -   Understanding common frontend compilation optimization methods used
     by AI compilers.
+
+```toc
+:maxdepth: 2
+
+Overview_of_AI_Compilers
+Overview_of_AI_Compiler_Frontends
+Intermediate_Representation
+Automatic_Differentiation
+Type_Systems_and_Static_Analysis
+Frontend_Compilation_Optimization
+Chapter_Summary
+Further_Reading
+```

chapter_compiler_frontend/index.md

@@ -0,0 +1,38 @@
+# AI Compiler Frontend
+
+Tailored for machine learning frameworks, an AI compiler is designed to
+convert Python-based machine learning programs into their optimized
+forms, enabling efficient native execution on heterogeneous processors.
+This chapter first outlines the typical architecture of an AI compiler
+before delving into the design of the compiler's frontend. The compiler
+frontend incorporates various techniques, including intermediate
+representations (IRs), automatic differentiation, type systems, static
+analysis, and compilation optimization.
+
+The learning objectives of this chapter include:
+
+-   Understanding the typical architecture of an AI compiler.
+
+-   Understanding the types and implementation of IRs in machine
+    learning frameworks.
+
+-   Understanding the methods of automatic differentiation implemented
+    in AI compilers.
+
+-   Understanding type systems and static analysis in AI compilers.
+
+-   Understanding common frontend compilation optimization methods used
+    by AI compilers.
+
+```toc
+:maxdepth: 2
+
+Overview_of_AI_Compilers
+Overview_of_AI_Compiler_Frontends
+Intermediate_Representation
+Automatic_Differentiation
+Type_Systems_and_Static_Analysis
+Frontend_Compilation_Optimization
+Chapter_Summary
+Further_Reading
+```