[mlir] Add tutorial index.md pages

[jpienaar]

Summary

Sets the content for the section entry pages Hugo side.

[mehdi_amini]

Thanks!

mlir/docs/Tutorials/Toy/Ch-1.md

-# Chapter 1: Toy Tutorial Introduction
+# Chapter 1: Toy Language and AST
 
 [TOC]
 
-This tutorial runs through the implementation of a basic toy language on top of
-MLIR. The goal of this tutorial is to introduce the concepts of MLIR; in
-particular, how [dialects](../../LangRef.md#dialects) can help easily support
-language specific constructs and transformations while still offering an easy
-path to lower to LLVM or other codegen infrastructure. This tutorial is based on
-the model of the
-[LLVM Kaleidoscope Tutorial](https://llvm.org/docs/tutorial/MyFirstLanguageFrontend/index.html).
-
-This tutorial assumes you have cloned and built MLIR; if you have not yet done
-so, see
-[Getting started with MLIR](https://mlir.llvm.org/getting_started/).
-
-## The Chapters
-
-This tutorial is divided in the following chapters:
-
--   [Chapter #1](Ch-1.md): Introduction to the Toy language and the definition
-    of its AST.
--   [Chapter #2](Ch-2.md): Traversing the AST to emit a dialect in MLIR,
-    introducing base MLIR concepts. Here we show how to start attaching
-    semantics to our custom operations in MLIR.
--   [Chapter #3](Ch-3.md): High-level language-specific optimization using
-    pattern rewriting system.
--   [Chapter #4](Ch-4.md): Writing generic dialect-independent transformations
-    with Interfaces. Here we will show how to plug dialect specific information
-    into generic transformations like shape inference and inlining.
--   [Chapter #5](Ch-5.md): Partially lowering to lower-level dialects. We'll
-    convert some of our high level language specific semantics towards a generic
-    affine oriented dialect for optimization.
--   [Chapter #6](Ch-6.md): Lowering to LLVM and code generation. Here we'll
-    target LLVM IR for code generation, and detail more of the lowering
-    framework.
--   [Chapter #7](Ch-7.md): Extending Toy: Adding support for a composite type.
-    We'll demonstrate how to add a custom type to MLIR, and how it fits in the
-    existing pipeline.
-
 ## The Language
 
 This tutorial will be illustrated with a toy language that we’ll call “Toy”
 (naming is hard...). Toy is a tensor-based language that allows you to define
 functions, perform some math computation, and print results.
 
 Given that we want to keep things simple, the codegen will be limited to tensors
 of rank <= 2, and the only datatype in Toy is a 64-bit floating point type (aka

mlir/docs/Tutorials/Toy/_index.md

+# Toy Tutorial
+
+This tutorial runs through the implementation of a basic toy language on top of
+MLIR. The goal of this tutorial is to introduce the concepts of MLIR; in
+particular, how [dialects](../../LangRef.md#dialects) can help easily support
+language specific constructs and transformations while still offering an easy
+path to lower to LLVM or other codegen infrastructure. This tutorial is based on
+the model of the
+[LLVM Kaleidoscope Tutorial](https://llvm.org/docs/tutorial/MyFirstLanguageFrontend/index.html).
+
+This tutorial assumes you have cloned and built MLIR; if you have not yet done
+so, see
+[Getting started with MLIR](https://mlir.llvm.org/getting_started/).
+
+This tutorial is divided in the following chapters:
+
+-   [Chapter #1](Ch-1.md): Introduction to the Toy language and the definition
+    of its AST.
+-   [Chapter #2](Ch-2.md): Traversing the AST to emit a dialect in MLIR,
+    introducing base MLIR concepts. Here we show how to start attaching
+    semantics to our custom operations in MLIR.
+-   [Chapter #3](Ch-3.md): High-level language-specific optimization using
+    pattern rewriting system.
+-   [Chapter #4](Ch-4.md): Writing generic dialect-independent transformations
+    with Interfaces. Here we will show how to plug dialect specific information
+    into generic transformations like shape inference and inlining.
+-   [Chapter #5](Ch-5.md): Partially lowering to lower-level dialects. We'll
+    convert some of our high level language specific semantics towards a generic
+    affine oriented dialect for optimization.
+-   [Chapter #6](Ch-6.md): Lowering to LLVM and code generation. Here we'll
+    target LLVM IR for code generation, and detail more of the lowering
+    framework.
+-   [Chapter #7](Ch-7.md): Extending Toy: Adding support for a composite type.
+    We'll demonstrate how to add a custom type to MLIR, and how it fits in the
+    existing pipeline.
+
+The [first chapter](Ch-1.md) will introduce the Toy language and AST.

mlir/docs/Tutorials/_index.md

+# Tutorials
+
+This section contains multiple MLIR tutorials.
+See [Toy tutorial](toy) for an introduction to using MLIR infrastructure.