[mlir][docs] Capitalize "Transform" in "transform dialect" (llvm#76840)

A mix of "Transform dialect" and "transform dialect" is used ATM. This
patch capitalizes the outstanding instances of "transform".

mlir/docs/Dialects/Transform.md

@@ -19,7 +19,7 @@ operations, and then applying loop unrolling to the inner loops produced by the
 previous transformations. As such, it is not intended as a replacement for the
 pass infrastructure, nor for the pattern rewriting infrastructure. In the most
 common case, the transform IR will be processed and applied to the payload IR by
-a pass. Transformations expressed by the transform dialect may be implemented
+a pass. Transformations expressed by the Transform dialect may be implemented
 using the pattern infrastructure or any other relevant MLIR component.
 
 The following IR gives a rough idea of what the operations in this dialect
@@ -271,7 +271,7 @@ operation lists.
 
 ## Handle Invalidation
 
-The execution model of the transform dialect allows a payload IR operation to be
+The execution model of the Transform dialect allows a payload IR operation to be
 associated with _multiple_ handles as well as nested payload IR operations to be
 associated with different handles. Similarly, a payload IR value may be
 associated with multiple transform IR value handles. When a transform IR
@@ -373,13 +373,13 @@ to specify which transformations the pass should run. The transform dialect
 provides a uniform, extensible mechanism for controlling transformations in
 such cases.
 
-The transform dialect is supposed to be consumed by an "interpreter" pass
+The Transform dialect is supposed to be consumed by an "interpreter" pass
 that drives the application of transformations. To ensure extensibility and
 composability, this pass is not expected to actually perform the
 transformations specified by the ops. Instead, the transformations are
 implemented by the transform ops themselves via `TransformOpInterface`. The
 pass serves as the entry point, handles the flow of transform operations and
-takes care of bookkeeping. As such, the transform dialect does not provide
+takes care of bookkeeping. As such, the Transform dialect does not provide
 the interpreter pass. Instead, it provides a set of utilities that can be
 used by clients to define their own interpreter passes or as part of a more
 complex pass. For example, the mapping between values in the transform IR

mlir/docs/Tutorials/transform/Ch1.md

@@ -79,7 +79,7 @@ transform.sequence failures(propagate) {
 
 ## Transform Dialect Interpreter
 
-Since we don’t want to recompile the compiler every time we change a transformation, we can use a transform dialect interpreter pass to apply this transformation sequence to the payload IR. As we will see in the next chapter, it is possible to define custom passes or even integrate the transform interpreter into a larger pass. For now, we can use the existing test pass:
+Since we don’t want to recompile the compiler every time we change a transformation, we can use a Transform dialect interpreter pass to apply this transformation sequence to the payload IR. As we will see in the next chapter, it is possible to define custom passes or even integrate the transform interpreter into a larger pass. For now, we can use the existing test pass:
 
 
 ```sh
@@ -168,7 +168,7 @@ Besides producing new handles, the tiling transform operation _consumes_ the ope
 
 ## Handle Invalidation and Expensive Checks Mode
 
-Undefined behavior is difficult to grapple with when it does happen, so the transform dialect interpreter provides a set of additional expensive checks that detect most undefined behavior in the transform IR. For example, if we wanted to  use the `%arg1` handle after it is consumed, it would cause undefined behavior that manifests as an assertion in the debug build, and likely as a segmentation fault in the release mode.
+Undefined behavior is difficult to grapple with when it does happen, so the Transform dialect interpreter provides a set of additional expensive checks that detect most undefined behavior in the transform IR. For example, if we wanted to  use the `%arg1` handle after it is consumed, it would cause undefined behavior that manifests as an assertion in the debug build, and likely as a segmentation fault in the release mode.
 
 ```mlir
 transform.sequence failures(propagate) {
@@ -379,7 +379,7 @@ Finally, we would like to replace the call to the outlined function with a call
 
 ## Tracking IR Modifications
 
-The transform dialect automatically tracks all IR changes that are made as part
+The Transform dialect automatically tracks all IR changes that are made as part
 of transform ops. (Implementations must use the provided rewriter to modify IR.)
 If a payload op is erased, it is automatically removed from all handles that it
 is currently associated with. If a payload op is replaced, the transform dialect

mlir/docs/Tutorials/transform/Ch2.md

@@ -10,7 +10,7 @@ The Transform dialect uses the dialect extension mechanism to allow additional o
 // In MyExtension.cpp.
 #include "mlir/Dialect/Transform/IR/TransformDialect.h"
 
-// Define a new transform dialect extension. This uses the CRTP idiom to identify
+// Define a new Transform dialect extension. This uses the CRTP idiom to identify
 // extensions.
 class MyExtension : public ::mlir::transform::TransformDialectExtension<MyExtension> {
 public:
@@ -200,7 +200,7 @@ must be modified with the provided rewriter.
 ```c++
 // In MyExtension.cpp
 
-// Implementation of our transform dialect operation.
+// Implementation of our Transform dialect operation.
 // This operation returns a tri-state result that can be one of:
 // - success when the transformation succeeded;
 // - definite failure when the transformation failed in such a way that
@@ -277,7 +277,7 @@ void registerMyExtension(::mlir::DialectRegistry &registry) {
 }
 ```
 
-After registering the extension, it becomes possible to use our new operation in the transform dialect interpreter. The upstream testing pass can be used as is.
+After registering the extension, it becomes possible to use our new operation in the Transform dialect interpreter. The upstream testing pass can be used as is.
 
 ```mlir
 transform.sequence failures(propagate) {

mlir/docs/Tutorials/transform/Ch3.md

@@ -138,7 +138,7 @@ void MyExtension::init() {
 }
 ```
 
-This type is now directly available in the transform dialect and can be used in operations.
+This type is now directly available in the Transform dialect and can be used in operations.
 
 
 ```mlir

mlir/docs/Tutorials/transform/ChH.md

@@ -1,7 +1,7 @@
 # Chapter H: Reproducing Halide Schedule
 
 This chapter demonstrates how a schedule from the [Halide
-DSL](http://halide-lang.org) can be implemented using transform dialect for
+DSL](http://halide-lang.org) can be implemented using Transform dialect for
 structured ops.
 
 Note that the IR below is pseudo-code with types removed for brevity. It may
@@ -408,7 +408,7 @@ identical_ to the code with the full schedule. Therefore, we will only unroll
 the corresponding loops corresponding to `xi` and `ci` dimensions that actually
 get unrolled by Halide.
 
-As tiling in the transform dialect produces handles to the loops materialized by
+As tiling in the Transform dialect produces handles to the loops materialized by
 tiling, unrolling those loops is just a matter of chaining the corresponding
 transformation. Note that the inner loop must be unrolled first as unrolling the
 outer loop will invalidate the handles to the inner loop.
@@ -499,7 +499,7 @@ bufferization is directly available as a transform operation.
 
 One-shot bufferization itself does not produce buffer deallocations, which may
 lead to leaks. So we have to run the buffer deallocation pass pipeline to avoid
-them. Note that the transform dialect seamlessly runs named passes and pass
+them. Note that the Transform dialect seamlessly runs named passes and pass
 pipelines: if desired, one could replace complex `--pass-pipeline expressions`
 with operations. Note that we apply the pipeline to functions rather than entire
 module to avoid running it on the transform IR that is contained in the module.

mlir/docs/Tutorials/transform/_index.md

@@ -8,15 +8,15 @@ scheduling languages). This tutorial presents the concepts of the MLIR transform
 dialect and related infrastructure. It will be accompanied by a practical
 demonstration of three use scenarios:
 
-- Composing transform dialect operations available in (upstream) MLIR to perform
+- Composing Transform dialect operations available in (upstream) MLIR to perform
   a sequence of optimizing transformations that results in efficient code for an
   MLIR linear algebra operation.
-- Defining new transform dialect operations and adapting existing transformation
-  code to work with the transform dialect infrastructure.
-- Setting up and using the transform dialect infrastructure in a downstream
+- Defining new Transform dialect operations and adapting existing transformation
+  code to work with the Transform dialect infrastructure.
+- Setting up and using the Transform dialect infrastructure in a downstream
   out-of-tree project with custom dialects, transformations and passes.
 
-After following the tutorial, one will be able to apply the transform dialect in
+After following the tutorial, one will be able to apply the Transform dialect in
 their work and extend it when necessary. Basic familiarity with MLIR is a
 prerequisite. See [Toy tutorial](../Toy) for introduction to MLIR.