[mlir][docs] Tidy up the pass infrastructure documentation

[rriddle]

Summary

The doc has grown stale and is missing some recent changes to the infrastructure.

[mehdi_amini]

mlir/docs/PassManagement.md

43

This last point is lost?

520–521

I'd say first that "registering passes allows to parse a textual pipeline description" (and then mention that it is useful for utilities like mlir-opt)

[rriddle]

Update

[rriddle]

mlir/docs/PassManagement.md

43

I felt that this point was just a restatement of the second bullet:

Modify the state of another operation not nested within the current
    operation being operated on.

520–521

Thanks. Tried to reword a bit to put less emphasis on command line, and more on the textual format in general.

[mehdi_amini]

mlir/docs/PassManagement.md

43

I see a difference though, the point you're referring to is about *modifying* the state of another operation, but it does not say anything about *inspecting* it.

[rriddle]

mlir/docs/PassManagement.md

43

Ah yes, I glanced over the first part. Adding it back.

[rriddle]

Update

mlir/docs/PassManagement.md

 # Pass Infrastructure
 
 [TOC]
 
 Passes represent the basic infrastructure for transformation and optimization.
-This document provides a quickstart to the pass infrastructure in MLIR and how
-to use it.
+This document provides an overview of the pass infrastructure in MLIR and how to
+use it.
 
 See [MLIR specification](LangRef.md) for more information about MLIR and its
 core aspects, such as the IR structure and operations.
 
 See [MLIR Rewrites](Tutorials/QuickstartRewrites.md) for a quick start on graph
-rewriting in MLIR. If your transformation involves pattern matching operation
-DAGs, this is a great place to start.
+rewriting in MLIR. If a transformation involves pattern matching operation DAGs,
+this is a great place to start.
 
 ## Operation Pass
 
 In MLIR, the main unit of abstraction and transformation is an
 [operation](LangRef.md#operations). As such, the pass manager is designed to
 work on instances of operations at different levels of nesting. The structure of
 the [pass manager](#pass-manager), and the concept of nesting, is detailed
 further below. All passes in MLIR derive from `OperationPass` and adhere to the
 following restrictions; any noncompliance will lead to problematic behavior in
 multithreaded and other advanced scenarios:
 
-*   Modify anything within the parent block/region/operation/etc, outside of the
-    current operation being operated on. This includes adding or removing
-    operations from the parent block.
-*   Maintain pass state across invocations of `runOnOperation`. A pass may be
-    run on several different operations with no guarantee of execution order.
-    *   When multithreading, a specific pass instance may not even execute on
-        all operations within the module. As such, a pass should not rely on
-        running on all operations.
+*   Modify any state referenced or relied upon outside the current being
+    operated on. This includes adding or removing operations from the parent
+    block, changing the attributes(depending on the contract of the current
+    operation)/operands/results/successors of the current operation.
 *   Modify the state of another operation not nested within the current
     operation being operated on.
-    *   Other threads may be operating on different operations within the module
-        simultaneously.
+    *   Other threads may be operating on these operations simultaneously.
+*   Inspect the state of sibling operations.
+    *   Other threads may be modifying these operations in parallel.
+    *   Inspecting the state of ancestor/parent operations is permitted.
+*   Maintain mutable pass state across invocations of `runOnOperation`. A pass
+    may be run on many different operations with no guarantee of execution
+    order.
+    *   When multithreading, a specific pass instance may not even execute on
+        all operations within the IR. As such, a pass should not rely on running
+        on all operations.
 *   Maintain any global mutable state, e.g. static variables within the source
     file. All mutable state should be maintained by an instance of the pass.
-*   Must be copy-constructible, multiple instances of the pass may be created by
-    the pass manager to process operations in parallel.
-*   Inspect the IR of sibling operations. Other threads may be modifying these
-    operations in parallel.
+*   Must be copy-constructible
+    *   Multiple instances of the pass may be created by the pass manager to
+        process operations in parallel.
 
 When creating an operation pass, there are two different types to choose from
 depending on the usage scenario:
 
 ### OperationPass : Op-Specific
 
 An `op-specific` operation pass operates explicitly on a given operation type.
 This operation type must adhere to the restrictions set by the pass manager for
 pass execution.
 
 To define an op-specific operation pass, a derived class must adhere to the
 following:
 
 *   Inherit from the CRTP class `OperationPass` and provide the operation type
     as an additional template parameter.
 *   Override the virtual `void runOnOperation()` method.
 
 A simple pass may look like:
 
 ```c++
 namespace {
-struct MyFunctionPass : public OperationPass<MyFunctionPass, FuncOp> {
+/// Here we utilize the CRTP `PassWrapper` utility class to provide some
+/// necessary utility hooks. This is only necessary for passes defined directly
+/// in C++. Passes defined declaratively use a cleaner mechanism for providing
+/// these utilities.
+struct MyFunctionPass : public PassWrapper<OperationPass<FuncOp>,
+                                           MyFunctionPass> {
   void runOnOperation() override {
     // Get the current FuncOp operation being operated on.
     FuncOp f = getOperation();
 
     // Walk the operations within the function.
     f.walk([](Operation *inst) {
       ....
     });
   }
 };
 } // end anonymous namespace
 
-// Register this pass to make it accessible to utilities like mlir-opt.
-// (Pass registration is discussed more below)
-static PassRegistration<MyFunctionPass> pass(
+/// Register this pass so that it can be built via from a textual pass pipeline.
+/// (Pass registration is discussed more below)
+void registerMyPass() {
+  PassRegistration<MyFunctionPass>(
     "flag-name-to-invoke-pass-via-mlir-opt", "Pass description here");
+}
 ```
 
 ### OperationPass : Op-Agnostic
 
 An `op-agnostic` pass operates on the operation type of the pass manager that it
-is added to. This means that a pass that operates on several different operation
-types in the same way only needs one implementation.
+is added to. This means that passes of this type may operate on several
+different operation types. Passes of this type are generally written generically
+using operation [interfaces](Interfaces.md) and [traits](Traits.md). Examples of
+this type of pass are
+[Common Sub-Expression Elimination](Passes.md#-cse-eliminate-common-sub-expressions)
+and [Inlining](Passes.md#-inline-inline-function-calls).
 
 To create an operation pass, a derived class must adhere to the following:
 
 *   Inherit from the CRTP class `OperationPass`.
 *   Override the virtual `void runOnOperation()` method.
 
 A simple pass may look like:
 
 ```c++
-struct MyOperationPass : public OperationPass<MyOperationPass> {
+/// Here we utilize the CRTP `PassWrapper` utility class to provide some
+/// necessary utility hooks. This is only necessary for passes defined directly
+/// in C++. Passes defined declaratively use a cleaner mechanism for providing
+/// these utilities.
+struct MyOperationPass : public PassWrapper<OperationPass<>, MyOperationPass> {
   void runOnOperation() override {
     // Get the current operation being operated on.
     Operation *op = getOperation();
     ...
   }
 };
 ```
 
 ### Dependent Dialects
 
 Dialects must be loaded in the MLIRContext before entities from these dialects
-(operations, types, attributes, ...) can be created. Dialects must be loaded
-before starting the multi-threaded pass pipeline execution. To this end, a pass
-that can create an entity from a dialect that isn't already loaded must express
-this by overriding the `getDependentDialects()` method and declare this list of
-Dialects explicitly.
+(operations, types, attributes, ...) can be created. Dialects must also be
+loaded before starting the execution of a multi-threaded pass pipeline. To this
+end, a pass that may create an entity from a dialect that isn't guaranteed to
+already ne loaded must express this by overriding the `getDependentDialects()`
+method and declare this list of Dialects explicitly.
 
 ## Analysis Management
 
 An important concept, along with transformation passes, are analyses. These are
 conceptually similar to transformation passes, except that they compute
 information on a specific operation without modifying it. In MLIR, analyses are
 not passes but free-standing classes that are computed lazily on-demand and
 cached to avoid unnecessary recomputation. An analysis in MLIR must adhere to

 }
 ```
 
 ## Pass Failure
 
 Passes in MLIR are allowed to gracefully fail. This may happen if some invariant
 of the pass was broken, potentially leaving the IR in some invalid state. If
 such a situation occurs, the pass can directly signal a failure to the pass
-manager. If a pass signaled a failure when executing, no other passes in the
-pipeline will execute and the `PassManager::run` will return failure. Failure
-signaling is provided in the form of a `signalPassFailure` method.
+manager via the `signalPassFailure` method. If a pass signaled a failure when
+executing, no other passes in the pipeline will execute and the top-level call
+to `PassManager::run` will return `failure`.
 
 ```c++
-void MyPass::runOnOperation() {
+void MyOperationPass::runOnOperation() {
   // Signal failure on a broken invariant.
-  if (some_broken_invariant) {
-    signalPassFailure();
-    return;
-  }
+  if (some_broken_invariant)
+    return signalPassFailure();
 }
 ```
 
 ## Pass Manager
 
-Above we introduced the different types of passes and their constraints. Now
-that we have our pass we need to be able to run it over a specific module. This
-is where the pass manager comes into play. The `PassManager` class is used to
-configure and run a pipeline. The `OpPassManager` class is used to schedule
-passes to run at a specific level of nesting.
+The above sections introduced the different types of passes and their
+invariants. This section introduces the concept of a PassManager, and how it can
+be used to configure and schedule a pass pipeline. There are two main classes
+related to pass management, the `PassManager` and the `OpPassManager`. The
+`PassManager` class acts as the top-level entry point, and contains various
+configurations used for the entire pass pipeline. The `OpPassManager` class is
+used to schedule passes to run at a specific level of nesting. The top-level
+`PassManager` also functions as an `OpPassManager`.
 
 ### OpPassManager
 
 An `OpPassManager` is essentially a collection of passes to execute on an
-operation of a given type. This operation type must adhere to the following
+operation of a specific type. This operation type must adhere to the following
 requirement:
 
-*   Must be registered and marked `IsolatedFromAbove`.
+*   Must be registered and marked
+    [`IsolatedFromAbove`](Traits.md#isolatedfromabove).
 
     *   Passes are expected to not modify operations at or above the current
         operation being processed. If the operation is not isolated, it may
-        inadvertently modify the use-list of an operation it is not supposed to
-        modify.
+        inadvertently modify or traverse the SSA use-list of an operation it is
+        not supposed to.
 
 Passes can be added to a pass manager via `addPass`. The pass must either be an
 `op-specific` pass operating on the same operation type as `OpPassManager`, or
 an `op-agnostic` pass.
 
-An `OpPassManager` cannot be created directly, but must be explicitly nested
-within another `OpPassManager` via the `nest<>` method. This method takes the
+An `OpPassManager` is generally creted by explicitly nesting a pipeline within
+another existing `OpPassManager` via the `nest<>` method. This method takes the
 operation type that the nested pass manager will operate on. At the top-level, a
-`PassManager` acts as an `OpPassManager` that operates on the
-[`module`](LangRef.md#module) operation. Nesting in this sense, corresponds to
-the structural nesting within [Regions](LangRef.md#regions) of the IR.
+`PassManager` acts as an `OpPassManager`. Nesting in this sense, corresponds to
+the [structural](Tutorials/UnderstandingTheIRStructure.md) nesting within
+[Regions](LangRef.md#regions) of the IR.
 
 For example, the following `.mlir`:
 
 ```
 module {
   spv.module "Logical" "GLSL450" {
     func @foo() {
       ...
`module`
   `spv.module`
     `function`
 ```
 
 Below is an example of constructing a pipeline that operates on the above
 structure:
 
 ```c++
+// Create a top-level `PassManager` class. If an operation type is not
+// explicitly specific, the default is the builtin `module` operation.
 PassManager pm(ctx);
+// Note: We could also create the above `PassManager` this way.
+PassManager pm(ctx, /*operationName=*/"module");
 
 // Add a pass on the top-level module operation.
 pm.addPass(std::make_unique<MyModulePass>());
 
-// Nest a pass manager that operates on spirv module operations nested directly
-// under the top-level module.
+// Nest a pass manager that operates on `spirv.module` operations nested
+// directly under the top-level module.
 OpPassManager &nestedModulePM = pm.nest<spirv::ModuleOp>();
 nestedModulePM.addPass(std::make_unique<MySPIRVModulePass>());
 
 // Nest a pass manager that operates on functions within the nested SPIRV
 // module.
 OpPassManager &nestedFunctionPM = nestedModulePM.nest<FuncOp>();
 nestedFunctionPM.addPass(std::make_unique<MyFunctionPass>());
 
 // Run the pass manager on the top-level module.
-Module m = ...;
+ModuleOp m = ...;
 if (failed(pm.run(m)))
     ... // One of the passes signaled a failure.
 ```
 
-The above pass manager would contain the following pipeline structure:
+The above pass manager contains the following pipeline structure:
 
 ```
 OpPassManager<ModuleOp>
   MyModulePass
   OpPassManager<spirv::ModuleOp>
     MySPIRVModulePass
     OpPassManager<FuncOp>
       MyFunctionPass
 ```
 
 These pipelines are then run over a single operation at a time. This means that,
 for example, given a series of consecutive passes on FuncOp, it will execute all
 on the first function, then all on the second function, etc. until the entire
 program has been run through the passes. This provides several benefits:
 
 *   This improves the cache behavior of the compiler, because it is only
     touching a single function at a time, instead of traversing the entire
     program.
 *   This improves multi-threading performance by reducing the number of jobs
     that need to be scheduled, as well as increasing the efficiency of each job.
     An entire function pipeline can be run on each function asynchronously.
 
-## Pass Registration
-
-Briefly shown in the example definitions of the various pass types is the
-`PassRegistration` class. This is a utility to register derived pass classes so
-that they may be created, and inspected, by utilities like mlir-opt. Registering
-a pass class takes the form:
-
-```c++
-static PassRegistration<MyPass> pass("command-line-arg", "description");
-```
-
-*   `MyPass` is the name of the derived pass class.
-*   "command-line-arg" is the argument to use on the command line to invoke the
-    pass from `mlir-opt`.
-*   "description" is a description of the pass.
-
-For passes that cannot be default-constructed, `PassRegistration` accepts an
-optional third argument that takes a callback to create the pass:
-
-```c++
-static PassRegistration<MyParametricPass> pass(
-    "command-line-arg", "description",
-    []() -> std::unique_ptr<Pass> {
-      std::unique_ptr<Pass> p = std::make_unique<MyParametricPass>(/*options*/);
-      /*... non-trivial-logic to configure the pass ...*/;
-      return p;
-    });
-```
-
-This variant of registration can be used, for example, to accept the
-configuration of a pass from command-line arguments and pass it over to the pass
-constructor. Make sure that the pass is copy-constructible in a way that does
-not share data as the [pass manager](#pass-manager) may create copies of the
-pass to run in parallel.
+## Dynamic Pass Pipelines
 
-### Pass Pipeline Registration
-
-Described above is the mechanism used for registering a specific derived pass
-class. On top of that, MLIR allows for registering custom pass pipelines in a
-similar fashion. This allows for custom pipelines to be available to tools like
-mlir-opt in the same way that passes are, which is useful for encapsulating
-common pipelines like the "-O1" series of passes. Pipelines are registered via a
-similar mechanism to passes in the form of `PassPipelineRegistration`. Compared
-to `PassRegistration`, this class takes an additional parameter in the form of a
-pipeline builder that modifies a provided `OpPassManager`.
+In some situations it may be useful to run a pass pipeline within another pass,
+to allow configuring or filtering based on some invariants of the current
+operation being operated on. For example, the
+[Inliner Pass](Passes.md#-inline-inline-function-calls) may want to run
+intraprocedural simplification passes while it is inlining to produce a better
+cost model, and provide more optimal inlining. To enable this, passes may run an
+arbitrary `OpPassManager` on the current operation being operated on or any
+operation nested within the current operation via the `LogicalResult
+Pass::runPipeline(OpPassManager &, Operation *)` method. This method returns
+whether the dynamic pipeline succeeded or failed, similarly to the result of the
+top-level `PassManager::run` method. A simple example is shown below:
 
 ```c++
-void pipelineBuilder(OpPassManager &pm) {
-  pm.addPass(std::make_unique<MyPass>());
-  pm.addPass(std::make_unique<MyOtherPass>());
+void MyModulePass::runOnOperation() {
+  ModuleOp module = getOperation();
+  if (hasSomeSpecificProperty(module)) {
+    OpPassManager dynamicPM("module");
+    ...; // Build the dynamic pipeline.
+    if (failed(runPipeline(dynamicPM, module)))
+      return signalPassFailure();
+  }
 }
-
-// Register an existing pipeline builder function.
-static PassPipelineRegistration<> pipeline(
-  "command-line-arg", "description", pipelineBuilder);
-
-// Register an inline pipeline builder.
-static PassPipelineRegistration<> pipeline(
-  "command-line-arg", "description", [](OpPassManager &pm) {
-    pm.addPass(std::make_unique<MyPass>());
-    pm.addPass(std::make_unique<MyOtherPass>());
-  });
-```
-
-Pipeline registration also allows for simplified registration of
-specializations for existing passes:
-
-```c++
-static PassPipelineRegistration<> foo10(
-    "foo-10", "Foo Pass 10", [] { return std::make_unique<FooPass>(10); } );
-```
-
-### Textual Pass Pipeline Specification
-
-In the previous sections, we showed how to register passes and pass pipelines
-with a specific argument and description. Once registered, these can be used on
-the command line to configure a pass manager. The limitation of using these
-arguments directly is that they cannot build a nested pipeline. For example, if
-our module has another module nested underneath, with just `-my-module-pass`
-there is no way to specify that this pass should run on the nested module and
-not the top-level module. This is due to the flattened nature of the command
-line.
-
-To circumvent this limitation, MLIR also supports a textual description of a
-pass pipeline. This allows for explicitly specifying the structure of the
-pipeline to add to the pass manager. This includes the nesting structure, as
-well as the passes and pass pipelines to run. A textual pipeline is defined as a
-series of names, each of which may in itself recursively contain a nested
-pipeline description. The syntax for this specification is as follows:
-
-```ebnf
-pipeline          ::= op-name `(` pipeline-element (`,` pipeline-element)* `)`
-pipeline-element  ::= pipeline | (pass-name | pass-pipeline-name) options?
-options           ::= '{' (key ('=' value)?)+ '}'
-```
-
-*   `op-name`
-    *   This corresponds to the mnemonic name of an operation to run passes on,
-        e.g. `func` or `module`.
-*   `pass-name` | `pass-pipeline-name`
-    *   This corresponds to the command-line argument of a registered pass or
-        pass pipeline, e.g. `cse` or `canonicalize`.
-*   `options`
-    *   Options are pass specific key value pairs that are handled as described
-        in the [instance specific pass options](#instance-specific-pass-options)
-        section.
-
-For example, the following pipeline:
-
-```shell
-$ mlir-opt foo.mlir -cse -canonicalize -convert-std-to-llvm
-```
-
-Can also be specified as (via the `-pass-pipeline` flag):
-
-```shell
-$ mlir-opt foo.mlir -pass-pipeline='func(cse, canonicalize), convert-std-to-llvm'
 ```
 
-In order to support round-tripping your pass to the textual representation using
-`OpPassManager::printAsTextualPipeline(raw_ostream&)`, override
-`Pass::printAsTextualPipeline(raw_ostream&)` to format your pass-name and
-options in the format described above.
-
-### Instance Specific Pass Options
-
-Options may be specified for a parametric pass. Individual options are defined
-using the [LLVM command line](https://llvm.org/docs/CommandLine.html) flag
-definition rules. These options will then be parsed at pass construction time
-independently for each instance of the pass. To provide options for passes, the
-`Option<>` and `OptionList<>` classes may be used:
+Note: though above the dynamic pipeline was constructed within the
+`runOnOperation` method, this is not necessary and pipelines should be cached
+when possible as the `OpPassManager` class can be safely copy constructed.
+
+The mechanism described in this section should be used whenever a pass pipeline
+should run in a nested fashion, i.e. when the nested pipeline cannot be
+scheduled statically along with the rest of the main pass pipeline. More
+specifically, a `PassManager` should generally never need to be constructed
+within a `Pass`. Using `runPipeline` also ensures that all analyses,
+[instrumentations](#pass-instrumentation), and other pass manager related
+components are integrated with the dynamic pipeline being executed.
+
+## Instance Specific Pass Options
+
+MLIR provides a builtin mechanism for passes to specify options that configure
+its behavior. These options are parsed at pass construction time independently
+for each instance of the pass. Options are defined using the `Option<>` and
+`ListOption<>` classes, and follow the
+[LLVM command line](https://llvm.org/docs/CommandLine.html) flag definition
+rules. See below for a few examples:
 
 ```c++
 struct MyPass ... {
   /// Make sure that we have a valid default constructor and copy constructor to
-  /// make sure that the options are initialized properly.
+  /// ensure that the options are initialized properly.
   MyPass() = default;
   MyPass(const MyPass& pass) {}
 
-  // These just forward onto llvm::cl::list and llvm::cl::opt respectively.
+  /// Any parameters after the description are forwarded to llvm::cl::list and
+  /// llvm::cl::opt respectively.
   Option<int> exampleOption{*this, "flag-name", llvm::cl::desc("...")};
   ListOption<int> exampleListOption{*this, "list-flag-name",
                                     llvm::cl::desc("...")};
 };
 ```
 
 For pass pipelines, the `PassPipelineRegistration` templates take an additional
-optional template parameter that is the Option struct definition to be used for
-that pipeline. To use pipeline specific options, create a class that inherits
-from `mlir::PassPipelineOptions` that contains the desired options. When using
-`PassPipelineRegistration`, the constructor now takes a function with the
-signature `void (OpPassManager &pm, const MyPipelineOptions&)` which should
-construct the passes from the options and pass them to the pm:
+template parameter for an optional `Option` struct definition. This struct
+should inherit from `mlir::PassPipelineOptions` and contain the desired pipeline
+options. When using `PassPipelineRegistration`, the constructor now takes a
+function with the signature `void (OpPassManager &pm, const MyPipelineOptions&)`
+which should construct the passes from the options and pass them to the pm:
 
 ```c++
 struct MyPipelineOptions : public PassPipelineOptions {
-  // These just forward onto llvm::cl::list and llvm::cl::opt respectively.
+  // The structure of these options is the same as those for pass options.
   Option<int> exampleOption{*this, "flag-name", llvm::cl::desc("...")};
   ListOption<int> exampleListOption{*this, "list-flag-name",
                                     llvm::cl::desc("...")};
 };
 
-
-static mlir::PassPipelineRegistration<MyPipelineOptions> pipeline(
+void registerMyPasses() {
+  PassPipelineRegistration<MyPipelineOptions>(
     "example-pipeline", "Run an example pipeline.",
     [](OpPassManager &pm, const MyPipelineOptions &pipelineOptions) {
       // Initialize the pass manager.
     });
+}
 ```
 
 ## Pass Statistics
 
 Statistics are a way to keep track of what the compiler is doing and how
 effective various transformations are. It is often useful to see what effect
-specific transformations have on a particular program, and how often they
-trigger. Pass statistics are instance specific which allow for taking this a
-step further as you are able to see the effect of placing a particular
-transformation at specific places within the pass pipeline. For example, they
-help answer questions like `What happens if I run CSE again here?`.
+specific transformations have on a particular input, and how often they trigger.
+Pass statistics are specific to each pass instance, which allow for seeing the
+effect of placing a particular transformation at specific places within the pass
+pipeline. For example, they help answer questions like "What happens if I run
+CSE again here?".
 
 Statistics can be added to a pass by using the 'Pass::Statistic' class. This
 class takes as a constructor arguments: the parent pass, a name, and a
-description. This class acts like an unsigned integer, and may be incremented
-and updated accordingly. These statistics use the same infrastructure as
+description. This class acts like an atomic unsigned integer, and may be
+incremented and updated accordingly. These statistics rely on the same
+infrastructure as
 [`llvm::Statistic`](http://llvm.org/docs/ProgrammersManual.html#the-statistic-class-stats-option)
 and thus have similar usage constraints. Collected statistics can be dumped by
 the [pass manager](#pass-manager) programmatically via
 `PassManager::enableStatistics`; or via `-pass-statistics` and
 `-pass-statistics-display` on the command line.
 
 An example is shown below:
 
 ```c++
-struct MyPass : public OperationPass<MyPass> {
-  Statistic testStat{this, "testStat", "A test statistic"};
+struct MyPass ... {
+  /// Make sure that we have a valid default constructor and copy constructor to
+  /// ensure that the options are initialized properly.
+  MyPass() = default;
+  MyPass(const MyPass& pass) {}
+
+  /// Define the statistic to track during the execution of MyPass.
+  Statistic exampleStat{this, "exampleStat", "An example statistic"};
 
   void runOnOperation() {
     ...
 
-    // Update our statistic after some invariant was hit.
-    ++testStat;
+    // Update the statistic after some invariant was hit.
+    ++exampleStat;
 
     ...
   }
 };
 ```
 
 The collected statistics may be aggregated in two types of views:
 
 A pipeline view that models the structure of the pass manager, this is the
 default view:
 
 ```shell
 $ mlir-opt -pass-pipeline='func(my-pass,my-pass)' foo.mlir -pass-statistics
 
 ===-------------------------------------------------------------------------===
                          ... Pass statistics report ...
 ===-------------------------------------------------------------------------===
 'func' Pipeline
   MyPass
-    (S) 15 testStat - A test statistic
+    (S) 15 exampleStat - An example statistic
   VerifierPass
   MyPass
-    (S)  6 testStat - A test statistic
+    (S)  6 exampleStat - An example statistic
   VerifierPass
 VerifierPass
 ```
 
-And a list view that aggregates all instances of a specific pass together:
+A list view that aggregates the statistics of all instances of a specific pass
+together:
 
 ```shell
 $ mlir-opt -pass-pipeline='func(my-pass, my-pass)' foo.mlir -pass-statistics -pass-statistics-display=list
 
 ===-------------------------------------------------------------------------===
                          ... Pass statistics report ...
 ===-------------------------------------------------------------------------===
 MyPass
-  (S) 21 testStat - A test statistic
+  (S) 21 exampleStat - An example statistic
+```
+
+## Pass Registration
+
+Briefly shown in the example definitions of the various pass types is the
+`PassRegistration` class. This mechanism allows for registering pass classes so
+that they may be created within a
+[textual pass pipeline description](#textual-pass-pipeline-specification). An
+example registration is shown below:
+
+```c++
+void registerMyPass() {
+  PassRegistration<MyPass>("argument", "description");
+}
+```
+
+*   `MyPass` is the name of the derived pass class.
+*   "argument" is the argument used to refer to the pass in the textual format.
+*   "description" is a brief description of the pass.
+
+For passes that cannot be default-constructed, `PassRegistration` accepts an
+optional third argument that takes a callback to create the pass:
+
+```c++
+void registerMyPass() {
+  PassRegistration<MyParametricPass>(
+    "argument", "description",
+    []() -> std::unique_ptr<Pass> {
+      std::unique_ptr<Pass> p = std::make_unique<MyParametricPass>(/*options*/);
+      /*... non-trivial-logic to configure the pass ...*/;
+      return p;
+    });
+}
+```
+
+This variant of registration can be used, for example, to accept the
+configuration of a pass from command-line arguments and pass it to the pass
+constructor.
+
+Note: Make sure that the pass is copy-constructible in a way that does not share
+data as the [pass manager](#pass-manager) may create copies of the pass to run
+in parallel.
+
+### Pass Pipeline Registration
+
+Described above is the mechanism used for registering a specific derived pass
+class. On top of that, MLIR allows for registering custom pass pipelines in a
+similar fashion. This allows for custom pipelines to be available to tools like
+mlir-opt in the same way that passes are, which is useful for encapsulating
+common pipelines like the "-O1" series of passes. Pipelines are registered via a
+similar mechanism to passes in the form of `PassPipelineRegistration`. Compared
+to `PassRegistration`, this class takes an additional parameter in the form of a
+pipeline builder that modifies a provided `OpPassManager`.
+
+```c++
+void pipelineBuilder(OpPassManager &pm) {
+  pm.addPass(std::make_unique<MyPass>());
+  pm.addPass(std::make_unique<MyOtherPass>());
+}
+
+void registerMyPasses() {
+  // Register an existing pipeline builder function.
+  PassPipelineRegistration<>(
+    "argument", "description", pipelineBuilder);
+
+  // Register an inline pipeline builder.
+  PassPipelineRegistration<>(
+    "argument", "description", [](OpPassManager &pm) {
+      pm.addPass(std::make_unique<MyPass>());
+      pm.addPass(std::make_unique<MyOtherPass>());
+    });
+}
+```
+
+### Textual Pass Pipeline Specification
+
+The previous sections detailed how to register passes and pass pipelines with a
+specific argument and description. Once registered, these can be used to
+configure a pass manager from a string description. This is especially useful
+for tools like `mlir-opt`, that configure pass managers from the command line,
+or as options to passes that utilize
+[dynamic pass pipelines](#dynamic-pass-pipelines).
+
+To support the ability to describe the full structure of pass pipelines, MLIR
+supports a custom textual description of pass pipelines. The textual description
+includes the nesting structure, the arguments of the passes and pass pipelines
+to run, and any options for those passes and pipelines. A textual pipeline is
+defined as a series of names, each of which may in itself recursively contain a
+nested pipeline description. The syntax for this specification is as follows:
+
+```ebnf
+pipeline          ::= op-name `(` pipeline-element (`,` pipeline-element)* `)`
+pipeline-element  ::= pipeline | (pass-name | pass-pipeline-name) options?
+options           ::= '{' (key ('=' value)?)+ '}'
 ```
 
+*   `op-name`
+    *   This corresponds to the mnemonic name of an operation to run passes on,
+        e.g. `func` or `module`.
+*   `pass-name` | `pass-pipeline-name`
+    *   This corresponds to the argument of a registered pass or pass pipeline,
+        e.g. `cse` or `canonicalize`.
+*   `options`
+    *   Options are specific key value pairs representing options defined by a
+        pass or pass pipeline, as described in the
+        ["Instance Specific Pass Options"](#instance-specific-pass-options)
+        section. See this section for an example usage in a textual pipeline.
+
+For example, the following pipeline:
+
+```shell
+$ mlir-opt foo.mlir -cse -canonicalize -convert-std-to-llvm='use-bare-ptr-memref-call-conv=1'
+```
+
+Can also be specified as (via the `-pass-pipeline` flag):
+
+```shell
+$ mlir-opt foo.mlir -pass-pipeline='func(cse,canonicalize),convert-std-to-llvm{use-bare-ptr-memref-call-conv=1}'
+```
+
+In order to support round-tripping a pass to the textual representation using
+`OpPassManager::printAsTextualPipeline(raw_ostream&)`, override `StringRef
+Pass::getArgument()` to specify the argument used when registering a pass.
+
 ## Declarative Pass Specification
 
 Some aspects of a Pass may be specified declaratively, in a form similar to
-[operations](OpDefinitions.md). This specification simplifies several
-mechanisms used when defining passes. It can be used for generating pass
-registration calls, defining boilerplate pass utilities, and generating pass
-documentation.
+[operations](OpDefinitions.md). This specification simplifies several mechanisms
+used when defining passes. It can be used for generating pass registration
+calls, defining boilerplate pass utilities, and generating pass documentation.
 
 Consider the following pass specified in C++:
 
 ```c++
 struct MyPass : PassWrapper<MyPass, OperationPass<ModuleOp>> {
+  MyPass() = default;
+  MyPass(const MyPass &) {}
+
   ...
 
-  /// Options.
+  // Specify any options.
   Option<bool> option{
       *this, "example-option",
       llvm::cl::desc("An example option"), llvm::cl::init(true)};
   ListOption<int64_t> listOption{
       *this, "example-list",
       llvm::cl::desc("An example list option"), llvm::cl::ZeroOrMore,
       llvm::cl::MiscFlags::CommaSeparated};
 
-  /// Statistics.
+  // Specify any statistics.
   Statistic statistic{this, "example-statistic", "An example statistic"};
 };
 
 /// Expose this pass to the outside world.
 std::unique_ptr<Pass> foo::createMyPass() {
   return std::make_unique<MyPass>();
 }
 
-static PassRegistration<MyPass> pass("my-pass", "My pass summary");
+/// Register this pass.
+void foo::registerMyPass() {
+  PassRegistration<MyPass>("my-pass", "My pass summary");
+}
 ```
 
 This pass may be specified declaratively as so:
 
 ```tablegen
 def MyPass : Pass<"my-pass", "ModuleOp"> {
   let summary = "My Pass Summary";
   let description = [{
def MyPass : Pass<"my-pass", "ModuleOp"> {
 
   // Specify any statistics.
   let statistics = [
     Statistic<"statistic", "example-statistic", "An example statistic">
   ];
 }
 ```
 
-Using the `gen-pass-decls` generator, we can generate the much of the
-boilerplater above automatically. This generator takes as an input a `-name`
-parameter, that provides a tag for the group of passes that are being generated.
-This generator produces two chunks of output:
+Using the `gen-pass-decls` generator, we can generate most of the boilerplate
+above automatically. This generator takes as an input a `-name` parameter, that
+provides a tag for the group of passes that are being generated. This generator
+produces two chunks of output:
 
-The first is the code for registering the declarative passes with the global
+The first is a code block for registering the declarative passes with the global
 registry. For each pass, the generator produces a `registerFooPass` where `Foo`
 is the name of the definition specified in tablegen. It also generates a
 `registerGroupPasses`, where `Group` is the tag provided via the `-name` input
 parameter, that registers all of the passes present.
 
 ```c++
+// gen-pass-decls -name="Example"
+
 #define GEN_PASS_REGISTRATION
 #include "Passes.h.inc"
 
 void registerMyPasses() {
-  // Register all of our passes.
-  registerMyPasses();
+  // Register all of the passes.
+  registerExamplePasses();
 
   // Register `MyPass` specifically.
   registerMyPassPass();
 }
 ```
 
-The second is a base class for each of the passes, with each containing most of
-the boiler plate related to pass definition. These classes are named in the form
-of `MyPassBase`, where `MyPass` is the name of the definition in tablegen. We
+The second is a base class for each of the passes, containing most of the boiler
+plate related to pass definitions. These classes are named in the form of
+`MyPassBase`, where `MyPass` is the name of the pass definition in tablegen. We
 can update the original C++ pass definition as so:
 
 ```c++
 /// Include the generated base pass class definitions.
 #define GEN_PASS_CLASSES
 #include "Passes.h.inc"
 
-// Define the main class as deriving from the generated base class.
+/// Define the main class as deriving from the generated base class.
 struct MyPass : MyPassBase<MyPass> {
+  /// The explicit constructor is no longer explicitly necessary when defining
+  /// pass options and statistics, the base class takes care of that
+  /// automatically.
   ...
+
+  /// The definitions of the options and statistics are now generated within
+  /// the base class, but are accessible in the same way.
 };
 
 /// Expose this pass to the outside world.
 std::unique_ptr<Pass> foo::createMyPass() {
   return std::make_unique<MyPass>();
 }
 ```
 
-Using the `gen-pass-doc` generator, we can generate markdown documentation for
-each of our passes. See [Passes.md](Passes.md) for example output of real MLIR
-passes.
+Using the `gen-pass-doc` generator, markdown documentation for each of the
+passes can be generated. See [Passes.md](Passes.md) for example output of real
+MLIR passes.
 
 ### Tablegen Specification
 
 The `Pass` class is used to begin a new pass definition. This class takes as an
-argument the command line argument to attribute to the pass, as well as an
-optional string corresponding to the operation type that the pass operates on.
-It contains the following fields:
+argument the registry argument to attribute to the pass, as well as an optional
+string corresponding to the operation type that the pass operates on. The class
+contains the following fields:
 
-*   summary
+*   `summary`
     -   A short one line summary of the pass, used as the description when
         registering the pass.
-*   description
+*   `description`
     -   A longer, more detailed description of the pass. This is used when
         generating pass documentation.
-*   dependentDialects
-    -   A list of strings that are the Dialect classes this pass can introduce.
-*   constructor
-    -   A piece of C++ code used to create a default instance of the pass.
-*   options
+*   `dependentDialects`
+    -   A list of strings representing the `Dialect` classes this pass may
+        introduce entities, Attributes/Operations/Types/etc., of.
+*   `constructor`
+    -   A code block used to create a default instance of the pass.
+*   `options`
     -   A list of pass options used by the pass.
-*   statistics
+*   `statistics`
     -   A list of pass statistics used by the pass.
 
 #### Options
 
-Options can be specified by the `Option` and `ListOption` classes. The `Option`
-class takes the following fields:
+Options may be specified via the `Option` and `ListOption` classes. The `Option`
+class takes the following template parameters:
 
 *   C++ variable name
     -   A name to use for the generated option variable.
 *   argument
-    -   The command line argument of the option.
+    -   The argument name of the option.
 *   type
     -   The C++ type of the option.
 *   default value
     -   The default option value.
 *   description
     -   A one line description of the option.
 *   additional option flags
     -   A string containing any additional options necessary to construct the
         option.
 
+```tablegen
+def MyPass : Pass<"my-pass"> {
+  let options = [
+    Option<"option", "example-option", "bool", /*default=*/"true",
+           "An example option">,
+  ];
+}
+```
+
 The `ListOption` class takes the following fields:
 
 *   C++ variable name
     -   A name to use for the generated option variable.
 *   argument
-    -   The command line argument of the option.
+    -   The argument name of the option.
 *   element type
     -   The C++ type of the list element.
 *   description
     -   A one line description of the option.
 *   additional option flags
     -   A string containing any additional options necessary to construct the
         option.
 
+```tablegen
+def MyPass : Pass<"my-pass"> {
+  let options = [
+    ListOption<"listOption", "example-list", "int64_t",
+               "An example list option",
+               "llvm::cl::ZeroOrMore, llvm::cl::MiscFlags::CommaSeparated">
+  ];
+}
+```
+
 #### Statistic
 
-Statistics can be specified via the `Statistic`, which takes the following
-fields:
+Statistics may be specified via the `Statistic`, which takes the following
+template parameters:
 
 *   C++ variable name
     -   A name to use for the generated statistic variable.
 *   display name
     -   The name used when displaying the statistic.
 *   description
     -   A one line description of the statistic.
 
+```tablegen
+def MyPass : Pass<"my-pass"> {
+  let statistics = [
+    Statistic<"statistic", "example-statistic", "An example statistic">
+  ];
+}
+```
+
 ## Pass Instrumentation
 
 MLIR provides a customizable framework to instrument pass execution and analysis
-computation. This is provided via the `PassInstrumentation` class. This class
-provides hooks into the PassManager that observe various pass events:
+computation, via the `PassInstrumentation` class. This class provides hooks into
+the PassManager that observe various events:
 
 *   `runBeforePipeline`
     *   This callback is run just before a pass pipeline, i.e. pass manager, is
         executed.
 *   `runAfterPipeline`
     *   This callback is run right after a pass pipeline has been executed,
         successfully or not.
 *   `runBeforePass`
     *   This callback is run just before a pass is executed.
 *   `runAfterPass`
     *   This callback is run right after a pass has been successfully executed.
-        If this hook is executed, runAfterPassFailed will not be.
+        If this hook is executed, `runAfterPassFailed` will *not* be.
 *   `runAfterPassFailed`
     *   This callback is run right after a pass execution fails. If this hook is
-        executed, runAfterPass will not be.
+        executed, `runAfterPass` will *not* be.
 *   `runBeforeAnalysis`
     *   This callback is run just before an analysis is computed.
 *   `runAfterAnalysis`
     *   This callback is run right after an analysis is computed.
 
-PassInstrumentation objects can be registered directly with a
+PassInstrumentation instances may be registered directly with a
 [PassManager](#pass-manager) instance via the `addInstrumentation` method.
 Instrumentations added to the PassManager are run in a stack like fashion, i.e.
 the last instrumentation to execute a `runBefore*` hook will be the first to
-execute the respective `runAfter*` hook. Below in an example instrumentation
-that counts the number of times DominanceInfo is computed:
+execute the respective `runAfter*` hook. The hooks of a `PassInstrumentation`
+class are guaranteed to be executed in a thread safe fashion, so additional
+synchronization is not necessary. Below in an example instrumentation that
+counts the number of times the `DominanceInfo` analysis is computed:
 
 ```c++
 struct DominanceCounterInstrumentation : public PassInstrumentation {
+  /// The cumulative count of how many times dominance has been calculated.
   unsigned &count;
 
   DominanceCounterInstrumentation(unsigned &count) : count(count) {}
   void runAfterAnalysis(llvm::StringRef, TypeID id, Operation *) override {
     if (id == TypeID::get<DominanceInfo>())
       ++count;
   }
 };
if (failed(pm.run(m)))
     ...
 
 llvm::errs() << "DominanceInfo was computed " << domInfoCount << " times!\n";
 ```
 
 ### Standard Instrumentations
 
 MLIR utilizes the pass instrumentation framework to provide a few useful
-developer tools and utilities. Each of these instrumentations are immediately
+developer tools and utilities. Each of these instrumentations are directly
 available to all users of the MLIR pass framework.
 
 #### Pass Timing
 
 The PassTiming instrumentation provides timing information about the execution
 of passes and computation of analyses. This provides a quick glimpse into what
-passes are taking the most time to execute, as well as how much of an effect
-your pass has on the total execution time of the pipeline. Users can enable this
+passes are taking the most time to execute, as well as how much of an effect a
+pass has on the total execution time of the pipeline. Users can enable this
 instrumentation directly on the PassManager via `enableTiming`. This
 instrumentation is also made available in mlir-opt via the `-pass-timing` flag.
 The PassTiming instrumentation provides several different display modes for the
 timing results, each of which is described below:
 
 ##### List Display Mode
 
 In this mode, the results are displayed in a list sorted by total time with each

 `PassManager::enableCrashReproducerGeneration` or via the command line flag
 `pass-pipeline-crash-reproducer`. In either case, an argument is provided that
 corresponds to the output `.mlir` file name that the reproducible should be
 written to. The reproducible contains the configuration of the pass manager that
 was executing, as well as the initial IR before any passes were run. A potential
 reproducible may have the form:
 
 ```mlir
-// configuration: -pass-pipeline='func(cse, canonicalize), inline'
+// configuration: -pass-pipeline='func(cse,canonicalize),inline'
 // note: verifyPasses=false
 
 module {
   func @foo() {
     ...
   }
 }
 ```