path: root/mlir/docs/Remarks.md

# Remark Infrastructure

Remarks are **structured, human- and machine-readable notes** emitted by the
compiler to explain:

- What was transformed
- What was missed
- Why it happened

The **`RemarkEngine`** collects finalized remarks during compilation and sends
them to a pluggable **streamer**. By default, MLIR integrates with LLVM’s
[`llvm::remarks`](https://llvm.org/docs/Remarks.html), allowing you to:

- Stream remarks as passes run
- Serialize them to **YAML** or **LLVM bitstream** for tooling

***

## Key Points

- **Opt-in** – Disabled by default; zero overhead unless enabled.
- **Per-context** – Configured on `MLIRContext`.
- **Formats** – LLVM Remark engine (YAML / Bitstream) or custom streamers.
- **Kinds** – `Passed`, `Missed`, `Failure`, `Analysis`.
- **API** – Lightweight streaming interface using `<<` (like MLIR diagnostics).

***

## How It Works

Two main components:

- **`RemarkEngine`** (owned by `MLIRContext`): Receives finalized
  `InFlightRemark`s, optionally mirrors them to the `DiagnosticEngine`, and
  dispatches to the installed streamer.

- **`MLIRRemarkStreamerBase`** (abstract): Backend interface with a single hook:

  ```c++
  virtual void streamOptimizationRemark(const Remark &remark) = 0;
  ```

**Default backend – `MLIRLLVMRemarkStreamer`** Adapts `mlir::Remark` to LLVM’s
remark format and writes YAML/bitstream via `llvm::remarks::RemarkStreamer`.

**Ownership flow:** `MLIRContext` → `RemarkEngine` → `MLIRRemarkStreamerBase`

***

## Categories

MLIR provides four built-in remark categories (extendable if needed):

#### 1. **Passed**

Optimization/transformation succeeded.

```
[Passed] RemarkName | Category:Vectorizer:myPass1 | Function=foo | Remark="vectorized loop", tripCount=128
```

#### 2. **Missed**

Optimization/transformation didn’t apply — ideally with actionable feedback.

```
[Missed]  | Category:Unroll | Function=foo | Reason="tripCount=4 < threshold=256", Suggestion="increase unroll to 128"
```

#### 3. **Failure**

Optimization/transformation attempted but failed. This is slightly different
from the `Missed` category.

For example, the user specifies `-use-max-register=100` when invoking the
compiler, but the attempt fails for some reason:

```bash
$ your-compiler -use-max-register=100 mycode.xyz
```

```
[Failed] Category:RegisterAllocator | Reason="Limiting to use-max-register=100 failed; it now uses 104 registers for better performance"
```

#### 4. **Analysis**

Neutral analysis results.

```
[Analysis] Category:Register | Remark="Kernel uses 168 registers"
[Analysis] Category:Register | Remark="Kernel uses 10kB local memory"
```

***

## Emitting Remarks

The `remark::*` helpers return an **in-flight remark**.
You append strings or key–value metrics using `<<`.

### Remark Options

When constructing a remark, you typically provide four fields that are `StringRef`:

1. **Remark name** – identifiable name
2. **Category** – high-level classification
3. **Sub-category** – more fine-grained classification
4. **Function name** – the function where the remark originates


### Example

```c++
#include "mlir/IR/Remarks.h"

LogicalResult MyPass::runOnOperation() {
  Location loc = getOperation()->getLoc();

  remark::RemarkOpts opts = remark::RemarkOpts::name(MyRemarkName1)
                                .category(categoryVectorizer)
                                .function(fName)
                                .subCategory(myPassname1);

  // PASSED
  remark::passed(loc, opts)
      << "vectorized loop"
      << remark::metric("tripCount", 128);

  // ANALYSIS
  remark::analysis(loc, opts)
      << "Kernel uses 168 registers";

  // MISSED (with reason + suggestion)
  int tripBad = 4, threshold = 256, target = 128;
  remark::missed(loc, opts)
      << remark::reason("tripCount={0} < threshold={1}", tripBad, threshold)
      << remark::suggest("increase unroll to {0}", target);

  // FAILURE
  remark::failed(loc, opts)
      << remark::reason("failed due to unsupported pattern");

  return success();
}
```

***

### Metrics and Shortcuts

Helper functions accept
[LLVM format](https://llvm.org/docs/ProgrammersManual.html#formatting-strings-the-formatv-function)
style strings. This format builds lazily, so remarks are zero-cost when
disabled.

#### Adding Remarks

- **`remark::add(fmt, ...)`** – Shortcut for `metric("Remark", ...)`.

#### Adding Reasons

- **`remark::reason(fmt, ...)`** – Shortcut for `metric("Reason", ...)`. Used to
  explain why a remark was missed or failed.

#### Adding Suggestions

- **`remark::suggest(fmt, ...)`** – Shortcut for `metric("Suggestion", ...)`.
  Used to provide actionable feedback.

#### Adding Custom Metrics

- **`remark::metric(key, value)`** – Adds a structured key–value metric.

Example: tracking `TripCount`. When exported to YAML, it appears under `args`
for machine readability:

```cpp
remark::metric("TripCount", value)
```

#### String Metrics

Passing a plain string (e.g. `<< "vectorized loop"`) is equivalent to:

```cpp
metric("Remark", "vectorized loop")
```

***

## Enabling Remarks

### 1. **With LLVMRemarkStreamer (YAML or Bitstream)**

Persists remarks to a file in the chosen format.

```c++
mlir::remark::RemarkCategories cats{/*passed=*/categoryLoopunroll,
                                     /*missed=*/std::nullopt,
                                     /*analysis=*/std::nullopt,
                                     /*failed=*/categoryLoopunroll};

mlir::remark::enableOptimizationRemarksWithLLVMStreamer(
    context, yamlFile, llvm::remarks::Format::YAML, cats);
```

**YAML format** – human-readable, easy to diff:

```yaml
--- !Passed
pass:            Category:SubCategory
name:            MyRemarkName1
function:        myFunc
loc:             myfile.mlir:12:3
args:
  - Remark:          vectorized loop
  - tripCount:       128
```

**Bitstream format** – compact binary for large runs.

***

### 2. **With `mlir::emitRemarks` (No Streamer)**

If the streamer isn't passed, the remarks are mirrored to the `DiagnosticEngine`
using `mlir::emitRemarks`

```c++
mlir::remark::RemarkCategories cats{/*passed=*/categoryLoopunroll,
                                     /*missed=*/std::nullopt,
                                     /*analysis=*/std::nullopt,
                                     /*failed=*/categoryLoopunroll};
remark::enableOptimizationRemarks(
    /*streamer=*/nullptr, cats,
    /*printAsEmitRemarks=*/true);
```

***

### 3. **With a Custom Streamer**

You can implement a custom streamer by inheriting `MLIRRemarkStreamerBase` to
consume remarks in any format.

```c++
class MyStreamer : public MLIRRemarkStreamerBase {
public:
  void streamOptimizationRemark(const Remark &remark) override {
    // Convert and write remark to your custom format
  }
};

auto myStreamer = std::make_unique<MyStreamer>();
remark::enableOptimizationRemarks(
    /*streamer=*/myStreamer, cats,
    /*printAsEmitRemarks=*/true);
```