[Mlir-commits] [mlir] [mlir] run buffer deallocation in transform tutorial (PR #67978)

[llvmlistbot at llvm.org]

llvmbot wrote:


<!--LLVM PR SUMMARY COMMENT-->

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<details>
<summary>Changes</summary>

Buffer deallocation pipeline previously was incorrect when applied to functions. It has since been fixed. Make sure it is exercised in the tutorial to avoid leaking allocations.

---
Full diff: https://github.com/llvm/llvm-project/pull/67978.diff


2 Files Affected:

- (modified) mlir/docs/Tutorials/transform/ChH.md (+14) 
- (modified) mlir/test/Examples/transform/ChH/full.mlir (+13) 


``````````diff
diff --git a/mlir/docs/Tutorials/transform/ChH.md b/mlir/docs/Tutorials/transform/ChH.md
index 0696853dda1cf75..7c12728ac32466d 100644
--- a/mlir/docs/Tutorials/transform/ChH.md
+++ b/mlir/docs/Tutorials/transform/ChH.md
@@ -497,6 +497,20 @@ bufferization is directly available as a transform operation.
   function_boundary_type_conversion = 1 : i32 }
 ```
 
+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
+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
+%f = transform.structured.match ops{["func.func"]} in %arg1
+  : (!transform.any_op) -> !transform.any_op
+transform.apply_registered_pass "buffer-deallocation-pipeline" to %f
+  : (!transform.any_op) -> !transform.any_op
+```
+
 In this particular case, the transformed IR could be directly bufferized. This
 is not always the case in general as some operations, in particular
 `tensor.empty` may not be bufferizable. Such operations need to be removed
diff --git a/mlir/test/Examples/transform/ChH/full.mlir b/mlir/test/Examples/transform/ChH/full.mlir
index ed0509fcef6f12b..d90d740b4453126 100644
--- a/mlir/test/Examples/transform/ChH/full.mlir
+++ b/mlir/test/Examples/transform/ChH/full.mlir
@@ -1,6 +1,7 @@
 // RUN: mlir-opt %s --test-transform-dialect-interpreter \
 // RUN:             --test-transform-dialect-erase-schedule \
 // RUN:             --math-uplift-to-fma \
+// RUN:             --convert-bufferization-to-memref \
 // RUN:             --test-lower-to-llvm |\
 // RUN: FileCheck %s
 
@@ -307,10 +308,22 @@ module attributes { transform.with_named_sequence } {
     // transformation process, so invalidation is not an issue. However, if
     // other transformations, such as loop unrolling, are required after
     // bufferization, new handles should be produced using the match operations.
+    //
+    // 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 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.
     %arg1 = transform.bufferization.one_shot_bufferize %arg0 {
       bufferize_function_boundaries = true,
       function_boundary_type_conversion = 1 : i32 }
       : (!transform.any_op) -> !transform.any_op
+    %f = transform.structured.match ops{["func.func"]} in %arg1
+      : (!transform.any_op) -> !transform.any_op
+    transform.apply_registered_pass "buffer-deallocation-pipeline" to %f
+      : (!transform.any_op) -> !transform.any_op
 
     // Apply general canonicalization and CSE to each function after
     // bufferization as new simplification opportunities may have appeared.

``````````

</details>


https://github.com/llvm/llvm-project/pull/67978