| Issue |
144025
|
| Summary |
[MLIR] Inconsistent output when executing MLIR program with and without `-affine-loop-coalescing`
|
| Labels |
mlir
|
| Assignees |
|
| Reporter |
Lambor24
|
My git version is [4903c11](https://github.com/llvm/llvm-project/commit/4903c11a7e144d63635b115d97936a7aecf7a2f6).
## Description:
I am experiencing an inconsistent result when executing the same MLIR program with and without the `-affine-loop-coalescing`.
## Steps to Reproduce:
### 1. **MLIR Program (test.mlir)**:
test.mlir:
```
module {
func.func private @printMemrefI32(tensor<*xi32>)
func.func @main() {
%0 = "tosa.const"() <{values = dense<2> : tensor<2x2x3xi32>}> : () -> tensor<2x2x3xi32>
%1 = "tosa.const"() <{values = dense<5> : tensor<2x1x2xi32>}> : () -> tensor<2x1x2xi32>
%2 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
%3 = "tosa.const"() <{values = dense<0> : tensor<1xi32>}> : () -> tensor<1xi32>
%4 = tosa.matmul %1, %0, %2, %3 : (tensor<2x1x2xi32>, tensor<2x2x3xi32>, tensor<1xi32>, tensor<1xi32>) -> tensor<2x1x3xi32>
%cast = tensor.cast %4 : tensor<2x1x3xi32> to tensor<*xi32>
call @printMemrefI32(%cast) : (tensor<*xi32>) -> ()
return
}
}
```
### 2. **Command to Run Without `-affine-loop-coalescing`:**
```
/path/llvm-project/build/bin/mlir-opt test.mlir -pass-pipeline='builtin.module(func.func(tosa-to-linalg-named,tosa-to-linalg))' | \
/path/llvm-project/build/bin/mlir-opt -tosa-to-arith -one-shot-bufferize="bufferize-function-boundaries" -convert-linalg-to-affine-loops | \
/path/llvm-project/build/bin/mlir-opt -pass-pipeline="builtin.module(func.func(convert-affine-for-to-gpu{gpu-block-dims=1 gpu-thread-dims=0}))" | \
/path/llvm-project/build/bin/mlir-opt -lower-affine -gpu-lower-to-nvvm-pipeline | \
/path/llvm-project/build/bin/mlir-runner -e main -entry-point-result=void \
-shared-libs=/path/llvm-project/build/lib/libmlir_runner_utils.so \
-shared-libs=/path/llvm-project/build/lib/libmlir_c_runner_utils.so \
-shared-libs=/path/llvm-project/build/lib/libmlir_cuda_runtime.so.so
```
### 3. **Output Without `-affine-loop-coalescing`:**
```
[[[20, 20, 20]],
[[20, 20, 20]]]
```
### 4. **Command to Run With `-affine-loop-coalescing`:**
```
/path/llvm-project/build/bin/mlir-opt test.mlir -pass-pipeline='builtin.module(func.func(tosa-to-linalg-named,tosa-to-linalg))' | \
/path/llvm-project/build/bin/mlir-opt -tosa-to-arith -one-shot-bufferize="bufferize-function-boundaries" -convert-linalg-to-affine-loops -affine-loop-coalescing | \
/path/llvm-project/build/bin/mlir-opt -pass-pipeline="builtin.module(func.func(convert-affine-for-to-gpu{gpu-block-dims=1 gpu-thread-dims=0}))" | \
/path/llvm-project/build/bin/mlir-opt -lower-affine -gpu-lower-to-nvvm-pipeline | \
/path/llvm-project/build/bin/mlir-runner -e main -entry-point-result=void \
-shared-libs=/path/llvm-project/build/lib/libmlir_runner_utils.so \
-shared-libs=/path/llvm-project/build/lib/libmlir_c_runner_utils.so \
-shared-libs=/path/llvm-project/build/lib/libmlir_cuda_runtime.so.so
```
### 5. **Output With `-affine-loop-coalescing`:**
```
[[[10, 10, 10]],
[[10, 10, 10]]]
```
I'm not sure if there is any bug in my program or if the wrong usage of the above passes caused this result.
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