-
Notifications
You must be signed in to change notification settings - Fork 647
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Reapply "Propagate reshapes through generics with reduction… (#18968)
This reverts commit 8d3faf8. Signed-off-by: Ian Wood <[email protected]>
- Loading branch information
Showing
3 changed files
with
103 additions
and
11 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
98 changes: 98 additions & 0 deletions
98
compiler/src/iree/compiler/Dialect/Flow/Transforms/test/pipeline_tests.mlir
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,98 @@ | ||
| // TODO(hanchung): Split the transformation pipeline tests into two mlir files. | ||
| // RUN: iree-opt --iree-global-optimization-transformation-pipeline --iree-dispatch-creation-pipeline --iree-flow-transformation-pipeline --split-input-file %s | FileCheck %s | ||
|
|
||
| #map = affine_map<(d0, d1) -> (d0)> | ||
| #map1 = affine_map<(d0, d1) -> (d1)> | ||
| #map2 = affine_map<(d0, d1) -> (d0, d1)> | ||
| #map3 = affine_map<(d0, d1) -> ()> | ||
| util.func public @main(%arg0: tensor<833xi32>, %arg1: tensor<833x833xf32>, %arg2: tensor<f32>) -> tensor<f32> { | ||
| %cst = arith.constant 5.66893432E-4 : f32 | ||
| %0 = tensor.empty() : tensor<833x833xf32> | ||
| %1 = linalg.generic { | ||
| indexing_maps = [#map2, #map3, #map2], iterator_types = ["parallel", "parallel"]} | ||
| ins(%arg1, %arg2 : tensor<833x833xf32>, tensor<f32>) | ||
| outs(%0 : tensor<833x833xf32>) { | ||
| ^bb0(%b0 : f32, %b1 : f32, %b2 : f32): | ||
| %2 = arith.divf %b0, %b1 : f32 | ||
| linalg.yield %2 : f32 | ||
| } -> tensor<833x833xf32> | ||
| %4 = linalg.generic { | ||
| indexing_maps = [#map, #map1, #map2, #map2], iterator_types = ["parallel", "parallel"]} | ||
| ins(%arg0, %arg0, %1 : tensor<833xi32>, tensor<833xi32>, tensor<833x833xf32>) | ||
| outs(%0 : tensor<833x833xf32>) { | ||
| ^bb0(%b0 : i32, %b1 : i32, %b2 : f32, %b3 : f32): | ||
| %5 = arith.cmpi eq, %b0, %b1 : i32 | ||
| %6 = arith.select %5, %b2, %cst : f32 | ||
| linalg.yield %6 : f32 | ||
| } -> tensor<833x833xf32> | ||
| %7 = tensor.empty() : tensor<f32> | ||
| %8 = linalg.fill ins(%cst : f32) outs(%7 : tensor<f32>) -> tensor<f32> | ||
| %9 = linalg.generic { | ||
| indexing_maps = [#map2, #map3], iterator_types = ["reduction", "reduction"]} | ||
| ins(%4 : tensor<833x833xf32>) outs(%7 : tensor<f32>) { | ||
| ^bb0(%b0 : f32, %b1 : f32): | ||
| %10 = arith.addf %b1, %b0 : f32 | ||
| linalg.yield %10 : f32 | ||
| } -> tensor<f32> | ||
| util.return %9 : tensor<f32> | ||
| } | ||
| // Check that the linalg op with two reduction loops get folded into a single | ||
| // reduction which then prevents the parallel ops to be folded into it. | ||
| // See https://github.com/iree-org/iree/issues/13285 | ||
| // CHECK: flow.executable private @[[EXECUTABLE0:[a-zA-Z0-9_]+]] | ||
| // CHECK: func.func @[[FUNC0:[a-zA-Z0-9_x]+]] | ||
| // CHECK: linalg.generic | ||
| // CHECK-SAME: ["reduction", "reduction"] | ||
| // CHECK-NOT: linalg.generic | ||
| // CHECK: util.func public @main( | ||
| // CHECK: %[[T0:.+]] = flow.dispatch @[[EXECUTABLE0]]::@[[FUNC0]] | ||
| // CHECK: util.return %[[T0]] | ||
|
|
||
| // ----- | ||
|
|
||
| #map = affine_map<(d0, d1, d2) -> (d0, d1, d2)> | ||
| #map1 = affine_map<(d0, d1, d2) -> (d0, d1, 0)> | ||
| #map2 = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d3, d4)> | ||
| #map3 = affine_map<(d0, d1, d2, d3, d4) -> (d2, d3, d4)> | ||
| #map4 = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d2)> | ||
| util.func public @grouped_quantized_matmul(%arg0: tensor<4096x32x128xi4>, %arg1: tensor<1x1x32x128xf32>, %arg2: tensor<4096x32x1xf32>, %arg3: tensor<4096x32x1xf32>) -> tensor<1x1x4096xf32> { | ||
| %cst = arith.constant 0.000000e+00 : f32 | ||
| %0 = tensor.empty() : tensor<1x1x4096xf32> | ||
| %1 = tensor.empty() : tensor<4096x32x128xf32> | ||
| %2 = linalg.fill ins(%cst : f32) outs(%0 : tensor<1x1x4096xf32>) -> tensor<1x1x4096xf32> | ||
| %3 = linalg.generic {indexing_maps = [#map, #map1, #map1, #map], iterator_types = ["parallel", "parallel", "parallel"]} ins(%arg0, %arg2, %arg3 : tensor<4096x32x128xi4>, tensor<4096x32x1xf32>, tensor<4096x32x1xf32>) outs(%1 : tensor<4096x32x128xf32>) { | ||
| ^bb0(%in: i4, %in_0: f32, %in_1: f32, %out: f32): | ||
| %5 = arith.extui %in : i4 to i32 | ||
| %6 = arith.uitofp %5 : i32 to f32 | ||
| %7 = arith.subf %6, %in_1 : f32 | ||
| %8 = arith.mulf %7, %in_0 : f32 | ||
| linalg.yield %8 : f32 | ||
| } -> tensor<4096x32x128xf32> | ||
| %4 = linalg.generic {indexing_maps = [#map2, #map3, #map4], iterator_types = ["parallel", "parallel", "parallel", "reduction", "reduction"]} ins(%arg1, %3 : tensor<1x1x32x128xf32>, tensor<4096x32x128xf32>) outs(%2 : tensor<1x1x4096xf32>) { | ||
| ^bb0(%in: f32, %in_0: f32, %out: f32): | ||
| %5 = arith.mulf %in, %in_0 : f32 | ||
| %6 = arith.addf %5, %out : f32 | ||
| linalg.yield %6 : f32 | ||
| } -> tensor<1x1x4096xf32> | ||
| util.return %4 : tensor<1x1x4096xf32> | ||
| } | ||
| // Check that the two linalg.generic ops are fused into the same dispatch. | ||
| // CHECK: flow.executable private @[[EXECUTABLE0:[a-zA-Z0-9_]+]] | ||
| // CHECK: func.func @[[FUNC0:[a-zA-Z0-9_x]+]] | ||
| // CHECK: %[[GEN0:.+]] = linalg.generic | ||
| // CHECK-SAME: ["parallel", "parallel", "parallel", "parallel", "parallel"] | ||
| // CHECK: arith.extui | ||
| // CHECK: arith.uitofp | ||
| // CHECK: arith.subf | ||
| // CHECK: arith.mulf | ||
| // CHECK: %[[GEN1:.+]] = linalg.generic | ||
| // CHECK-SAME: ["parallel", "parallel", "parallel", "reduction", "reduction"] | ||
| // CHECK-SAME: ins( | ||
| // CHECK-SAME: %[[GEN0]] | ||
| // CHECK-SAME: outs( | ||
| // CHECK: arith.mulf | ||
| // CHECK: arith.addf | ||
| // CHECK: flow.dispatch.tensor.store %[[GEN1]] | ||
| // CHECK: util.func public @grouped_quantized_matmul( | ||
| // CHECK: %[[T0:.+]] = flow.dispatch @[[EXECUTABLE0]]::@[[FUNC0]] | ||
| // CHECK: util.return %[[T0]] |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters