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Differential D94093

[mlir][Linalg] Add a test case that consumer has "reduction" loops.
ClosedPublic

Authored by hanchung on Jan 5 2021, 8:35 AM.

Details

Reviewers
mravishankar
nicolasvasilache
Commits
rG30dcbb2a8301: [mlir][Linalg] Add a test case that consumer has "reduction" loops.
Summary

In the past, this was a missing test case and the fusion was not supported. It's
supported after the revisit of init_tensor in Linalg.

Diff Detail

Event Timeline

hanchung created this revision.Jan 5 2021, 8:35 AM
Herald added subscribers: teijeong, rdzhabarov, tatianashp and 14 others. · View Herald TranscriptJan 5 2021, 8:35 AM
hanchung requested review of this revision.Jan 5 2021, 8:35 AM
Herald added a project: Restricted Project. · View Herald TranscriptJan 5 2021, 8:35 AM
Herald added subscribers: limo1996, stephenneuendorffer. · View Herald Transcript
hanchung updated this revision to Diff 314628.Jan 5 2021, 8:37 AM

format the test a bit.

nicolasvasilache accepted this revision.Jan 5 2021, 8:52 AM
This revision is now accepted and ready to land.Jan 5 2021, 8:52 AM
Harbormaster completed remote builds in B84060: Diff 314626.Jan 5 2021, 8:59 AM
Harbormaster completed remote builds in B84062: Diff 314628.Jan 5 2021, 9:15 AM
Closed by commit rG30dcbb2a8301: [mlir][Linalg] Add a test case that consumer has "reduction" loops. (authored by hanchung). · Explain WhyJan 5 2021, 9:47 AM
This revision was automatically updated to reflect the committed changes.
hanchung added a commit: rG30dcbb2a8301: [mlir][Linalg] Add a test case that consumer has "reduction" loops..

Revision Contents

PathSize
mlir/
test/
Dialect/
Linalg/
43 lines

Diff 314626

mlir/test/Dialect/Linalg/fusion-tensor.mlir

Show First 20 Lines • Show All 530 Lines • ▼ Show 20 Lines
// CHECK-SAME: indexing_maps = [#[[MAP]], #[[MAP]]] // CHECK-SAME: indexing_maps = [#[[MAP]], #[[MAP]]]
// CHECK-SAME: ins(%[[ARG0]] : tensor<4xf32>) // CHECK-SAME: ins(%[[ARG0]] : tensor<4xf32>)
// CHECK-SAME: outs(%[[T0]] : tensor<4xf32>) // CHECK-SAME: outs(%[[T0]] : tensor<4xf32>)
// CHECK: ^{{.+}}( // CHECK: ^{{.+}}(
// CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: f32, %[[ARG2:[a-zA-Z0-9_]+]]: f32) // CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: f32, %[[ARG2:[a-zA-Z0-9_]+]]: f32)
// CHECK: %[[T2:.+]] = addf %[[ARG1]], %[[CST]] // CHECK: %[[T2:.+]] = addf %[[ARG1]], %[[CST]]
// CHECK: linalg.yield %[[T2]] // CHECK: linalg.yield %[[T2]]
// CHECK: return %[[T1]] // CHECK: return %[[T1]]
// -----
#map0 = affine_map<(d0, d1) -> (d0, d1)>
#map1 = affine_map<(d0) -> (0, d0)>
#map2 = affine_map<(d0) -> (0)>
func @consumer_with_reduction(%arg0: tensor<1x10xf32>,
%arg1: tensor<1x10xf32>,
%arg2: tensor<1xf32>) -> tensor<1xf32> {
%init = linalg.init_tensor [1, 10] : tensor<1x10xf32>
%0 = linalg.generic
{indexing_maps = [#map0, #map0, #map0],
iterator_types = ["parallel", "parallel"]}
ins(%arg0, %arg1 : tensor<1x10xf32>, tensor<1x10xf32>)
outs(%init : tensor<1x10xf32>) {
^bb0(%arg3: f32, %arg4: f32, %arg5: f32): // no predecessors
%2 = addf %arg3, %arg4 : f32
linalg.yield %2 : f32
} -> tensor<1x10xf32>
%1 = linalg.generic
{indexing_maps = [#map1, #map2],
iterator_types = ["reduction"]}
ins(%0 : tensor<1x10xf32>)
outs(%arg2 : tensor<1xf32>) {
^bb0(%arg3: f32, %arg4: f32): // no predecessors
%2 = addf %arg3, %arg4 : f32
linalg.yield %2 : f32
} -> tensor<1xf32>
return %1 : tensor<1xf32>
}
// CHECK-DAG: #[[MAP0:.+]] = affine_map<(d0) -> (0, d0)>
// CHECK-DAG: #[[MAP1:.+]] = affine_map<(d0) -> (0)>
// CHECK: func @consumer_with_reduction(%[[ARG0:.+]]: tensor<1x10xf32>, %[[ARG1:.+]]: tensor<1x10xf32>, %[[ARG2:.+]]: tensor<1xf32>)
// CHECK: %[[RES:.+]] = linalg.generic
// CHECK-SAME: indexing_maps = [#[[MAP0]], #[[MAP0]], #[[MAP1]]]
// CHECK-SAME: iterator_types = ["reduction"]
// CHECK-SAME: ins(%[[ARG0]], %[[ARG1]] : tensor<1x10xf32>, tensor<1x10xf32>)
// CHECK: ^{{.+}}(
// CHECK-SAME: %[[T0:.+]]: f32, %[[T1:.+]]: f32, %[[T2:.+]]: f32)
// CHECK: %[[T3:.+]] = addf %[[T0]], %[[T1]] : f32
// CHECK: %[[T4:.+]] = addf %[[T3]], %[[T2]] : f32
// CHECK: linalg.yield %[[T4]]
// CHECK: return %[[RES]]