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| author | River Riddle <riverriddle@google.com> | 2019-03-28 14:58:52 -0700 |
|---|---|---|
| committer | jpienaar <jpienaar@google.com> | 2019-03-29 17:51:32 -0700 |
| commit | 01140bd137cfb0ca6b14293e9392640be9857a73 (patch) | |
| tree | c660508c28ef36a124a399d79061840b19b25c27 /mlir/test/Transforms/Vectorize | |
| parent | 9d9675fc8fa96e78efa17dcc2d6fcc3e773f7a5f (diff) | |
| download | bcm5719-llvm-01140bd137cfb0ca6b14293e9392640be9857a73.tar.gz bcm5719-llvm-01140bd137cfb0ca6b14293e9392640be9857a73.zip | |
Change the muli-return syntax for operations. The name of the operation result now contains the number of results that it refers to if the number of results is greater than 1.
Example:
%call:2 = call @multi_return() : () -> (f32, i32)
use(%calltensorflow/mlir#0, %calltensorflow/mlir#1)
This cl also adds parser support for uniquely named result values. This means that a test writer can now write something like:
%foo, %bar = call @multi_return() : () -> (f32, i32)
use(%foo, %bar)
Note: The printer will still print the collapsed form.
PiperOrigin-RevId: 240860058
Diffstat (limited to 'mlir/test/Transforms/Vectorize')
| -rw-r--r-- | mlir/test/Transforms/Vectorize/vectorize_1d.mlir | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/mlir/test/Transforms/Vectorize/vectorize_1d.mlir b/mlir/test/Transforms/Vectorize/vectorize_1d.mlir index 15b6ba73f0a..df829fe7799 100644 --- a/mlir/test/Transforms/Vectorize/vectorize_1d.mlir +++ b/mlir/test/Transforms/Vectorize/vectorize_1d.mlir @@ -46,7 +46,7 @@ func @vec1d_2(%A : memref<?x?xf32>, %B : memref<?x?x?xf32>) { // CHECK-NEXT: {{.*}} = vector_transfer_read %arg0, [[C0]], [[APP3]] {permutation_map: #[[map_proj_d0d1_d1]]} : {{.*}} -> vector<128xf32> affine.for %i3 = 0 to %M { // vectorized %r3 = affine.apply (d0) -> (d0) (%i3) - %a3 = load %A[%cst0, %r3#0] : memref<?x?xf32> + %a3 = load %A[%cst0, %r3] : memref<?x?xf32> } return } @@ -161,7 +161,7 @@ func @vec_rejected_2(%A : memref<?x?xf32>, %B : memref<?x?x?xf32>) { // CHECK: affine.for %i{{[0-9]*}} = 0 to [[ARG_M]] { affine.for %i2 = 0 to %M { // not vectorized, would vectorize with --test-fastest-varying=1 %r2 = affine.apply (d0) -> (d0) (%i2) - %a2 = load %A[%r2#0, %cst0] : memref<?x?xf32> + %a2 = load %A[%r2, %cst0] : memref<?x?xf32> } return } |
