[Mlir-commits] [mlir] e27ff89 - Revert "[mlir][SVE] Add an e2e test for vectorization of linalg.matmul (#69592)"

[Andrzej Warzynski]

Author: Andrzej Warzynski
Date: 2023-10-26T12:51:05Z
New Revision: e27ff897c2bf88d9c0b3d101bbe5e830e2831203

URL: https://github.com/llvm/llvm-project/commit/e27ff897c2bf88d9c0b3d101bbe5e830e2831203
DIFF: https://github.com/llvm/llvm-project/commit/e27ff897c2bf88d9c0b3d101bbe5e830e2831203.diff

LOG: Revert "[mlir][SVE] Add an e2e test for vectorization of linalg.matmul (#69592)"

Broken bot:
* https://lab.llvm.org/buildbot/#/builders/197/builds/10572

This reverts commit 64025b8eba200c0be7cedbb36c6dcbbea3ca96c7.

Added: 
    

Modified: 
    

Removed: 
    mlir/test/Integration/Dialect/Linalg/CPU/ArmSVE/matmul.mlir


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diff  --git a/mlir/test/Integration/Dialect/Linalg/CPU/ArmSVE/matmul.mlir b/mlir/test/Integration/Dialect/Linalg/CPU/ArmSVE/matmul.mlir
deleted file mode 100644
index bc94161d5d37545..000000000000000
--- a/mlir/test/Integration/Dialect/Linalg/CPU/ArmSVE/matmul.mlir
+++ /dev/null
@@ -1,71 +0,0 @@
-// RUN: mlir-opt %s -test-transform-dialect-interpreter -test-transform-dialect-erase-schedule \
-// RUN:   -one-shot-bufferize -func-bufferize -cse -canonicalize -convert-vector-to-scf -arm-sve-legalize-vector-storage \
-// RUN:   -convert-vector-to-llvm="enable-arm-sve" -test-lower-to-llvm | \
-// RUN: %mcr_aarch64_cmd -e=entry -entry-point-result=void --march=aarch64 --mattr="+sve" -shared-libs=%mlir_runner_utils,%mlir_c_runner_utils | \
-// RUN: FileCheck %s
-
-func.func @entry() {
-  %c1 = arith.constant 1 : index
-  %c2 = arith.constant 2 : index
-  %c4 = arith.constant 4 : index
-  %c0 = arith.constant 0 : index
-  %step = arith.constant 1 : index
-  %c0_f32 = arith.constant 0.0 : f32
-
-  %vscale = vector.vscale
-  %vl_fp = arith.muli %c4, %vscale : index
-  %A_alloc = bufferization.alloc_tensor(%c2, %c1) : tensor<?x?xf32>
-  %B_alloc = bufferization.alloc_tensor(%c1, %vl_fp) : tensor<?x?xf32>
-  %C_alloc = bufferization.alloc_tensor(%c2, %vl_fp) : tensor<?x?xf32>
-
-  %pi = arith.constant  3.14 : f32
-  %A = linalg.fill ins(%pi : f32) outs(%A_alloc : tensor<?x?xf32>) -> tensor<?x?xf32>
-  %B = linalg.fill ins(%pi : f32) outs(%B_alloc : tensor<?x?xf32>) -> tensor<?x?xf32>
-  %C_in = linalg.fill ins(%c0_f32 : f32) outs(%C_alloc : tensor<?x?xf32>) -> tensor<?x?xf32>
-
-  %C_out = linalg.matmul ins(%A, %B: tensor<?x?xf32>, tensor<?x?xf32>) outs(%C_in: tensor<?x?xf32>) -> tensor<?x?xf32>
-
-  // CHECK-LABEL: SVE: START OF TEST OUTPUT
-  vector.print str "SVE: START OF TEST OUTPUT"
-
-  // There are at least 4 x f32 elements in every SVE vector, i.e. 
-  //    * %vscale >= 1. 
-  // Hence, when checking the outupt there will always be at least 4 elements
-  // in every row. For implementations with wider vectors, you should see more
-  // elements being printed.
-  // CHECK-NEXT: Unranked Memref {{.*}} rank = 2 offset = 0 sizes = [2, 16] strides = [16, 1] data =
-  // CHECK-NEXT: [9.8596,   9.8596,   9.8596,   9.8596
-  // CHECK-NEXT: [9.8596,   9.8596,   9.8596,   9.8596
-
-  %xf = tensor.cast %C_out : tensor<?x?xf32> to tensor<*xf32>
-  call @printMemrefF32(%xf) : (tensor<*xf32>) -> ()
-
-  // CHECK-NEXT: SVE: END OF TEST OUTPUT
-  vector.print str "SVE: END OF TEST OUTPUT"
-
-  return
-}
-
-transform.sequence failures(propagate) {
-^bb1(%module_op: !transform.any_op):
-  %0 = transform.structured.match ops{["linalg.matmul"]} in %module_op : (!transform.any_op) -> !transform.any_op
-  %func_op = get_parent_op %0 : (!transform.any_op) -> !transform.op<"func.func">
-  // The tile sizes match the output matrix sizes
-  %1, %loops:3 = transform.structured.tile_using_for %0 [2, [4], 1] : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op, !transform.any_op)
-  %2 = transform.structured.match ops{["linalg.matmul"]} in %module_op : (!transform.any_op) -> !transform.any_op
-  // The vector sizes match the output matrix sizes
-  // TOOD: Use variables to re-use "shared" sizes
-  transform.structured.vectorize %2 vector_sizes [2, [4], 1] : !transform.any_op
-
-  transform.apply_patterns to %func_op {
-    transform.apply_patterns.vector.reduction_to_contract
-    transform.apply_patterns.vector.transfer_permutation_patterns
-    transform.apply_patterns.vector.lower_masked_transfers
-  } : !transform.op<"func.func">
-  transform.apply_patterns to %func_op {
-    transform.apply_patterns.vector.lower_contraction lowering_strategy = "outerproduct"
-    transform.apply_patterns.vector.lower_outerproduct
-  } : !transform.op<"func.func">
-}
-
-func.func private @printMemrefF32(%ptr : tensor<*xf32>)