Revert "[mlir][sparse] stress test BSR" #72735
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This reverts commit 813aaf3.
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@llvm/pr-subscribers-mlir-sparse Author: Mehdi Amini (joker-eph) ChangesReverts llvm/llvm-project#72712 This causes timeouts on the bots. Full diff: https://github.com/llvm/llvm-project/pull/72735.diff 1 Files Affected:
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/block_majors.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/block_majors.mlir
deleted file mode 100755
index ca7a3b302fdb632..000000000000000
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/block_majors.mlir
+++ /dev/null
@@ -1,178 +0,0 @@
-//--------------------------------------------------------------------------------------------------
-// WHEN CREATING A NEW TEST, PLEASE JUST COPY & PASTE WITHOUT EDITS.
-//
-// Set-up that's shared across all tests in this directory. In principle, this
-// config could be moved to lit.local.cfg. However, there are downstream users that
-// do not use these LIT config files. Hence why this is kept inline.
-//
-// DEFINE: %{sparsifier_opts} = enable-runtime-library=true
-// DEFINE: %{sparsifier_opts_sve} = enable-arm-sve=true %{sparsifier_opts}
-// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"
-// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"
-// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
-// DEFINE: %{run_opts} = -e main -entry-point-result=void
-// DEFINE: %{run} = mlir-cpu-runner %{run_opts} %{run_libs}
-// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs}
-//
-// DEFINE: %{env} =
-//--------------------------------------------------------------------------------------------------
-
-// RUN: %{compile} | %{run} | FileCheck %s
-//
-// Do the same run, but now with direct IR generation.
-// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false
-// RUN: %{compile} | %{run} | FileCheck %s
-//
-// Do the same run, but now with direct IR generation and vectorization.
-// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false enable-buffer-initialization=true vl=2 reassociate-fp-reductions=true enable-index-optimizations=true
-// RUN: %{compile} | %{run} | FileCheck %s
-
-#BSR_row_rowmajor = #sparse_tensor.encoding<{
- map = (i, j) ->
- ( i floordiv 3 : dense
- , j floordiv 4 : compressed
- , i mod 3 : dense
- , j mod 4 : dense
- )
-}>
-
-#BSR_row_colmajor = #sparse_tensor.encoding<{
- map = (i, j) ->
- ( i floordiv 3 : dense
- , j floordiv 4 : compressed
- , j mod 4 : dense
- , i mod 3 : dense
- )
-}>
-
-#BSR_col_rowmajor = #sparse_tensor.encoding<{
- map = (i, j) ->
- ( j floordiv 4 : dense
- , i floordiv 3 : compressed
- , i mod 3 : dense
- , j mod 4 : dense
- )
-}>
-
-#BSR_col_colmajor = #sparse_tensor.encoding<{
- map = (i, j) ->
- ( j floordiv 4 : dense
- , i floordiv 3 : compressed
- , j mod 4 : dense
- , i mod 3 : dense
- )
-}>
-
-//
-// Example 3x4 block storage of a 6x16 matrix:
-//
-// +---------+---------+---------+---------+
-// | 1 2 . . | . . . . | . . . . | . . . . |
-// | . . . . | . . . . | . . . . | . . . . |
-// | . . . 3 | . . . . | . . . . | . . . . |
-// +---------+---------+---------+---------+
-// | . . . . | . . . . | 4 5 . . | . . . . |
-// | . . . . | . . . . | . . . . | . . . . |
-// | . . . . | . . . . | . . 6 7 | . . . . |
-// +---------+---------+---------+---------+
-//
-// Storage for CSR block storage. Note that this essentially
-// provides CSR storage of 2x4 blocks with either row-major
-// or column-major storage within each 3x4 block of elements.
-//
-// positions[1] : 0 1 2
-// coordinates[1] : 0 2
-// values : 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3,
-// 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 [row-major]
-//
-// 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3,
-// 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 [col-major]
-//
-// Storage for CSC block storage. Note that this essentially
-// provides CSC storage of 4x2 blocks with either row-major
-// or column-major storage within each 3x4 block of elements.
-//
-// positions[1] : 0 1 1 2 2
-// coordinates[1] : 0 1
-// values : 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3,
-// 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 [row-major]
-//
-// 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3,
-// 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 [col-major]
-//
-module {
-
- func.func @main() {
- %c0 = arith.constant 0 : index
- %f0 = arith.constant 0.0 : f64
-
- %m = arith.constant sparse<
- [ [0, 0], [0, 1], [2, 3], [3, 8], [3, 9], [5, 10], [5, 11] ],
- [ 1., 2., 3., 4., 5., 6., 7.]
- > : tensor<6x16xf64>
- %s1 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor<?x?xf64, #BSR_row_rowmajor>
- %s2 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor<?x?xf64, #BSR_row_colmajor>
- %s3 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor<?x?xf64, #BSR_col_rowmajor>
- %s4 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor<?x?xf64, #BSR_col_colmajor>
-
- // CHECK: ( 0, 1, 2 )
- // CHECK-NEXT: ( 0, 2 )
- // CHECK-NEXT: ( 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 )
- %pos1 = sparse_tensor.positions %s1 {level = 1 : index } : tensor<?x?xf64, #BSR_row_rowmajor> to memref<?xindex>
- %vecp1 = vector.transfer_read %pos1[%c0], %c0 : memref<?xindex>, vector<3xindex>
- vector.print %vecp1 : vector<3xindex>
- %crd1 = sparse_tensor.coordinates %s1 {level = 1 : index } : tensor<?x?xf64, #BSR_row_rowmajor> to memref<?xindex>
- %vecc1 = vector.transfer_read %crd1[%c0], %c0 : memref<?xindex>, vector<2xindex>
- vector.print %vecc1 : vector<2xindex>
- %val1 = sparse_tensor.values %s1 : tensor<?x?xf64, #BSR_row_rowmajor> to memref<?xf64>
- %vecv1 = vector.transfer_read %val1[%c0], %f0 : memref<?xf64>, vector<24xf64>
- vector.print %vecv1 : vector<24xf64>
-
- // CHECK-NEXT: ( 0, 1, 2 )
- // CHECK-NEXT: ( 0, 2 )
- // CHECK-NEXT: ( 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 )
- %pos2 = sparse_tensor.positions %s2 {level = 1 : index } : tensor<?x?xf64, #BSR_row_colmajor> to memref<?xindex>
- %vecp2 = vector.transfer_read %pos2[%c0], %c0 : memref<?xindex>, vector<3xindex>
- vector.print %vecp2 : vector<3xindex>
- %crd2 = sparse_tensor.coordinates %s2 {level = 1 : index } : tensor<?x?xf64, #BSR_row_colmajor> to memref<?xindex>
- %vecc2 = vector.transfer_read %crd2[%c0], %c0 : memref<?xindex>, vector<2xindex>
- vector.print %vecc2 : vector<2xindex>
- %val2 = sparse_tensor.values %s2 : tensor<?x?xf64, #BSR_row_colmajor> to memref<?xf64>
- %vecv2 = vector.transfer_read %val2[%c0], %f0 : memref<?xf64>, vector<24xf64>
- vector.print %vecv2 : vector<24xf64>
-
- // CHECK-NEXT: ( 0, 1, 1, 2, 2 )
- // CHECK-NEXT: ( 0, 1 )
- // CHECK-NEXT: ( 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 )
- %pos3 = sparse_tensor.positions %s3 {level = 1 : index } : tensor<?x?xf64, #BSR_col_rowmajor> to memref<?xindex>
- %vecp3 = vector.transfer_read %pos3[%c0], %c0 : memref<?xindex>, vector<5xindex>
- vector.print %vecp3 : vector<5xindex>
- %crd3 = sparse_tensor.coordinates %s3 {level = 1 : index } : tensor<?x?xf64, #BSR_col_rowmajor> to memref<?xindex>
- %vecc3 = vector.transfer_read %crd3[%c0], %c0 : memref<?xindex>, vector<2xindex>
- vector.print %vecc3 : vector<2xindex>
- %val3 = sparse_tensor.values %s3 : tensor<?x?xf64, #BSR_col_rowmajor> to memref<?xf64>
- %vecv3 = vector.transfer_read %val3[%c0], %f0 : memref<?xf64>, vector<24xf64>
- vector.print %vecv3 : vector<24xf64>
-
- // CHECK-NEXT: ( 0, 1, 1, 2, 2 )
- // CHECK-NEXT: ( 0, 1 )
- // CHECK-NEXT: ( 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 )
- %pos4 = sparse_tensor.positions %s4 {level = 1 : index } : tensor<?x?xf64, #BSR_col_colmajor> to memref<?xindex>
- %vecp4 = vector.transfer_read %pos4[%c0], %c0 : memref<?xindex>, vector<5xindex>
- vector.print %vecp4 : vector<5xindex>
- %crd4 = sparse_tensor.coordinates %s4 {level = 1 : index } : tensor<?x?xf64, #BSR_col_colmajor> to memref<?xindex>
- %vecc4 = vector.transfer_read %crd4[%c0], %c0 : memref<?xindex>, vector<2xindex>
- vector.print %vecc4 : vector<2xindex>
- %val4 = sparse_tensor.values %s4 : tensor<?x?xf64, #BSR_col_colmajor> to memref<?xf64>
- %vecv4 = vector.transfer_read %val4[%c0], %f0 : memref<?xf64>, vector<24xf64>
- vector.print %vecv4 : vector<24xf64>
-
- // Release the resources.
- bufferization.dealloc_tensor %s1: tensor<?x?xf64, #BSR_row_rowmajor>
- bufferization.dealloc_tensor %s2: tensor<?x?xf64, #BSR_row_colmajor>
- bufferization.dealloc_tensor %s3: tensor<?x?xf64, #BSR_col_rowmajor>
- bufferization.dealloc_tensor %s4: tensor<?x?xf64, #BSR_col_colmajor>
-
- return
- }
-}
|
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@llvm/pr-subscribers-mlir Author: Mehdi Amini (joker-eph) ChangesReverts llvm/llvm-project#72712 This causes timeouts on the bots. Full diff: https://github.com/llvm/llvm-project/pull/72735.diff 1 Files Affected:
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/block_majors.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/block_majors.mlir
deleted file mode 100755
index ca7a3b302fdb632..000000000000000
--- a/mlir/test/Integration/Dialect/SparseTensor/CPU/block_majors.mlir
+++ /dev/null
@@ -1,178 +0,0 @@
-//--------------------------------------------------------------------------------------------------
-// WHEN CREATING A NEW TEST, PLEASE JUST COPY & PASTE WITHOUT EDITS.
-//
-// Set-up that's shared across all tests in this directory. In principle, this
-// config could be moved to lit.local.cfg. However, there are downstream users that
-// do not use these LIT config files. Hence why this is kept inline.
-//
-// DEFINE: %{sparsifier_opts} = enable-runtime-library=true
-// DEFINE: %{sparsifier_opts_sve} = enable-arm-sve=true %{sparsifier_opts}
-// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"
-// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"
-// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
-// DEFINE: %{run_opts} = -e main -entry-point-result=void
-// DEFINE: %{run} = mlir-cpu-runner %{run_opts} %{run_libs}
-// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs}
-//
-// DEFINE: %{env} =
-//--------------------------------------------------------------------------------------------------
-
-// RUN: %{compile} | %{run} | FileCheck %s
-//
-// Do the same run, but now with direct IR generation.
-// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false
-// RUN: %{compile} | %{run} | FileCheck %s
-//
-// Do the same run, but now with direct IR generation and vectorization.
-// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false enable-buffer-initialization=true vl=2 reassociate-fp-reductions=true enable-index-optimizations=true
-// RUN: %{compile} | %{run} | FileCheck %s
-
-#BSR_row_rowmajor = #sparse_tensor.encoding<{
- map = (i, j) ->
- ( i floordiv 3 : dense
- , j floordiv 4 : compressed
- , i mod 3 : dense
- , j mod 4 : dense
- )
-}>
-
-#BSR_row_colmajor = #sparse_tensor.encoding<{
- map = (i, j) ->
- ( i floordiv 3 : dense
- , j floordiv 4 : compressed
- , j mod 4 : dense
- , i mod 3 : dense
- )
-}>
-
-#BSR_col_rowmajor = #sparse_tensor.encoding<{
- map = (i, j) ->
- ( j floordiv 4 : dense
- , i floordiv 3 : compressed
- , i mod 3 : dense
- , j mod 4 : dense
- )
-}>
-
-#BSR_col_colmajor = #sparse_tensor.encoding<{
- map = (i, j) ->
- ( j floordiv 4 : dense
- , i floordiv 3 : compressed
- , j mod 4 : dense
- , i mod 3 : dense
- )
-}>
-
-//
-// Example 3x4 block storage of a 6x16 matrix:
-//
-// +---------+---------+---------+---------+
-// | 1 2 . . | . . . . | . . . . | . . . . |
-// | . . . . | . . . . | . . . . | . . . . |
-// | . . . 3 | . . . . | . . . . | . . . . |
-// +---------+---------+---------+---------+
-// | . . . . | . . . . | 4 5 . . | . . . . |
-// | . . . . | . . . . | . . . . | . . . . |
-// | . . . . | . . . . | . . 6 7 | . . . . |
-// +---------+---------+---------+---------+
-//
-// Storage for CSR block storage. Note that this essentially
-// provides CSR storage of 2x4 blocks with either row-major
-// or column-major storage within each 3x4 block of elements.
-//
-// positions[1] : 0 1 2
-// coordinates[1] : 0 2
-// values : 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3,
-// 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 [row-major]
-//
-// 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3,
-// 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 [col-major]
-//
-// Storage for CSC block storage. Note that this essentially
-// provides CSC storage of 4x2 blocks with either row-major
-// or column-major storage within each 3x4 block of elements.
-//
-// positions[1] : 0 1 1 2 2
-// coordinates[1] : 0 1
-// values : 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3,
-// 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 [row-major]
-//
-// 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3,
-// 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 [col-major]
-//
-module {
-
- func.func @main() {
- %c0 = arith.constant 0 : index
- %f0 = arith.constant 0.0 : f64
-
- %m = arith.constant sparse<
- [ [0, 0], [0, 1], [2, 3], [3, 8], [3, 9], [5, 10], [5, 11] ],
- [ 1., 2., 3., 4., 5., 6., 7.]
- > : tensor<6x16xf64>
- %s1 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor<?x?xf64, #BSR_row_rowmajor>
- %s2 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor<?x?xf64, #BSR_row_colmajor>
- %s3 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor<?x?xf64, #BSR_col_rowmajor>
- %s4 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor<?x?xf64, #BSR_col_colmajor>
-
- // CHECK: ( 0, 1, 2 )
- // CHECK-NEXT: ( 0, 2 )
- // CHECK-NEXT: ( 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 )
- %pos1 = sparse_tensor.positions %s1 {level = 1 : index } : tensor<?x?xf64, #BSR_row_rowmajor> to memref<?xindex>
- %vecp1 = vector.transfer_read %pos1[%c0], %c0 : memref<?xindex>, vector<3xindex>
- vector.print %vecp1 : vector<3xindex>
- %crd1 = sparse_tensor.coordinates %s1 {level = 1 : index } : tensor<?x?xf64, #BSR_row_rowmajor> to memref<?xindex>
- %vecc1 = vector.transfer_read %crd1[%c0], %c0 : memref<?xindex>, vector<2xindex>
- vector.print %vecc1 : vector<2xindex>
- %val1 = sparse_tensor.values %s1 : tensor<?x?xf64, #BSR_row_rowmajor> to memref<?xf64>
- %vecv1 = vector.transfer_read %val1[%c0], %f0 : memref<?xf64>, vector<24xf64>
- vector.print %vecv1 : vector<24xf64>
-
- // CHECK-NEXT: ( 0, 1, 2 )
- // CHECK-NEXT: ( 0, 2 )
- // CHECK-NEXT: ( 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 )
- %pos2 = sparse_tensor.positions %s2 {level = 1 : index } : tensor<?x?xf64, #BSR_row_colmajor> to memref<?xindex>
- %vecp2 = vector.transfer_read %pos2[%c0], %c0 : memref<?xindex>, vector<3xindex>
- vector.print %vecp2 : vector<3xindex>
- %crd2 = sparse_tensor.coordinates %s2 {level = 1 : index } : tensor<?x?xf64, #BSR_row_colmajor> to memref<?xindex>
- %vecc2 = vector.transfer_read %crd2[%c0], %c0 : memref<?xindex>, vector<2xindex>
- vector.print %vecc2 : vector<2xindex>
- %val2 = sparse_tensor.values %s2 : tensor<?x?xf64, #BSR_row_colmajor> to memref<?xf64>
- %vecv2 = vector.transfer_read %val2[%c0], %f0 : memref<?xf64>, vector<24xf64>
- vector.print %vecv2 : vector<24xf64>
-
- // CHECK-NEXT: ( 0, 1, 1, 2, 2 )
- // CHECK-NEXT: ( 0, 1 )
- // CHECK-NEXT: ( 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 )
- %pos3 = sparse_tensor.positions %s3 {level = 1 : index } : tensor<?x?xf64, #BSR_col_rowmajor> to memref<?xindex>
- %vecp3 = vector.transfer_read %pos3[%c0], %c0 : memref<?xindex>, vector<5xindex>
- vector.print %vecp3 : vector<5xindex>
- %crd3 = sparse_tensor.coordinates %s3 {level = 1 : index } : tensor<?x?xf64, #BSR_col_rowmajor> to memref<?xindex>
- %vecc3 = vector.transfer_read %crd3[%c0], %c0 : memref<?xindex>, vector<2xindex>
- vector.print %vecc3 : vector<2xindex>
- %val3 = sparse_tensor.values %s3 : tensor<?x?xf64, #BSR_col_rowmajor> to memref<?xf64>
- %vecv3 = vector.transfer_read %val3[%c0], %f0 : memref<?xf64>, vector<24xf64>
- vector.print %vecv3 : vector<24xf64>
-
- // CHECK-NEXT: ( 0, 1, 1, 2, 2 )
- // CHECK-NEXT: ( 0, 1 )
- // CHECK-NEXT: ( 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 )
- %pos4 = sparse_tensor.positions %s4 {level = 1 : index } : tensor<?x?xf64, #BSR_col_colmajor> to memref<?xindex>
- %vecp4 = vector.transfer_read %pos4[%c0], %c0 : memref<?xindex>, vector<5xindex>
- vector.print %vecp4 : vector<5xindex>
- %crd4 = sparse_tensor.coordinates %s4 {level = 1 : index } : tensor<?x?xf64, #BSR_col_colmajor> to memref<?xindex>
- %vecc4 = vector.transfer_read %crd4[%c0], %c0 : memref<?xindex>, vector<2xindex>
- vector.print %vecc4 : vector<2xindex>
- %val4 = sparse_tensor.values %s4 : tensor<?x?xf64, #BSR_col_colmajor> to memref<?xf64>
- %vecv4 = vector.transfer_read %val4[%c0], %f0 : memref<?xf64>, vector<24xf64>
- vector.print %vecv4 : vector<24xf64>
-
- // Release the resources.
- bufferization.dealloc_tensor %s1: tensor<?x?xf64, #BSR_row_rowmajor>
- bufferization.dealloc_tensor %s2: tensor<?x?xf64, #BSR_row_colmajor>
- bufferization.dealloc_tensor %s3: tensor<?x?xf64, #BSR_col_rowmajor>
- bufferization.dealloc_tensor %s4: tensor<?x?xf64, #BSR_col_colmajor>
-
- return
- }
-}
|
sr-tream
pushed a commit
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that referenced
this pull request
Nov 20, 2023
Reverts llvm#72712 This causes timeouts on the bots.
zahiraam
pushed a commit
to zahiraam/llvm-project
that referenced
this pull request
Nov 20, 2023
Reverts llvm#72712 This causes timeouts on the bots.
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Reverts #72712
This causes timeouts on the bots.