[Mlir-commits] [mlir] Revert "[mlir][sparse] stress test BSR" (PR #72735)

Mehdi Amini llvmlistbot at llvm.org
Fri Nov 17 19:06:44 PST 2023


https://github.com/joker-eph created https://github.com/llvm/llvm-project/pull/72735

Reverts llvm/llvm-project#72712

This causes timeouts on the bots.

>From 9b2aa827d44f7cca47b8d8f66e19c023f6df5baf Mon Sep 17 00:00:00 2001
From: Mehdi Amini <joker.eph at gmail.com>
Date: Fri, 17 Nov 2023 19:06:26 -0800
Subject: [PATCH] Revert "[mlir][sparse] stress test BSR (#72712)"

This reverts commit 813aaf39f94609a46f38f1e3a15a763a2cc0d2cf.
---
 .../SparseTensor/CPU/block_majors.mlir        | 178 ------------------
 1 file changed, 178 deletions(-)
 delete mode 100755 mlir/test/Integration/Dialect/SparseTensor/CPU/block_majors.mlir

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
-  }
-}



More information about the Mlir-commits mailing list