forked from OSchip/llvm-project
[mlir][sparse] add an elaborate sparse storage scheme integration test
Looks "under the hood" of the sparse stogage schemes. Users should typically not be interested in these details (hey, that is why we have "sparse compilers"!) but this test makes sure the compact contents are as expected. Reviewed By: ThomasRaoux, bixia Differential Revision: https://reviews.llvm.org/D107683
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Aart Bik
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15cacab73f
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// RUN: mlir-opt %s \
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// RUN: --sparsification --sparse-tensor-conversion \
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// RUN: --convert-vector-to-scf --convert-scf-to-std \
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// RUN: --func-bufferize --tensor-constant-bufferize --tensor-bufferize \
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// RUN: --std-bufferize --finalizing-bufferize \
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// RUN: --convert-vector-to-llvm --convert-memref-to-llvm --convert-std-to-llvm | \
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// RUN: mlir-cpu-runner \
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// RUN: -e entry -entry-point-result=void \
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// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \
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// RUN: FileCheck %s
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//
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// Several common sparse storage schemes.
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//
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#Dense = #sparse_tensor.encoding<{
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dimLevelType = [ "dense", "dense" ]
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}>
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#CSR = #sparse_tensor.encoding<{
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dimLevelType = [ "dense", "compressed" ]
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}>
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#DCSR = #sparse_tensor.encoding<{
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dimLevelType = [ "compressed", "compressed" ]
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}>
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#CSC = #sparse_tensor.encoding<{
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dimLevelType = [ "dense", "compressed" ],
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dimOrdering = affine_map<(i,j) -> (j,i)>
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}>
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#DCSC = #sparse_tensor.encoding<{
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dimLevelType = [ "compressed", "compressed" ],
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dimOrdering = affine_map<(i,j) -> (j,i)>
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}>
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//
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// Integration test that looks "under the hood" of sparse storage schemes.
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//
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module {
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//
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// Main driver that initializes a sparse tensor and inspects the sparse
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// storage schemes in detail. Note that users of the MLIR sparse compiler
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// are typically not concerned with such details, but the test ensures
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// everything is working "under the hood".
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//
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func @entry() {
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%c0 = constant 0 : index
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%c1 = constant 1 : index
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%d0 = constant 0.0 : f64
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//
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// Initialize a dense tensor.
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//
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%t = constant dense<[
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[ 1.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 3.0],
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[ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
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[ 0.0, 0.0, 4.0, 0.0, 0.0, 0.0, 0.0, 0.0],
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[ 0.0, 0.0, 0.0, 5.0, 0.0, 0.0, 0.0, 0.0],
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[ 0.0, 0.0, 0.0, 0.0, 6.0, 0.0, 0.0, 0.0],
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[ 0.0, 7.0, 8.0, 0.0, 0.0, 0.0, 0.0, 9.0],
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[ 0.0, 0.0, 10.0, 0.0, 0.0, 0.0, 11.0, 12.0],
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[ 0.0, 13.0, 14.0, 0.0, 0.0, 0.0, 15.0, 16.0],
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[ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
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[ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 17.0, 0.0]
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]> : tensor<10x8xf64>
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//
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// Convert dense tensor to various sparse tensors.
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//
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%0 = sparse_tensor.convert %t : tensor<10x8xf64> to tensor<10x8xf64, #Dense>
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%1 = sparse_tensor.convert %t : tensor<10x8xf64> to tensor<10x8xf64, #CSR>
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%2 = sparse_tensor.convert %t : tensor<10x8xf64> to tensor<10x8xf64, #DCSR>
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%3 = sparse_tensor.convert %t : tensor<10x8xf64> to tensor<10x8xf64, #CSC>
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%4 = sparse_tensor.convert %t : tensor<10x8xf64> to tensor<10x8xf64, #DCSC>
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//
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// Inspect storage scheme of Dense.
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//
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// CHECK: ( 1, 0, 2, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0,
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// CHECK-SAME: 0, 0, 4, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0,
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// CHECK-SAME: 0, 0, 0, 0, 6, 0, 0, 0, 0, 7, 8, 0, 0, 0, 0, 9,
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// CHECK-SAME: 0, 0, 10, 0, 0, 0, 11, 12, 0, 13, 14, 0, 0, 0, 15, 16,
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// CHECK-SAME: 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 0 )
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//
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%5 = sparse_tensor.values %0 : tensor<10x8xf64, #Dense> to memref<?xf64>
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%6 = vector.transfer_read %5[%c0], %d0: memref<?xf64>, vector<80xf64>
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vector.print %6 : vector<80xf64>
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//
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// Inspect storage scheme of CSR.
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//
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// pointers(1)
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// indices(1)
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// values
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//
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// CHECK: ( 0, 3, 3, 4, 5, 6, 9, 12, 16, 16, 17 )
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// CHECK: ( 0, 2, 7, 2, 3, 4, 1, 2, 7, 2, 6, 7, 1, 2, 6, 7, 6 )
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// CHECK: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 )
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//
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%7 = sparse_tensor.pointers %1, %c1 : tensor<10x8xf64, #CSR> to memref<?xindex>
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%8 = vector.transfer_read %7[%c0], %c0: memref<?xindex>, vector<11xindex>
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vector.print %8 : vector<11xindex>
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%9 = sparse_tensor.indices %1, %c1 : tensor<10x8xf64, #CSR> to memref<?xindex>
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%10 = vector.transfer_read %9[%c0], %c0: memref<?xindex>, vector<17xindex>
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vector.print %10 : vector<17xindex>
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%11 = sparse_tensor.values %1 : tensor<10x8xf64, #CSR> to memref<?xf64>
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%12 = vector.transfer_read %11[%c0], %d0: memref<?xf64>, vector<17xf64>
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vector.print %12 : vector<17xf64>
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//
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// Inspect storage scheme of DCSR.
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//
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// pointers(0)
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// indices(0)
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// pointers(1)
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// indices(1)
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// values
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//
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// CHECK: ( 0, 8 )
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// CHECK: ( 0, 2, 3, 4, 5, 6, 7, 9 )
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// CHECK: ( 0, 3, 4, 5, 6, 9, 12, 16, 17 )
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// CHECK: ( 0, 2, 7, 2, 3, 4, 1, 2, 7, 2, 6, 7, 1, 2, 6, 7, 6 )
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// CHECK: ( 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 )
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//
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%13 = sparse_tensor.pointers %2, %c0 : tensor<10x8xf64, #DCSR> to memref<?xindex>
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%14 = vector.transfer_read %13[%c0], %c0: memref<?xindex>, vector<2xindex>
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vector.print %14 : vector<2xindex>
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%15 = sparse_tensor.indices %2, %c0 : tensor<10x8xf64, #DCSR> to memref<?xindex>
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%16 = vector.transfer_read %15[%c0], %c0: memref<?xindex>, vector<8xindex>
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vector.print %16 : vector<8xindex>
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%17 = sparse_tensor.pointers %2, %c1 : tensor<10x8xf64, #DCSR> to memref<?xindex>
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%18 = vector.transfer_read %17[%c0], %c0: memref<?xindex>, vector<9xindex>
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vector.print %18 : vector<9xindex>
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%19 = sparse_tensor.indices %2, %c1 : tensor<10x8xf64, #DCSR> to memref<?xindex>
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%20 = vector.transfer_read %19[%c0], %c0: memref<?xindex>, vector<17xindex>
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vector.print %20 : vector<17xindex>
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%21 = sparse_tensor.values %2 : tensor<10x8xf64, #DCSR> to memref<?xf64>
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%22 = vector.transfer_read %21[%c0], %d0: memref<?xf64>, vector<17xf64>
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vector.print %22 : vector<17xf64>
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//
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// Inspect storage scheme of CSC.
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//
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// pointers(1)
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// indices(1)
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// values
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//
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// CHECK: ( 0, 1, 3, 8, 9, 10, 10, 13, 17 )
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// CHECK: ( 0, 5, 7, 0, 2, 5, 6, 7, 3, 4, 6, 7, 9, 0, 5, 6, 7 )
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// CHECK: ( 1, 7, 13, 2, 4, 8, 10, 14, 5, 6, 11, 15, 17, 3, 9, 12, 16 )
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//
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%23 = sparse_tensor.pointers %3, %c1 : tensor<10x8xf64, #CSC> to memref<?xindex>
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%24 = vector.transfer_read %23[%c0], %c0: memref<?xindex>, vector<9xindex>
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vector.print %24 : vector<9xindex>
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%25 = sparse_tensor.indices %3, %c1 : tensor<10x8xf64, #CSC> to memref<?xindex>
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%26 = vector.transfer_read %25[%c0], %c0: memref<?xindex>, vector<17xindex>
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vector.print %26 : vector<17xindex>
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%27 = sparse_tensor.values %3 : tensor<10x8xf64, #CSC> to memref<?xf64>
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%28 = vector.transfer_read %27[%c0], %d0: memref<?xf64>, vector<17xf64>
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vector.print %28 : vector<17xf64>
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//
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// Inspect storage scheme of DCSC.
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//
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// pointers(0)
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// indices(0)
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// pointers(1)
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// indices(1)
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// values
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//
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// CHECK: ( 0, 7 )
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// CHECK: ( 0, 1, 2, 3, 4, 6, 7 )
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// CHECK: ( 0, 1, 3, 8, 9, 10, 13, 17 )
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// CHECK: ( 0, 5, 7, 0, 2, 5, 6, 7, 3, 4, 6, 7, 9, 0, 5, 6, 7 )
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// CHECK: ( 1, 7, 13, 2, 4, 8, 10, 14, 5, 6, 11, 15, 17, 3, 9, 12, 16 )
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//
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%29 = sparse_tensor.pointers %4, %c0 : tensor<10x8xf64, #DCSC> to memref<?xindex>
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%30 = vector.transfer_read %29[%c0], %c0: memref<?xindex>, vector<2xindex>
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vector.print %30 : vector<2xindex>
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%31 = sparse_tensor.indices %4, %c0 : tensor<10x8xf64, #DCSC> to memref<?xindex>
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%32 = vector.transfer_read %31[%c0], %c0: memref<?xindex>, vector<7xindex>
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vector.print %32 : vector<7xindex>
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%33 = sparse_tensor.pointers %4, %c1 : tensor<10x8xf64, #DCSC> to memref<?xindex>
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%34 = vector.transfer_read %33[%c0], %c0: memref<?xindex>, vector<8xindex>
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vector.print %34 : vector<8xindex>
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%35 = sparse_tensor.indices %4, %c1 : tensor<10x8xf64, #DCSC> to memref<?xindex>
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%36 = vector.transfer_read %35[%c0], %c0: memref<?xindex>, vector<17xindex>
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vector.print %36 : vector<17xindex>
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%37 = sparse_tensor.values %4 : tensor<10x8xf64, #DCSC> to memref<?xf64>
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%38 = vector.transfer_read %37[%c0], %d0: memref<?xf64>, vector<17xf64>
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vector.print %38 : vector<17xf64>
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return
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}
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}
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