9048ea28da
This reverts commit 5561e174117ff395d65b6978d04b62c1a1275138 The logic was moved from cmake into lit fixing the issue that lead to the revert and potentially others with multi-config cmake generators Differential Revision: https://reviews.llvm.org/D143925
117 lines
4.4 KiB
MLIR
117 lines
4.4 KiB
MLIR
// DEFINE: %{option} = enable-runtime-library=true
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// DEFINE: %{compile} = mlir-opt %s --sparse-compiler=%{option}
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// DEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/test.tns" \
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// DEFINE: mlir-cpu-runner \
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// DEFINE: -e entry -entry-point-result=void \
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// DEFINE: -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils | \
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// DEFINE: FileCheck %s
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//
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// RUN: %{compile} | %{run}
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//
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// Do the same run, but now with direct IR generation.
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// REDEFINE: %{option} = enable-runtime-library=false
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// RUN: %{compile} | %{run}
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//
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// Do the same run, but now with direct IR generation and vectorization.
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// REDEFINE: %{option} = "enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true"
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// RUN: %{compile} | %{run}
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// Do the same run, but now with direct IR generation and, if available, VLA
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// vectorization.
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// REDEFINE: %{option} = "enable-runtime-library=false vl=4 enable-arm-sve=%ENABLE_VLA"
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// REDEFINE: %{run} = TENSOR0="%mlir_src_dir/test/Integration/data/test.tns" \
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// REDEFINE: %lli \
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// REDEFINE: --entry-function=entry_lli \
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// REDEFINE: --extra-module=%S/Inputs/main_for_lli.ll \
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// REDEFINE: %VLA_ARCH_ATTR_OPTIONS \
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// REDEFINE: --dlopen=%mlir_native_utils_lib_dir/libmlir_c_runner_utils%shlibext --dlopen=%mlir_runner_utils | \
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// REDEFINE: FileCheck %s
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// RUN: %{compile} | mlir-translate -mlir-to-llvmir | %{run}
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!Filename = !llvm.ptr<i8>
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#SparseTensor = #sparse_tensor.encoding<{
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dimLevelType = [ "compressed", "compressed", "compressed", "compressed",
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"compressed", "compressed", "compressed", "compressed" ],
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// Note that any dimOrdering permutation should give the same results
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// since, even though it impacts the sparse storage scheme layout,
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// it should not change the semantics.
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dimOrdering = affine_map<(i,j,k,l,m,n,o,p) -> (p,o,j,k,i,l,m,n)>
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}>
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#trait_flatten = {
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indexing_maps = [
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affine_map<(i,j,k,l,m,n,o,p) -> (i,j,k,l,m,n,o,p)>, // A
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affine_map<(i,j,k,l,m,n,o,p) -> (i,j)> // X (out)
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],
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iterator_types = [ "parallel", "parallel", "reduction", "reduction",
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"reduction", "reduction", "reduction", "reduction" ],
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doc = "X(i,j) += A(i,j,k,l,m,n,o,p)"
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}
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//
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// Integration test that lowers a kernel annotated as sparse to
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// actual sparse code, initializes a matching sparse storage scheme
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// from file, and runs the resulting code with the JIT compiler.
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//
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module {
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//
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// A kernel that flattens a rank 8 tensor into a dense matrix.
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//
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func.func @kernel_flatten(%arga: tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor>,
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%argx: tensor<7x3xf64>)
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-> tensor<7x3xf64> {
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%0 = linalg.generic #trait_flatten
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ins(%arga: tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor>)
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outs(%argx: tensor<7x3xf64>) {
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^bb(%a: f64, %x: f64):
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%0 = arith.addf %x, %a : f64
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linalg.yield %0 : f64
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} -> tensor<7x3xf64>
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return %0 : tensor<7x3xf64>
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}
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func.func private @getTensorFilename(index) -> (!Filename)
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func.func private @printMemrefF64(%ptr : tensor<*xf64>)
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//
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// Main driver that reads tensor from file and calls the sparse kernel.
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//
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func.func @entry() {
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%d0 = arith.constant 0.0 : f64
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%c0 = arith.constant 0 : index
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%c1 = arith.constant 1 : index
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%c3 = arith.constant 3 : index
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%c7 = arith.constant 7 : index
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// Setup matrix memory that is initialized to zero.
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%x = arith.constant dense<0.000000e+00> : tensor<7x3xf64>
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// Read the sparse tensor from file, construct sparse storage.
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%fileName = call @getTensorFilename(%c0) : (index) -> (!Filename)
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%a = sparse_tensor.new %fileName : !Filename to tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor>
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// Call the kernel.
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%0 = call @kernel_flatten(%a, %x)
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: (tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor>, tensor<7x3xf64>) -> tensor<7x3xf64>
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// Print the result for verification.
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//
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// CHECK: {{\[}}[6.25, 0, 0],
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// CHECK-NEXT: [4.224, 6.21, 0],
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// CHECK-NEXT: [0, 0, 15.455],
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// CHECK-NEXT: [0, 0, 0],
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// CHECK-NEXT: [0, 0, 0],
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// CHECK-NEXT: [0, 0, 0],
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// CHECK-NEXT: [7, 0, 0]]
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//
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%1 = tensor.cast %0 : tensor<7x3xf64> to tensor<*xf64>
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call @printMemrefF64(%1) : (tensor<*xf64>) -> ()
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// Release the resources.
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bufferization.dealloc_tensor %a : tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor>
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return
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}
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}
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