eb177803bf
1. Remove the trailing comma for the last element of memref and add closing parenthesis. 2. Change integration tests to use the new format.
92 lines
3.6 KiB
MLIR
92 lines
3.6 KiB
MLIR
//--------------------------------------------------------------------------------------------------
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// WHEN CREATING A NEW TEST, PLEASE JUST COPY & PASTE WITHOUT EDITS.
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//
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// Set-up that's shared across all tests in this directory. In principle, this
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// config could be moved to lit.local.cfg. However, there are downstream users that
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// do not use these LIT config files. Hence why this is kept inline.
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//
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// DEFINE: %{sparsifier_opts} = enable-runtime-library=true
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// DEFINE: %{sparsifier_opts_sve} = enable-arm-sve=true %{sparsifier_opts}
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// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"
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// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"
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// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils
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// DEFINE: %{run_opts} = -e main -entry-point-result=void
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// DEFINE: %{run} = mlir-cpu-runner %{run_opts} %{run_libs}
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// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs}
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//
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// DEFINE: %{env} =
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//--------------------------------------------------------------------------------------------------
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// RUN: %{compile} | %{run} | FileCheck %s
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//
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// Do the same run, but now with direct IR generation.
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// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false
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// RUN: %{compile} | %{run} | FileCheck %s
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//
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// Do the same run, but now with vectorization.
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// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true
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// RUN: %{compile} | %{run} | FileCheck %s
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//
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// Do the same run, but now with VLA vectorization.
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// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | %{run_sve} | FileCheck %s %}
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// Current fails for SVE, see https://github.com/llvm/llvm-project/issues/60626
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// UNSUPPORTED: target=aarch64{{.*}}
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#SparseVector = #sparse_tensor.encoding<{ map = (d0) -> (d0 : compressed) }>
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#trait_op = {
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indexing_maps = [
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affine_map<(i) -> (i)> // X (out)
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],
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iterator_types = ["parallel"],
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doc = "X(i) = OP X(i)"
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}
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module {
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// Performs zero-preserving math to sparse vector.
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func.func @sparse_tanh(%vec: tensor<?xf64, #SparseVector>)
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-> tensor<?xf64, #SparseVector> {
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%0 = linalg.generic #trait_op
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outs(%vec: tensor<?xf64, #SparseVector>) {
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^bb(%x: f64):
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%1 = math.tanh %x : f64
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linalg.yield %1 : f64
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} -> tensor<?xf64, #SparseVector>
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return %0 : tensor<?xf64, #SparseVector>
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}
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// Driver method to call and verify vector kernels.
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func.func @main() {
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// Setup sparse vector.
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%v1 = arith.constant sparse<
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[ [0], [3], [11], [17], [20], [21], [28], [29], [31] ],
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[ -1.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 100.0 ]
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> : tensor<32xf64>
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%sv1 = sparse_tensor.convert %v1
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: tensor<32xf64> to tensor<?xf64, #SparseVector>
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// Call sparse vector kernel.
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%0 = call @sparse_tanh(%sv1) : (tensor<?xf64, #SparseVector>)
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-> tensor<?xf64, #SparseVector>
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//
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// Verify the results (within some precision).
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//
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// CHECK: ---- Sparse Tensor ----
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// CHECK-NEXT: nse = 9
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// CHECK-NEXT: dim = ( 32 )
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// CHECK-NEXT: lvl = ( 32 )
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// CHECK-NEXT: pos[0] : ( 0, 9 )
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// CHECK-NEXT: crd[0] : ( 0, 3, 11, 17, 20, 21, 28, 29, 31 )
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// CHECK-NEXT: values : ({{ -0.761[0-9]*, 0.761[0-9]*, 0.96[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 1}} )
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// CHECK-NEXT: ----
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//
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sparse_tensor.print %0 : tensor<?xf64, #SparseVector>
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// Release the resources.
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bufferization.dealloc_tensor %sv1 : tensor<?xf64, #SparseVector>
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return
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}
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}
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