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1//--------------------------------------------------------------------------------------------------2// WHEN CREATING A NEW TEST, PLEASE JUST COPY & PASTE WITHOUT EDITS.3//4// Set-up that's shared across all tests in this directory. In principle, this5// config could be moved to lit.local.cfg. However, there are downstream users that6// do not use these LIT config files. Hence why this is kept inline.7//8// DEFINE: %{sparsifier_opts} = enable-runtime-library=true9// DEFINE: %{sparsifier_opts_sve} = enable-arm-sve=true %{sparsifier_opts}10// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"11// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"12// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils13// DEFINE: %{run_libs_sve} = -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils14// DEFINE: %{run_opts} = -e main -entry-point-result=void15// DEFINE: %{run} = mlir-runner %{run_opts} %{run_libs}16// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs_sve}17//18// DEFINE: %{env} =19//--------------------------------------------------------------------------------------------------20 21// RUN: %{compile} | %{run} | FileCheck %s22 23//24// Integration test that generates a tensor with specified sparsity level.25//26 27!Generator = !llvm.ptr28!Array = !llvm.ptr29 30#SparseVector = #sparse_tensor.encoding<{31 map = (d0) -> (d0 : compressed)32}>33 34module {35 func.func private @rtsrand(index) -> (!Generator)36 func.func private @rtrand(!Generator, index) -> (index)37 func.func private @rtdrand(!Generator) -> ()38 func.func private @shuffle(memref<?xi64>, !Generator) -> () attributes { llvm.emit_c_interface }39 40 //41 // Main driver.42 //43 func.func @main() {44 %c0 = arith.constant 0 : index45 %c1 = arith.constant 1 : index46 %f0 = arith.constant 0.0 : f6447 %c99 = arith.constant 99 : index48 %c100 = arith.constant 100 : index49 50 // Set up input size and sparsity level.51 %size = arith.constant 50 : index52 %sparsity = arith.constant 90 : index53 %zeros = arith.muli %size, %sparsity : index54 %nz = arith.floordivsi %zeros, %c100 : index55 %nse = arith.subi %size, %nz : index56 57 // Set up an empty vector.58 %empty = tensor.empty(%size) : tensor<?xf64>59 %zero_vec = linalg.fill ins(%f0 : f64) outs(%empty : tensor<?xf64>) -> tensor<?xf64>60 61 // Generate shuffled indices in the range of [0, %size).62 %array = memref.alloc (%size) : memref<?xi64>63 %g = func.call @rtsrand(%c0) : (index) ->(!Generator)64 func.call @shuffle(%array, %g) : (memref<?xi64>, !Generator) -> ()65 66 // Iterate through the number of nse indices to insert values.67 %output = scf.for %iv = %c0 to %nse step %c1 iter_args(%iter = %zero_vec) -> tensor<?xf64> {68 // Fetch the index to insert value from shuffled index array.69 %val = memref.load %array[%iv] : memref<?xi64>70 %idx = arith.index_cast %val : i64 to index71 // Generate a random number from 1 to 100.72 %ri0 = func.call @rtrand(%g, %c99) : (!Generator, index) -> (index)73 %ri1 = arith.addi %ri0, %c1 : index74 %r0 = arith.index_cast %ri1 : index to i6475 %fr = arith.uitofp %r0 : i64 to f6476 // Insert the random number to current index.77 %out = tensor.insert %fr into %iter[%idx] : tensor<?xf64>78 scf.yield %out : tensor<?xf64>79 }80 81 %sv = sparse_tensor.convert %output : tensor<?xf64> to tensor<?xf64, #SparseVector>82 %n0 = sparse_tensor.number_of_entries %sv : tensor<?xf64, #SparseVector>83 84 // Print the number of non-zeros for verification85 // as shuffle may generate different numbers.86 //87 // CHECK: 588 vector.print %n0 : index89 90 // Release the resources.91 bufferization.dealloc_tensor %sv : tensor<?xf64, #SparseVector>92 bufferization.dealloc_tensor %empty : tensor<?xf64>93 memref.dealloc %array : memref<?xi64>94 func.call @rtdrand(%g) : (!Generator) -> ()95 96 return97 }98}99