// RUN: mlir-opt %s --lower-sparse-ops-to-foreach="enable-runtime-library=false enable-convert=false" \ // RUN: --lower-sparse-foreach-to-scf | FileCheck %s #CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }> #CSC = #sparse_tensor.encoding<{ map = (d0, d1) -> (d1 : dense, d0 : compressed) }> #COO = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton) }> // CHECK-LABEL: func.func @sparse_new( // CHECK-SAME: %[[A:.*]]: !llvm.ptr) -> tensor { // CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr to tensor // CHECK: %[[R:.*]] = sparse_tensor.convert %[[COO]] // CHECK: bufferization.dealloc_tensor %[[COO]] // CHECK: return %[[R]] func.func @sparse_new(%arg0: !llvm.ptr) -> tensor { %0 = sparse_tensor.new %arg0 : !llvm.ptr to tensor return %0 : tensor } // CHECK-LABEL: func.func @sparse_new_csc( // CHECK-SAME: %[[A:.*]]: !llvm.ptr) -> tensor { // CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr to tensor // CHECK: %[[R:.*]] = sparse_tensor.convert %[[COO]] // CHECK: bufferization.dealloc_tensor %[[COO]] // CHECK: return %[[R]] func.func @sparse_new_csc(%arg0: !llvm.ptr) -> tensor { %0 = sparse_tensor.new %arg0 : !llvm.ptr to tensor return %0 : tensor } // CHECK-LABEL: func.func @sparse_new_coo( // CHECK-SAME: %[[A:.*]]: !llvm.ptr) -> tensor { // CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr to tensor // CHECK: return %[[COO]] func.func @sparse_new_coo(%arg0: !llvm.ptr) -> tensor { %0 = sparse_tensor.new %arg0 : !llvm.ptr to tensor return %0 : tensor } // CHECK-LABEL: func.func @sparse_out( // CHECK-SAME: %[[A:.*]]: tensor<10x20xf32, #sparse{{[0-9]*}}>, // CHECK-SAME: %[[B:.*]]: !llvm.ptr) { // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index // CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index // CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index // CHECK-DAG: %[[C10:.*]] = arith.constant 10 : index // CHECK-DAG: %[[C20:.*]] = arith.constant 20 : index // CHECK: %[[NNZ:.*]] = sparse_tensor.number_of_entries %[[A]] // CHECK: %[[DS:.*]] = memref.alloca(%[[C2]]) : memref // CHECK: memref.store %[[C10]], %[[DS]]{{\[}}%[[C0]]] : memref // CHECK: memref.store %[[C20]], %[[DS]]{{\[}}%[[C1]]] : memref // CHECK: %[[W:.*]] = call @createSparseTensorWriter(%[[B]]) // CHECK: call @outSparseTensorWriterMetaData(%[[W]], %[[C2]], %[[NNZ]], %[[DS]]) // CHECK: %[[V:.*]] = memref.alloca() : memref // CHECK: scf.for %{{.*}} = %[[C0]] to %[[C10]] step %[[C1]] { // CHECK: scf.for {{.*}} { // CHECK: func.call @outSparseTensorWriterNextF32(%[[W]], %[[C2]], %[[DS]], %[[V]]) // CHECK: } // CHECK: } // CHECK: call @delSparseTensorWriter(%[[W]]) // CHECK: return // CHECK: } func.func @sparse_out( %arg0: tensor<10x20xf32, #CSR>, %arg1: !llvm.ptr) -> () { sparse_tensor.out %arg0, %arg1 : tensor<10x20xf32, #CSR>, !llvm.ptr return }