1// RUN: mlir-opt %s --sparse-tensor-codegen --canonicalize --cse | FileCheck %s 2 3#CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed)}> 4#COO = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)}> 5 6// CHECK-LABEL: func.func @sparse_alloc_copy_CSR( 7// CHECK-SAME: %[[VAL_0:.*0]]: memref<?xindex>, 8// CHECK-SAME: %[[VAL_1:.*1]]: memref<?xindex>, 9// CHECK-SAME: %[[VAL_2:.*2]]: memref<?xf32>, 10// CHECK-SAME: %[[VAL_3:.*]]: !sparse_tensor.storage_specifier<#{{.*}}>) -> (memref<?xindex>, memref<?xindex>, memref<?xf32>, !sparse_tensor.storage_specifier<#{{.*}}>) { 11// CHECK: %[[VAL_4:.*]] = arith.constant 0 : index 12// CHECK: %[[VAL_5:.*]] = memref.dim %[[VAL_0]], %[[VAL_4]] : memref<?xindex> 13// CHECK: %[[VAL_6:.*]] = memref.alloc(%[[VAL_5]]) : memref<?xindex> 14// CHECK: memref.copy %[[VAL_0]], %[[VAL_6]] : memref<?xindex> to memref<?xindex> 15// CHECK: %[[VAL_7:.*]] = memref.dim %[[VAL_1]], %[[VAL_4]] : memref<?xindex> 16// CHECK: %[[VAL_8:.*]] = memref.alloc(%[[VAL_7]]) : memref<?xindex> 17// CHECK: memref.copy %[[VAL_1]], %[[VAL_8]] : memref<?xindex> to memref<?xindex> 18// CHECK: %[[VAL_9:.*]] = memref.dim %[[VAL_2]], %[[VAL_4]] : memref<?xf32> 19// CHECK: %[[VAL_10:.*]] = memref.alloc(%[[VAL_9]]) : memref<?xf32> 20// CHECK: memref.copy %[[VAL_2]], %[[VAL_10]] : memref<?xf32> to memref<?xf32> 21func.func @sparse_alloc_copy_CSR(%arg0: tensor<2x2xf32, #CSR>) -> tensor<2x2xf32, #CSR> { 22 %0 = bufferization.alloc_tensor() copy(%arg0) : tensor<2x2xf32, #CSR> 23 "test.sink"(%0) : (tensor<2x2xf32, #CSR>) -> () 24} 25 26// CHECK-LABEL: func.func @sparse_alloc_copy_COO( 27// CHECK-SAME: %[[VAL_0:.*0]]: memref<?xindex>, 28// CHECK-SAME: %[[VAL_1:.*1]]: memref<?xindex>, 29// CHECK-SAME: %[[VAL_2:.*2]]: memref<?xf32>, 30// CHECK-SAME: %[[VAL_3:.*]]: !sparse_tensor.storage_specifier<#{{.*}}>) -> (memref<?xindex>, memref<?xindex>, memref<?xf32>, !sparse_tensor.storage_specifier<#{{.*}}>) { 31// CHECK: %[[VAL_4:.*]] = arith.constant 0 : index 32// CHECK: %[[VAL_5:.*]] = memref.dim %[[VAL_0]], %[[VAL_4]] : memref<?xindex> 33// CHECK: %[[VAL_6:.*]] = memref.alloc(%[[VAL_5]]) : memref<?xindex> 34// CHECK: memref.copy %[[VAL_0]], %[[VAL_6]] : memref<?xindex> to memref<?xindex> 35// CHECK: %[[VAL_7:.*]] = memref.dim %[[VAL_1]], %[[VAL_4]] : memref<?xindex> 36// CHECK: %[[VAL_8:.*]] = memref.alloc(%[[VAL_7]]) : memref<?xindex> 37// CHECK: memref.copy %[[VAL_1]], %[[VAL_8]] : memref<?xindex> to memref<?xindex> 38// CHECK: %[[VAL_9:.*]] = memref.dim %[[VAL_2]], %[[VAL_4]] : memref<?xf32> 39// CHECK: %[[VAL_10:.*]] = memref.alloc(%[[VAL_9]]) : memref<?xf32> 40// CHECK: memref.copy %[[VAL_2]], %[[VAL_10]] : memref<?xf32> to memref<?xf32> 41func.func @sparse_alloc_copy_COO(%arg0: tensor<2x2xf32, #COO>) -> tensor<2x2xf32, #COO> { 42 %0 = bufferization.alloc_tensor() copy(%arg0) : tensor<2x2xf32, #COO> 43 "test.sink"(%0) : (tensor<2x2xf32, #COO>) -> () 44} 45