| // RUN: mlir-opt %s --sparse-tensor-codegen --cse | FileCheck %s |
| |
| #CSR = #sparse_tensor.encoding<{ |
| map = (d0, d1) -> (d0 : dense, d1 : compressed) |
| }> |
| |
| #CSR_SLICE = #sparse_tensor.encoding<{ |
| map = (d0 : #sparse_tensor<slice(0, 4, 1)>, d1 : #sparse_tensor<slice(0, 8, 1)>) -> (d0 : dense, d1 : compressed) |
| }> |
| |
| // CHECK-LABEL: func.func @sparse_slice( |
| // CHECK-SAME: %[[VAL_0:.*0]]: memref<?xindex>, |
| // CHECK-SAME: %[[VAL_1:.*1]]: memref<?xindex>, |
| // CHECK-SAME: %[[VAL_2:.*2]]: memref<?xf64>, |
| // CHECK-SAME: %[[VAL_3:.*3]]: !sparse_tensor.storage_specifier<#sparse{{[0-9]*}}>) |
| // CHECK: %[[VAL_4:.*]] = sparse_tensor.storage_specifier.init with %[[VAL_3]] |
| // CHECK: %[[VAL_5:.*]] = arith.constant 0 : index |
| // CHECK: %[[VAL_6:.*]] = arith.constant 4 : index |
| // CHECK: %[[VAL_7:.*]] = arith.constant 1 : index |
| // CHECK: %[[VAL_8:.*]] = sparse_tensor.storage_specifier.set %[[VAL_4]] dim_offset at 0 with %[[VAL_5]] |
| // CHECK: %[[VAL_9:.*]] = sparse_tensor.storage_specifier.set %[[VAL_8]] lvl_sz at 0 with %[[VAL_6]] |
| // CHECK: %[[VAL_10:.*]] = sparse_tensor.storage_specifier.set %[[VAL_9]] dim_stride at 0 with %[[VAL_7]] |
| // CHECK: %[[VAL_11:.*]] = arith.constant 8 : index |
| // CHECK: %[[VAL_12:.*]] = sparse_tensor.storage_specifier.set %[[VAL_10]] dim_offset at 1 with %[[VAL_5]] |
| // CHECK: %[[VAL_13:.*]] = sparse_tensor.storage_specifier.set %[[VAL_12]] lvl_sz at 1 with %[[VAL_11]] |
| // CHECK: %[[VAL_14:.*]] = sparse_tensor.storage_specifier.set %[[VAL_13]] dim_stride at 1 with %[[VAL_7]] |
| // CHECK: return %[[VAL_0]], %[[VAL_1]], %[[VAL_2]], %[[VAL_14]] |
| func.func @sparse_slice(%t1 : tensor<8x8xf64, #CSR>) -> tensor<4x8xf64, #CSR_SLICE> { |
| %a1 = tensor.extract_slice %t1[0, 0][4, 8][1, 1] : tensor<8x8xf64, #CSR> to |
| tensor<4x8xf64, #CSR_SLICE> |
| return %a1 : tensor<4x8xf64, #CSR_SLICE> |
| } |
