| // RUN: mlir-opt %s --sparse-tensor-codegen --canonicalize --cse | FileCheck %s |
| |
| #CSR = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed)}> |
| #COO = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton)}> |
| |
| // CHECK-LABEL: func.func @sparse_alloc_copy_CSR( |
| // CHECK-SAME: %[[VAL_0:.*0]]: memref<?xindex>, |
| // CHECK-SAME: %[[VAL_1:.*1]]: memref<?xindex>, |
| // CHECK-SAME: %[[VAL_2:.*2]]: memref<?xf32>, |
| // CHECK-SAME: %[[VAL_3:.*]]: !sparse_tensor.storage_specifier<#{{.*}}>) -> (memref<?xindex>, memref<?xindex>, memref<?xf32>, !sparse_tensor.storage_specifier<#{{.*}}>) { |
| // CHECK: %[[VAL_4:.*]] = arith.constant 0 : index |
| // CHECK: %[[VAL_5:.*]] = memref.dim %[[VAL_0]], %[[VAL_4]] : memref<?xindex> |
| // CHECK: %[[VAL_6:.*]] = memref.alloc(%[[VAL_5]]) : memref<?xindex> |
| // CHECK: memref.copy %[[VAL_0]], %[[VAL_6]] : memref<?xindex> to memref<?xindex> |
| // CHECK: %[[VAL_7:.*]] = memref.dim %[[VAL_1]], %[[VAL_4]] : memref<?xindex> |
| // CHECK: %[[VAL_8:.*]] = memref.alloc(%[[VAL_7]]) : memref<?xindex> |
| // CHECK: memref.copy %[[VAL_1]], %[[VAL_8]] : memref<?xindex> to memref<?xindex> |
| // CHECK: %[[VAL_9:.*]] = memref.dim %[[VAL_2]], %[[VAL_4]] : memref<?xf32> |
| // CHECK: %[[VAL_10:.*]] = memref.alloc(%[[VAL_9]]) : memref<?xf32> |
| // CHECK: memref.copy %[[VAL_2]], %[[VAL_10]] : memref<?xf32> to memref<?xf32> |
| func.func @sparse_alloc_copy_CSR(%arg0: tensor<2x2xf32, #CSR>) -> tensor<2x2xf32, #CSR> { |
| %0 = bufferization.alloc_tensor() copy(%arg0) : tensor<2x2xf32, #CSR> |
| "test.sink"(%0) : (tensor<2x2xf32, #CSR>) -> () |
| } |
| |
| // CHECK-LABEL: func.func @sparse_alloc_copy_COO( |
| // CHECK-SAME: %[[VAL_0:.*0]]: memref<?xindex>, |
| // CHECK-SAME: %[[VAL_1:.*1]]: memref<?xindex>, |
| // CHECK-SAME: %[[VAL_2:.*2]]: memref<?xf32>, |
| // CHECK-SAME: %[[VAL_3:.*]]: !sparse_tensor.storage_specifier<#{{.*}}>) -> (memref<?xindex>, memref<?xindex>, memref<?xf32>, !sparse_tensor.storage_specifier<#{{.*}}>) { |
| // CHECK: %[[VAL_4:.*]] = arith.constant 0 : index |
| // CHECK: %[[VAL_5:.*]] = memref.dim %[[VAL_0]], %[[VAL_4]] : memref<?xindex> |
| // CHECK: %[[VAL_6:.*]] = memref.alloc(%[[VAL_5]]) : memref<?xindex> |
| // CHECK: memref.copy %[[VAL_0]], %[[VAL_6]] : memref<?xindex> to memref<?xindex> |
| // CHECK: %[[VAL_7:.*]] = memref.dim %[[VAL_1]], %[[VAL_4]] : memref<?xindex> |
| // CHECK: %[[VAL_8:.*]] = memref.alloc(%[[VAL_7]]) : memref<?xindex> |
| // CHECK: memref.copy %[[VAL_1]], %[[VAL_8]] : memref<?xindex> to memref<?xindex> |
| // CHECK: %[[VAL_9:.*]] = memref.dim %[[VAL_2]], %[[VAL_4]] : memref<?xf32> |
| // CHECK: %[[VAL_10:.*]] = memref.alloc(%[[VAL_9]]) : memref<?xf32> |
| // CHECK: memref.copy %[[VAL_2]], %[[VAL_10]] : memref<?xf32> to memref<?xf32> |
| func.func @sparse_alloc_copy_COO(%arg0: tensor<2x2xf32, #COO>) -> tensor<2x2xf32, #COO> { |
| %0 = bufferization.alloc_tensor() copy(%arg0) : tensor<2x2xf32, #COO> |
| "test.sink"(%0) : (tensor<2x2xf32, #COO>) -> () |
| } |
