mirror of
https://github.com/intel/llvm.git
synced 2026-01-17 14:48:27 +08:00
a0615d020a
This commit is part of the migration of towards the new STEA syntax/design. In particular, this commit includes the following changes:
* Renaming compiler-internal functions/methods:
* `SparseTensorEncodingAttr::{getDimLevelType => getLvlTypes}`
* `Merger::{getDimLevelType => getLvlType}` (for consistency)
* `sparse_tensor::{getDimLevelType => buildLevelType}` (to help reduce confusion vs actual getter methods)
* Renaming external facets to match:
* the STEA parser and printer
* the C and Python bindings
* PyTACO
However, the actual renaming of the `DimLevelType` itself (along with all the "dlt" names) will be handled in a separate commit.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D150330
45 lines
3.0 KiB
MLIR
45 lines
3.0 KiB
MLIR
// RUN: mlir-opt %s --sparse-tensor-codegen --canonicalize --cse | FileCheck %s
|
|
|
|
#CSR = #sparse_tensor.encoding<{ lvlTypes = ["dense", "compressed"]}>
|
|
#COO = #sparse_tensor.encoding<{ lvlTypes = ["compressed-nu", "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>) -> ()
|
|
}
|