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
75 lines
3.9 KiB
MLIR
75 lines
3.9 KiB
MLIR
// RUN: mlir-opt %s -post-sparsification-rewrite="enable-runtime-library=false enable-convert=false" | \
|
|
// RUN: FileCheck %s
|
|
|
|
#CSR = #sparse_tensor.encoding<{
|
|
lvlTypes = ["dense", "compressed"]
|
|
}>
|
|
|
|
#CSC = #sparse_tensor.encoding<{
|
|
lvlTypes = [ "dense", "compressed" ],
|
|
dimOrdering = affine_map<(i, j) -> (j, i)>
|
|
}>
|
|
|
|
#COO = #sparse_tensor.encoding<{
|
|
lvlTypes = [ "compressed-nu", "singleton" ]
|
|
}>
|
|
|
|
// CHECK-LABEL: func.func @sparse_new(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>> {
|
|
// CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr<i8> to tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "compressed-nu", "singleton" ] }>>
|
|
// CHECK: %[[R:.*]] = sparse_tensor.convert %[[COO]]
|
|
// CHECK: bufferization.dealloc_tensor %[[COO]]
|
|
// CHECK: return %[[R]]
|
|
func.func @sparse_new(%arg0: !llvm.ptr<i8>) -> tensor<?x?xf32, #CSR> {
|
|
%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<?x?xf32, #CSR>
|
|
return %0 : tensor<?x?xf32, #CSR>
|
|
}
|
|
|
|
// CHECK-LABEL: func.func @sparse_new_csc(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ], dimOrdering = affine_map<(d0, d1) -> (d1, d0)> }>> {
|
|
// CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr<i8> to tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "compressed-nu", "singleton" ], dimOrdering = affine_map<(d0, d1) -> (d1, d0)> }>>
|
|
// CHECK: %[[R:.*]] = sparse_tensor.convert %[[COO]]
|
|
// CHECK: bufferization.dealloc_tensor %[[COO]]
|
|
// CHECK: return %[[R]]
|
|
func.func @sparse_new_csc(%arg0: !llvm.ptr<i8>) -> tensor<?x?xf32, #CSC> {
|
|
%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<?x?xf32, #CSC>
|
|
return %0 : tensor<?x?xf32, #CSC>
|
|
}
|
|
|
|
// CHECK-LABEL: func.func @sparse_new_coo(
|
|
// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "compressed-nu", "singleton" ] }>> {
|
|
// CHECK: %[[COO:.*]] = sparse_tensor.new %[[A]] : !llvm.ptr<i8> to tensor<?x?xf32, #sparse_tensor.encoding<{ lvlTypes = [ "compressed-nu", "singleton" ] }>>
|
|
// CHECK: return %[[COO]]
|
|
func.func @sparse_new_coo(%arg0: !llvm.ptr<i8>) -> tensor<?x?xf32, #COO> {
|
|
%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<?x?xf32, #COO>
|
|
return %0 : tensor<?x?xf32, #COO>
|
|
}
|
|
|
|
// CHECK-LABEL: func.func @sparse_out(
|
|
// CHECK-SAME: %[[A:.*]]: tensor<10x20xf32, #sparse_tensor.encoding<{ lvlTypes = [ "dense", "compressed" ] }>>,
|
|
// CHECK-SAME: %[[B:.*]]: !llvm.ptr<i8>) {
|
|
// 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<?xindex>
|
|
// CHECK: memref.store %[[C10]], %[[DS]]{{\[}}%[[C0]]] : memref<?xindex>
|
|
// CHECK: memref.store %[[C20]], %[[DS]]{{\[}}%[[C1]]] : memref<?xindex>
|
|
// CHECK: %[[W:.*]] = call @createSparseTensorWriter(%[[B]])
|
|
// CHECK: call @outSparseTensorWriterMetaData(%[[W]], %[[C2]], %[[NNZ]], %[[DS]])
|
|
// CHECK: %[[V:.*]] = memref.alloca() : memref<f32>
|
|
// 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<i8>) -> () {
|
|
sparse_tensor.out %arg0, %arg1 : tensor<10x20xf32, #CSR>, !llvm.ptr<i8>
|
|
return
|
|
}
|