f66e5769d4
This revision contains all "sparsification" ops and rewriting necessary to support sparse output tensors when the kernel has no reduction (viz. insertions occur in lexicographic order and are "injective"). This will be later generalized to allow reductions too. Also, this first revision only supports sparse 1-d tensors (viz. vectors) as output in the runtime support library. This will be generalized to n-d tensors shortly. But this way, the revision is kept to a manageable size. Reviewed By: bixia Differential Revision: https://reviews.llvm.org/D113705
36 lines
1.5 KiB
MLIR
36 lines
1.5 KiB
MLIR
// RUN: mlir-opt %s --canonicalize --cse | FileCheck %s
|
|
|
|
#SparseVector = #sparse_tensor.encoding<{dimLevelType = ["compressed"]}>
|
|
|
|
// CHECK-LABEL: func @sparse_nop_convert(
|
|
// CHECK-SAME: %[[A:.*]]: tensor<64xf32, #sparse_tensor.encoding<{{{.*}}}>>)
|
|
// CHECK-NOT: sparse_tensor.convert
|
|
// CHECK: return %[[A]] : tensor<64xf32, #sparse_tensor.encoding<{{{.*}}}>>
|
|
func @sparse_nop_convert(%arg0: tensor<64xf32, #SparseVector>) -> tensor<64xf32, #SparseVector> {
|
|
%0 = sparse_tensor.convert %arg0 : tensor<64xf32, #SparseVector> to tensor<64xf32, #SparseVector>
|
|
return %0 : tensor<64xf32, #SparseVector>
|
|
}
|
|
|
|
// CHECK-LABEL: func @sparse_dce_convert(
|
|
// CHECK-SAME: %[[A:.*]]: tensor<64xf32>)
|
|
// CHECK-NOT: sparse_tensor.convert
|
|
// CHECK: return
|
|
func @sparse_dce_convert(%arg0: tensor<64xf32>) {
|
|
%0 = sparse_tensor.convert %arg0 : tensor<64xf32> to tensor<64xf32, #SparseVector>
|
|
return
|
|
}
|
|
|
|
// CHECK-LABEL: func @sparse_dce_getters(
|
|
// CHECK-SAME: %[[A:.*]]: tensor<64xf32, #sparse_tensor.encoding<{{{.*}}}>>)
|
|
// CHECK-NOT: sparse_tensor.pointers
|
|
// CHECK-NOT: sparse_tensor.indices
|
|
// CHECK-NOT: sparse_tensor.values
|
|
// CHECK: return
|
|
func @sparse_dce_getters(%arg0: tensor<64xf32, #SparseVector>) {
|
|
%c = arith.constant 0 : index
|
|
%0 = sparse_tensor.pointers %arg0, %c : tensor<64xf32, #SparseVector> to memref<?xindex>
|
|
%1 = sparse_tensor.indices %arg0, %c : tensor<64xf32, #SparseVector> to memref<?xindex>
|
|
%2 = sparse_tensor.values %arg0 : tensor<64xf32, #SparseVector> to memref<?xf32>
|
|
return
|
|
}
|