llvm-project/mlir/test/Dialect/SparseTensor/fold.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.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.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.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
}