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
65 lines
2.8 KiB
MLIR
65 lines
2.8 KiB
MLIR
// RUN: mlir-opt %s --canonicalize --cse | FileCheck %s
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#SparseVector = #sparse_tensor.encoding<{lvlTypes = ["compressed"]}>
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// CHECK-LABEL: func @sparse_nop_dense2dense_convert(
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// CHECK-SAME: %[[A:.*]]: tensor<64xf32>)
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// CHECK-NOT: sparse_tensor.convert
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// CHECK: return %[[A]] : tensor<64xf32>
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func.func @sparse_nop_dense2dense_convert(%arg0: tensor<64xf32>) -> tensor<64xf32> {
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%0 = sparse_tensor.convert %arg0 : tensor<64xf32> to tensor<64xf32>
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return %0 : tensor<64xf32>
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}
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// CHECK-LABEL: func @sparse_dce_convert(
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// CHECK-SAME: %[[A:.*]]: tensor<64xf32>)
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// CHECK-NOT: sparse_tensor.convert
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// CHECK: return
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func.func @sparse_dce_convert(%arg0: tensor<64xf32>) {
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%0 = sparse_tensor.convert %arg0 : tensor<64xf32> to tensor<64xf32, #SparseVector>
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return
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}
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// CHECK-LABEL: func @sparse_dce_getters(
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// CHECK-SAME: %[[A:.*]]: tensor<64xf32, #sparse_tensor.encoding<{{{.*}}}>>)
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// CHECK-NOT: sparse_tensor.positions
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// CHECK-NOT: sparse_tensor.coordinates
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// CHECK-NOT: sparse_tensor.values
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// CHECK: return
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func.func @sparse_dce_getters(%arg0: tensor<64xf32, #SparseVector>) {
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%0 = sparse_tensor.positions %arg0 { level = 0 : index } : tensor<64xf32, #SparseVector> to memref<?xindex>
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%1 = sparse_tensor.coordinates %arg0 { level = 0 : index } : tensor<64xf32, #SparseVector> to memref<?xindex>
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%2 = sparse_tensor.values %arg0 : tensor<64xf32, #SparseVector> to memref<?xf32>
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return
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}
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// CHECK-LABEL: func @sparse_concat_dce(
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// CHECK-NOT: sparse_tensor.concatenate
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// CHECK: return
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func.func @sparse_concat_dce(%arg0: tensor<2xf64, #SparseVector>,
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%arg1: tensor<3xf64, #SparseVector>,
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%arg2: tensor<4xf64, #SparseVector>) {
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%0 = sparse_tensor.concatenate %arg0, %arg1, %arg2 {dimension = 0 : index}
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: tensor<2xf64, #SparseVector>,
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tensor<3xf64, #SparseVector>,
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tensor<4xf64, #SparseVector> to tensor<9xf64, #SparseVector>
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return
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}
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// CHECK-LABEL: func @sparse_get_specifier_dce_fold(
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// CHECK-SAME: %[[A0:.*]]: !sparse_tensor.storage_specifier
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// CHECK-SAME: %[[A1:.*]]: index,
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// CHECK-SAME: %[[A2:.*]]: index)
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// CHECK-NOT: sparse_tensor.storage_specifier.set
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// CHECK-NOT: sparse_tensor.storage_specifier.get
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// CHECK: return %[[A1]]
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func.func @sparse_get_specifier_dce_fold(%arg0: !sparse_tensor.storage_specifier<#SparseVector>, %arg1: index, %arg2: index) -> index {
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%0 = sparse_tensor.storage_specifier.set %arg0 lvl_sz at 0 with %arg1
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: !sparse_tensor.storage_specifier<#SparseVector>
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%1 = sparse_tensor.storage_specifier.set %0 pos_mem_sz at 0 with %arg2
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: !sparse_tensor.storage_specifier<#SparseVector>
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%2 = sparse_tensor.storage_specifier.get %1 lvl_sz at 0
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: !sparse_tensor.storage_specifier<#SparseVector>
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return %2 : index
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}
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