28 lines
1.1 KiB
MLIR
28 lines
1.1 KiB
MLIR
// RUN: mlir-opt %s --post-sparsification-rewrite="enable-runtime-library=false" \
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// RUN: --sparse-tensor-codegen=create-sparse-deallocs=false \
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// RUN: --canonicalize --cse | FileCheck %s -check-prefix=CHECK-NO-DEALLOC
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// RUN: mlir-opt %s --post-sparsification-rewrite="enable-runtime-library=false" \
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// RUN: --sparse-tensor-codegen=create-sparse-deallocs=true \
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// RUN: --canonicalize --cse | FileCheck %s -check-prefix=CHECK-DEALLOC
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#CSR = #sparse_tensor.encoding<{ dimLevelType = ["dense", "compressed"]}>
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#CSC = #sparse_tensor.encoding<{
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dimLevelType = ["dense", "compressed"],
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dimOrdering = affine_map<(i,j) -> (j,i)>
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}>
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//
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// No memref.dealloc is user-requested so
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// CHECK-NO-DEALLOC-LABEL: @sparse_convert_permuted
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// CHECK-NO-DEALLOC-NOT: memref.dealloc
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//
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// Otherwise memref.dealloc is created to free temporary sparse buffers.
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// CHECK-DEALLOC-LABEL: @sparse_convert_permuted
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// CHECK-DEALLOC: memref.dealloc
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//
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func.func @sparse_convert_permuted(%arg0: tensor<?x?xf32, #CSR>) -> tensor<?x?xf32, #CSC> {
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%0 = sparse_tensor.convert %arg0 : tensor<?x?xf32, #CSR> to tensor<?x?xf32, #CSC>
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return %0 : tensor<?x?xf32, #CSC>
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}
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