e445349d2c
Also fix the rewrite rule for sparse_tensor.new to reflect the recent change of the runtime C interface and to use utilities for memref.alloca. Reviewed By: aartbik Differential Revision: https://reviews.llvm.org/D135891
64 lines
3.3 KiB
MLIR
64 lines
3.3 KiB
MLIR
// RUN: mlir-opt %s -sparse-tensor-rewrite=enable-runtime-library=false | FileCheck %s
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#CSR = #sparse_tensor.encoding<{
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dimLevelType = ["dense", "compressed"]
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}>
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// CHECK-LABEL: func.func @sparse_new(
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// CHECK-SAME: %[[A:.*]]: !llvm.ptr<i8>) -> tensor<?x?xf32, #sparse_tensor.encoding<{ dimLevelType = [ "dense", "compressed" ] }>> {
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// CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index
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// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
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// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
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// CHECK: %[[R:.*]] = call @createSparseTensorReader(%[[A]])
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// CHECK: %[[DS:.*]] = memref.alloca(%[[C2]]) : memref<?xindex>
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// CHECK: call @getSparseTensorReaderDimSizes(%[[R]], %[[DS]])
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// CHECK: %[[D0:.*]] = memref.load %[[DS]]{{\[}}%[[C0]]]
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// CHECK: %[[D1:.*]] = memref.load %[[DS]]{{\[}}%[[C1]]]
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// CHECK: %[[T:.*]] = bufferization.alloc_tensor(%[[D0]], %[[D1]])
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// CHECK: %[[N:.*]] = call @getSparseTensorReaderNNZ(%[[R]])
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// CHECK: %[[VB:.*]] = memref.alloca()
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// CHECK: scf.for %{{.*}} = %[[C0]] to %[[N]] step %[[C1]] {
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// CHECK: func.call @getSparseTensorReaderNextF32(%[[R]], %[[DS]], %[[VB]])
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// CHECK: %[[E0:.*]] = memref.load %[[DS]]{{\[}}%[[C0]]]
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// CHECK: %[[E1:.*]] = memref.load %[[DS]]{{\[}}%[[C1]]]
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// CHECK: %[[V:.*]] = memref.load %[[VB]][]
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// CHECK: sparse_tensor.insert %[[V]] into %[[T]]{{\[}}%[[E0]], %[[E1]]]
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// CHECK: }
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// CHECK: call @delSparseTensorReader(%[[R]])
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// CHECK: %[[R:.*]] = sparse_tensor.convert %[[T]]
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// CHECK: bufferization.dealloc_tensor %[[T]]
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// CHECK: return %[[R]]
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// CHECK: }
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func.func @sparse_new(%arg0: !llvm.ptr<i8>) -> tensor<?x?xf32, #CSR> {
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%0 = sparse_tensor.new %arg0 : !llvm.ptr<i8> to tensor<?x?xf32, #CSR>
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return %0 : tensor<?x?xf32, #CSR>
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}
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// CHECK-LABEL: func.func @sparse_out(
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// CHECK-SAME: %[[A:.*]]: tensor<10x20xf32, #sparse_tensor.encoding<{ dimLevelType = [ "dense", "compressed" ] }>>,
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// CHECK-SAME: %[[B:.*]]: !llvm.ptr<i8>) {
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// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
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// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
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// CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index
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// CHECK-DAG: %[[C10:.*]] = arith.constant 10 : index
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// CHECK-DAG: %[[C20:.*]] = arith.constant 20 : index
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// CHECK: %[[NNZ:.*]] = sparse_tensor.number_of_entries %[[A]]
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// CHECK: %[[DS:.*]] = memref.alloca(%[[C2]]) : memref<?xindex>
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// CHECK: memref.store %[[C10]], %[[DS]]{{\[}}%[[C0]]] : memref<?xindex>
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// CHECK: memref.store %[[C20]], %[[DS]]{{\[}}%[[C1]]] : memref<?xindex>
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// CHECK: %[[W:.*]] = call @createSparseTensorWriter(%[[B]])
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// CHECK: call @outSparseTensorWriterMetaData(%[[W]], %[[C2]], %[[NNZ]], %[[DS]])
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// CHECK: %[[V:.*]] = memref.alloca() : memref<f32>
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// CHECK: scf.for %{{.*}} = %[[C0]] to %[[C10]] step %[[C1]] {
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// CHECK: scf.for {{.*}} {
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// CHECK: func.call @outSparseTensorWriterNextF32(%[[W]], %[[C2]], %[[DS]], %[[V]])
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// CHECK: }
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// CHECK: }
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// CHECK: call @delSparseTensorWriter(%[[W]])
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// CHECK: return
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// CHECK: }
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func.func @sparse_out( %arg0: tensor<10x20xf32, #CSR>, %arg1: !llvm.ptr<i8>) -> () {
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sparse_tensor.out %arg0, %arg1 : tensor<10x20xf32, #CSR>, !llvm.ptr<i8>
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return
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}
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