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// RUN: mlir-opt %s --post-sparsification-rewrite="enable-runtime-library=false enable-convert=false" \
// RUN: --cse --canonicalize | FileCheck %s
#SparseMatrix = #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }>
// CHECK: func.func @sparse_reshape(
// CHECK-SAME: %[[S:.*]]:
// CHECK-DAG: %[[C25:.*]] = arith.constant 25 : index
// CHECK-DAG: %[[C10:.*]] = arith.constant 10 : index
// CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.*]] = arith.constant 1 : index
// CHECK: %[[B:.*]] = bufferization.alloc_tensor()
// CHECK: %[[P0:.*]] = sparse_tensor.positions %[[S]] {level = 0 : index}
// CHECK: %[[I0:.*]] = sparse_tensor.coordinates %[[S]] {level = 0 : index}
// CHECK: %[[P1:.*]] = sparse_tensor.positions %[[S]] {level = 1 : index}
// CHECK: %[[I1:.*]] = sparse_tensor.coordinates %[[S]] {level = 1 : index}
// CHECK: %[[V:.*]] = sparse_tensor.values %[[S]]
// CHECK: %[[S0:.*]] = memref.load %[[P0]]{{\[}}%[[C0]]] : memref<?xindex>
// CHECK: %[[E0:.*]] = memref.load %[[P0]]{{\[}}%[[C1]]] : memref<?xindex>
// CHECK: %[[RET:.*]] = scf.for %[[I:.*]] = %[[S0]] to %[[E0]] step %[[C1]] iter_args(%[[A0:.*]] = %[[B]])
// CHECK: %[[SI0:.*]] = memref.load %[[I0]]{{\[}}%[[I]]] : memref<?xindex>
// CHECK-DAG: %[[S1:.*]] = memref.load %[[P1]]{{\[}}%[[I]]] : memref<?xindex>
// CHECK-DAG: %[[PE1:.*]] = arith.addi %[[I]], %[[C1]] : index
// CHECK: %[[E1:.*]] = memref.load %[[P1]]{{\[}}%[[PE1]]] : memref<?xindex>
// CHECK: %[[RET_1:.*]] = scf.for %[[J:.*]] = %[[S1]] to %[[E1]] step %[[C1]] iter_args(%[[A1:.*]] = %[[A0]])
// CHECK: %[[SI1:.*]] = memref.load %[[I1]]{{\[}}%[[J]]] : memref<?xindex>
// CHECK: %[[SV:.*]] = memref.load %[[V]]{{\[}}%[[J]]] : memref<?xf64>
// CHECK: %[[T:.*]] = arith.muli %[[SI0]], %[[C25]] : index
// CHECK: %[[DI:.*]] = arith.addi %[[T]], %[[SI1]] : index
// CHECK: %[[D:.*]] = arith.divui %[[DI]], %[[C10]] : index
// CHECK: %[[R:.*]] = arith.remui %[[DI]], %[[C10]] : index
// CHECK: %[[R1:.*]] = sparse_tensor.insert %[[SV]] into %[[A1]]{{\[}}%[[D]], %[[R]]]
// CHECK: scf.yield %[[R1]]
// CHECK: }
// CHECK: scf.yield %[[RET_1]]
// CHECK: }
// CHECK: %[[NT1:.*]] = sparse_tensor.load %[[RET]] hasInserts
// CHECK: return %[[NT1]] : tensor<10x10xf64, #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed" ] }>>
//
func.func @sparse_reshape(%arg0: tensor<4x25xf64, #SparseMatrix>) -> tensor<10x10xf64, #SparseMatrix> {
%shape = arith.constant dense <[ 10, 10 ]> : tensor<2xi32>
%0 = tensor.reshape %arg0(%shape) :
(tensor<4x25xf64, #SparseMatrix>, tensor<2xi32>) -> tensor<10x10xf64, #SparseMatrix>
return %0 : tensor<10x10xf64, #SparseMatrix>
}
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