| // RUN: mlir-opt %s --sparse-assembler -split-input-file | FileCheck %s | |
| // ----- | |
| // CHECK-LABEL: func.func @nop( | |
| // CHECK-SAME: %[[A:.*]]: tensor<100xf32>) -> tensor<100xf32> { | |
| // CHECK: return %[[A]] : tensor<100xf32> | |
| // CHECK: } | |
| func.func @nop(%arg0: tensor<100xf32>) -> tensor<100xf32> { | |
| return %arg0 : tensor<100xf32> | |
| } | |
| // ----- | |
| // CHECK-LABEL: func.func @sparse_in( | |
| // CHECK-SAME: %[[B:.*0]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[C:.*1]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[A:.*]]: tensor<?xf32>) -> tensor<64x64xf32> { | |
| // CHECK: %[[I:.*]] = sparse_tensor.assemble (%[[B]], %[[C]]), %[[A]] | |
| // CHECK: %[[F:.*]] = call @_internal_sparse_in(%[[I]]) | |
| // CHECK: return %[[F]] : tensor<64x64xf32> | |
| // CHECK: } | |
| // CHECK: func.func private @_internal_sparse_in | |
| #sparse = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }> | |
| func.func @sparse_in(%arg0: tensor<64x64xf32, #sparse>) -> tensor<64x64xf32> { | |
| %0 = sparse_tensor.convert %arg0 : tensor<64x64xf32, #sparse> to tensor<64x64xf32> | |
| return %0 : tensor<64x64xf32> | |
| } | |
| // ----- | |
| // CHECK-LABEL: func.func @sparse_in2( | |
| // CHECK-SAME: %[[X:.*0]]: tensor<100xf32>, | |
| // CHECK-SAME: %[[B:.*1]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[C:.*2]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[A:.*3]]: tensor<?xf32>) -> tensor<64x64xf32> { | |
| // CHECK: %[[I:.*]] = sparse_tensor.assemble (%[[B]], %[[C]]), %[[A]] | |
| // CHECK: %[[F:.*]] = call @_internal_sparse_in2(%[[X]], %[[I]]) | |
| // CHECK: return %[[F]] : tensor<64x64xf32> | |
| // CHECK: } | |
| // CHECK: func.func private @_internal_sparse_in2 | |
| #sparse = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }> | |
| func.func @sparse_in2(%arg0: tensor<100xf32>, %arg1: tensor<64x64xf32, #sparse>) -> tensor<64x64xf32> { | |
| %0 = sparse_tensor.convert %arg1 : tensor<64x64xf32, #sparse> to tensor<64x64xf32> | |
| return %0 : tensor<64x64xf32> | |
| } | |
| // ----- | |
| // CHECK-LABEL: func.func @sparse_out( | |
| // CHECK-SAME: %[[X:.*0]]: tensor<64x64xf32>, | |
| // CHECK-SAME: %[[B:.*1]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[C:.*2]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[A:.*3]]: tensor<?xf32>) | |
| // CHECK: %[[F:.*]] = call @_internal_sparse_out(%[[X]]) | |
| // CHECK: sparse_tensor.disassemble %[[F]] | |
| // CHECK: return | |
| // CHECK: } | |
| // CHECK: func.func private @_internal_sparse_out | |
| #sparse = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }> | |
| func.func @sparse_out(%arg0: tensor<64x64xf32>) -> tensor<64x64xf32, #sparse> { | |
| %0 = sparse_tensor.convert %arg0 : tensor<64x64xf32> to tensor<64x64xf32, #sparse> | |
| return %0 : tensor<64x64xf32, #sparse> | |
| } | |
| // ----- | |
| // CHECK-LABEL: func.func @sparse_out2( | |
| // CHECK-SAME: %[[X:.*0]]: tensor<64x64xf32>, | |
| // CHECK-SAME: %[[B:.*1]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[C:.*2]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[A:.*3]]: tensor<?xf32>) | |
| // CHECK: %[[F:.*]]:2 = call @_internal_sparse_out2(%[[X]]) | |
| // CHECK: sparse_tensor.disassemble %[[F]]#1 | |
| // CHECK: return %[[F]]#0 | |
| // CHECK: } | |
| // CHECK: func.func private @_internal_sparse_out2 | |
| #sparse = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }> | |
| func.func @sparse_out2(%arg0: tensor<64x64xf32>) -> (tensor<64x64xf32>, tensor<64x64xf32, #sparse>) { | |
| %0 = sparse_tensor.convert %arg0 : tensor<64x64xf32> to tensor<64x64xf32, #sparse> | |
| return %arg0, %0 : tensor<64x64xf32>, tensor<64x64xf32, #sparse> | |
| } | |
| // ----- | |
| // CHECK-LABEL: func.func @sparse_inout( | |
| // CHECK-SAME: %[[B:.*0]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[C:.*1]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[A:.*2]]: tensor<?xf32>, | |
| // CHECK-SAME: %[[E:.*3]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[F:.*4]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[D:.*5]]: tensor<?xf32>) | |
| // CHECK: %[[I:.*]] = sparse_tensor.assemble (%[[B]], %[[C]]), %[[A]] | |
| // CHECK: %[[F:.*]] = call @_internal_sparse_inout(%[[I]]) | |
| // CHECK: sparse_tensor.disassemble %[[F]] | |
| // CHECK: return | |
| // CHECK: } | |
| // CHECK: func.func private @_internal_sparse_inout | |
| #sparse = #sparse_tensor.encoding<{ map = (d0, d1) -> (d0 : dense, d1 : compressed) }> | |
| func.func @sparse_inout(%arg0: tensor<64x64xf32, #sparse>) -> tensor<64x64xf32, #sparse> { | |
| return %arg0 : tensor<64x64xf32, #sparse> | |
| } | |
| // ----- | |
| // CHECK-LABEL: func.func @sparse_inout_coo_soa( | |
| // CHECK-SAME: %[[B:.*0]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[C:.*1]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[D:.*2]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[A:.*3]]: tensor<?xf32>, | |
| // CHECK-SAME: %[[F:.*4]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[G:.*5]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[H:.*6]]: tensor<?xindex>, | |
| // CHECK-SAME: %[[E:.*7]]: tensor<?xf32>) | |
| // CHECK: %[[I:.*]] = sparse_tensor.assemble (%[[B]], %[[C]], %[[D]]), %[[A]] | |
| // CHECK: %[[F:.*]] = call @_internal_sparse_inout_coo_soa(%[[I]]) | |
| // CHECK: sparse_tensor.disassemble %[[F]] | |
| // CHECK: return | |
| // CHECK: } | |
| // CHECK: func.func private @_internal_sparse_inout | |
| #sparse = #sparse_tensor.encoding<{ | |
| map = (d0, d1) -> (d0 : compressed(nonunique), d1 : singleton(soa)) | |
| }> | |
| func.func @sparse_inout_coo_soa(%arg0: tensor<64x64xf32, #sparse>) -> tensor<64x64xf32, #sparse> { | |
| return %arg0 : tensor<64x64xf32, #sparse> | |
| } |