574 lines
30 KiB
MLIR
574 lines
30 KiB
MLIR
// RUN: onnf-opt --shape-inference --lower-frontend %s -split-input-file | FileCheck %s
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func @test_add_add(%arg0 : tensor<?x10xf32>, %arg1 : tensor<?x10xf32>) -> tensor<*xf32> {
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%0 = "onnx.Add"(%arg0, %arg1) : (tensor<?x10xf32>, tensor<?x10xf32>) -> tensor<*xf32>
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%1 = "onnx.Add"(%0, %arg1) : (tensor<*xf32>, tensor<?x10xf32>) -> tensor<*xf32>
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"std.return"(%1) : (tensor<*xf32>) -> ()
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// CHECK-LABEL: test_add_add
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/// First Add
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// CHECK: [[DIM_0:%.+]] = dim %arg0, 0 : memref<?x10xf32>
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// CHECK: [[RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim %arg0, 0 : memref<?x10xf32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
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// CHECK: [[LOAD1:%.+]] = load %arg0[%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[ADDF:%.+]] = addf [[LOAD1]], [[LOAD2]] : f32
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// CHECK: store [[ADDF]], [[RES]][%arg2, %arg3] : memref<?x10xf32>
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/// Second Add
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// CHECK: [[DIM_0:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
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// CHECK: [[RET_RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
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// CHECK: [[LOAD1:%.+]] = load [[RES]][%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[ADDF:%.+]] = addf [[LOAD1]], [[LOAD2]] : f32
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// CHECK: store [[ADDF]], [[RET_RES]][%arg2, %arg3] : memref<?x10xf32>
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/// Dealloc of first result.
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// CHECK: dealloc [[RES]] : memref<?x10xf32>
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// CHECK-NOT: dealloc [[RET_RES]] : memref<?x10xf32>
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// CHECK: return [[RET_RES]] : memref<?x10xf32>
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}
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func @test_mul_mul(%arg0 : tensor<?x10xf32>, %arg1 : tensor<?x10xf32>) -> tensor<*xf32> {
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%0 = "onnx.Mul"(%arg0, %arg1) : (tensor<?x10xf32>, tensor<?x10xf32>) -> tensor<*xf32>
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%1 = "onnx.Mul"(%0, %arg1) : (tensor<*xf32>, tensor<?x10xf32>) -> tensor<*xf32>
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"std.return"(%1) : (tensor<*xf32>) -> ()
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// CHECK-LABEL: test_mul_mul
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/// First Mul
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// CHECK: [[DIM_0:%.+]] = dim %arg0, 0 : memref<?x10xf32>
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// CHECK: [[RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim %arg0, 0 : memref<?x10xf32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
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// CHECK: [[LOAD1:%.+]] = load %arg0[%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[MULF:%.+]] = mulf [[LOAD1]], [[LOAD2]] : f32
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// CHECK: store [[MULF]], [[RES]][%arg2, %arg3] : memref<?x10xf32>
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/// Second Mul
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// CHECK: [[DIM_0:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
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// CHECK: [[RET_RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
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// CHECK: [[LOAD1:%.+]] = load [[RES]][%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[MULF:%.+]] = mulf [[LOAD1]], [[LOAD2]] : f32
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// CHECK: store [[MULF]], [[RET_RES]][%arg2, %arg3] : memref<?x10xf32>
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/// Dealloc of first result.
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// CHECK: dealloc [[RES]] : memref<?x10xf32>
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// CHECK-NOT: dealloc [[RET_RES]] : memref<?x10xf32>
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// CHECK: return [[RET_RES]] : memref<?x10xf32>
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}
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func @test_div_div(%arg0 : tensor<?x10xf32>, %arg1 : tensor<?x10xf32>) -> tensor<*xf32> {
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%0 = "onnx.Div"(%arg0, %arg1) : (tensor<?x10xf32>, tensor<?x10xf32>) -> tensor<*xf32>
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%1 = "onnx.Div"(%0, %arg1) : (tensor<*xf32>, tensor<?x10xf32>) -> tensor<*xf32>
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"std.return"(%1) : (tensor<*xf32>) -> ()
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// CHECK-LABEL: test_div_div
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/// First Div
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// CHECK: [[DIM_0:%.+]] = dim %arg0, 0 : memref<?x10xf32>
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// CHECK: [[RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim %arg0, 0 : memref<?x10xf32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
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// CHECK: [[LOAD1:%.+]] = load %arg0[%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[DIVF:%.+]] = divf [[LOAD1]], [[LOAD2]] : f32
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// CHECK: store [[DIVF]], [[RES]][%arg2, %arg3] : memref<?x10xf32>
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/// Second Div
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// CHECK: [[DIM_0:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
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// CHECK: [[RET_RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
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// CHECK: [[LOAD1:%.+]] = load [[RES]][%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[DIVF:%.+]] = divf [[LOAD1]], [[LOAD2]] : f32
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// CHECK: store [[DIVF]], [[RET_RES]][%arg2, %arg3] : memref<?x10xf32>
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/// Dealloc of first result.
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// CHECK: dealloc [[RES]] : memref<?x10xf32>
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// CHECK-NOT: dealloc [[RET_RES]] : memref<?x10xf32>
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// CHECK: return [[RET_RES]] : memref<?x10xf32>
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}
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func @test_sub_sub(%arg0 : tensor<?x10xf32>, %arg1 : tensor<?x10xf32>) -> tensor<*xf32> {
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%0 = "onnx.Sub"(%arg0, %arg1) : (tensor<?x10xf32>, tensor<?x10xf32>) -> tensor<*xf32>
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%1 = "onnx.Sub"(%0, %arg1) : (tensor<*xf32>, tensor<?x10xf32>) -> tensor<*xf32>
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"std.return"(%1) : (tensor<*xf32>) -> ()
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// CHECK-LABEL: test_sub_sub
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/// First Sub
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// CHECK: [[DIM_0:%.+]] = dim %arg0, 0 : memref<?x10xf32>
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// CHECK: [[RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim %arg0, 0 : memref<?x10xf32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
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// CHECK: [[LOAD1:%.+]] = load %arg0[%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[SUBF:%.+]] = subf [[LOAD1]], [[LOAD2]] : f32
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// CHECK: store [[SUBF]], [[RES]][%arg2, %arg3] : memref<?x10xf32>
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/// Second Sub
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// CHECK: [[DIM_0:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
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// CHECK: [[RET_RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
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// CHECK: [[LOAD1:%.+]] = load [[RES]][%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xf32>
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// CHECK: [[SUBF:%.+]] = subf [[LOAD1]], [[LOAD2]] : f32
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// CHECK: store [[SUBF]], [[RET_RES]][%arg2, %arg3] : memref<?x10xf32>
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/// Dealloc of first result.
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// CHECK: dealloc [[RES]] : memref<?x10xf32>
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// CHECK-NOT: dealloc [[RET_RES]] : memref<?x10xf32>
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// CHECK: return [[RET_RES]] : memref<?x10xf32>
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}
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func @test_and_and(%arg0 : tensor<?x10xi32>, %arg1 : tensor<?x10xi32>) -> tensor<*xi32> {
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%0 = "onnx.And"(%arg0, %arg1) : (tensor<?x10xi32>, tensor<?x10xi32>) -> tensor<*xi32>
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%1 = "onnx.And"(%0, %arg1) : (tensor<*xi32>, tensor<?x10xi32>) -> tensor<*xi32>
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"std.return"(%1) : (tensor<*xi32>) -> ()
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// CHECK-LABEL: test_and_and
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/// First And
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// CHECK: [[DIM_0:%.+]] = dim %arg0, 0 : memref<?x10xi32>
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// CHECK: [[RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xi32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim %arg0, 0 : memref<?x10xi32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
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// CHECK: [[LOAD1:%.+]] = load %arg0[%arg2, %arg3] : memref<?x10xi32>
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// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xi32>
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// CHECK: [[AND:%.+]] = and [[LOAD1]], [[LOAD2]] : i32
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// CHECK: store [[AND]], [[RES]][%arg2, %arg3] : memref<?x10xi32>
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/// Second And
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// CHECK: [[DIM_0:%.+]] = dim [[RES]], 0 : memref<?x10xi32>
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// CHECK: [[RET_RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xi32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim [[RES]], 0 : memref<?x10xi32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
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// CHECK: [[LOAD1:%.+]] = load [[RES]][%arg2, %arg3] : memref<?x10xi32>
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// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xi32>
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// CHECK: [[AND:%.+]] = and [[LOAD1]], [[LOAD2]] : i32
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// CHECK: store [[AND]], [[RET_RES]][%arg2, %arg3] : memref<?x10xi32>
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/// Dealloc of first result.
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// CHECK: dealloc [[RES]] : memref<?x10xi32>
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// CHECK-NOT: dealloc [[RET_RES]] : memref<?x10xi32>
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// CHECK: return [[RET_RES]] : memref<?x10xi32>
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}
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func @test_or_or(%arg0 : tensor<?x10xi32>, %arg1 : tensor<?x10xi32>) -> tensor<*xi32> {
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%0 = "onnx.Or"(%arg0, %arg1) : (tensor<?x10xi32>, tensor<?x10xi32>) -> tensor<*xi32>
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%1 = "onnx.Or"(%0, %arg1) : (tensor<*xi32>, tensor<?x10xi32>) -> tensor<*xi32>
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"std.return"(%1) : (tensor<*xi32>) -> ()
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// CHECK-LABEL: test_or_or
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/// First Or
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// CHECK: [[DIM_0:%.+]] = dim %arg0, 0 : memref<?x10xi32>
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// CHECK: [[RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xi32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim %arg0, 0 : memref<?x10xi32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
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// CHECK: [[LOAD1:%.+]] = load %arg0[%arg2, %arg3] : memref<?x10xi32>
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// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xi32>
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// CHECK: [[OR:%.+]] = or [[LOAD1]], [[LOAD2]] : i32
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// CHECK: store [[OR]], [[RES]][%arg2, %arg3] : memref<?x10xi32>
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/// Second Or
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// CHECK: [[DIM_0:%.+]] = dim [[RES]], 0 : memref<?x10xi32>
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// CHECK: [[RET_RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xi32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim [[RES]], 0 : memref<?x10xi32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
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// CHECK: [[LOAD1:%.+]] = load [[RES]][%arg2, %arg3] : memref<?x10xi32>
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// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xi32>
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// CHECK: [[OR:%.+]] = or [[LOAD1]], [[LOAD2]] : i32
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// CHECK: store [[OR]], [[RET_RES]][%arg2, %arg3] : memref<?x10xi32>
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/// Dealloc of first result.
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// CHECK: dealloc [[RES]] : memref<?x10xi32>
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// CHECK-NOT: dealloc [[RET_RES]] : memref<?x10xi32>
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// CHECK: return [[RET_RES]] : memref<?x10xi32>
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}
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func @test_xor_xor(%arg0 : tensor<?x10xi32>, %arg1 : tensor<?x10xi32>) -> tensor<*xi32> {
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%0 = "onnx.Xor"(%arg0, %arg1) : (tensor<?x10xi32>, tensor<?x10xi32>) -> tensor<*xi32>
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%1 = "onnx.Xor"(%0, %arg1) : (tensor<*xi32>, tensor<?x10xi32>) -> tensor<*xi32>
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"std.return"(%1) : (tensor<*xi32>) -> ()
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// CHECK-LABEL: test_xor_xor
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/// First Xor
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// CHECK: [[DIM_0:%.+]] = dim %arg0, 0 : memref<?x10xi32>
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// CHECK: [[RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xi32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim %arg0, 0 : memref<?x10xi32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
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// CHECK: [[LOAD1:%.+]] = load %arg0[%arg2, %arg3] : memref<?x10xi32>
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// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xi32>
|
|
// CHECK: [[XOR:%.+]] = xor [[LOAD1]], [[LOAD2]] : i32
|
|
// CHECK: store [[XOR]], [[RES]][%arg2, %arg3] : memref<?x10xi32>
|
|
|
|
/// Second Xor
|
|
// CHECK: [[DIM_0:%.+]] = dim [[RES]], 0 : memref<?x10xi32>
|
|
// CHECK: [[RET_RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xi32>
|
|
// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
|
|
// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
|
|
// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
|
|
// CHECK: } : () -> (!krnl.loop, !krnl.loop)
|
|
// CHECK: [[DIM_2:%.+]] = dim [[RES]], 0 : memref<?x10xi32>
|
|
// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg2 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg3 = 0 to 10) {
|
|
// CHECK: [[LOAD1:%.+]] = load [[RES]][%arg2, %arg3] : memref<?x10xi32>
|
|
// CHECK: [[LOAD2:%.+]] = load %arg1[%arg2, %arg3] : memref<?x10xi32>
|
|
// CHECK: [[XOR:%.+]] = xor [[LOAD1]], [[LOAD2]] : i32
|
|
// CHECK: store [[XOR]], [[RET_RES]][%arg2, %arg3] : memref<?x10xi32>
|
|
|
|
/// Dealloc of first result.
|
|
// CHECK: dealloc [[RES]] : memref<?x10xi32>
|
|
// CHECK-NOT: dealloc [[RET_RES]] : memref<?x10xi32>
|
|
|
|
// CHECK: return [[RET_RES]] : memref<?x10xi32>
|
|
}
|
|
|
|
func @test_exp_exp(%arg0 : tensor<?x10xf32>) -> tensor<*xf32> {
|
|
%0 = "onnx.Exp"(%arg0) : (tensor<?x10xf32>) -> tensor<*xf32>
|
|
%1 = "onnx.Exp"(%0) : (tensor<*xf32>) -> tensor<*xf32>
|
|
"std.return"(%1) : (tensor<*xf32>) -> ()
|
|
|
|
// CHECK-LABEL: test_exp_exp
|
|
/// First Exp
|
|
// CHECK: [[DIM_0:%.+]] = dim %arg0, 0 : memref<?x10xf32>
|
|
// CHECK: [[RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
|
|
// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
|
|
// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
|
|
// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
|
|
// CHECK: } : () -> (!krnl.loop, !krnl.loop)
|
|
// CHECK: [[DIM_2:%.+]] = dim %arg0, 0 : memref<?x10xf32>
|
|
// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg1 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg2 = 0 to 10) {
|
|
// CHECK: [[LOAD:%.+]] = load %arg0[%arg1, %arg2] : memref<?x10xf32>
|
|
// CHECK: [[EXP:%.+]] = exp [[LOAD]] : f32
|
|
// CHECK: store [[EXP]], [[RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
|
|
/// Second Exp
|
|
// CHECK: [[DIM_0:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
|
|
// CHECK: [[RET_RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
|
|
// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
|
|
// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
|
|
// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
|
|
// CHECK: } : () -> (!krnl.loop, !krnl.loop)
|
|
// CHECK: [[DIM_2:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
|
|
// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg1 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg2 = 0 to 10) {
|
|
// CHECK: [[LOAD:%.+]] = load [[RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
// CHECK: [[EXP:%.+]] = exp [[LOAD]] : f32
|
|
// CHECK: store [[EXP]], [[RET_RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
|
|
/// Dealloc of first result.
|
|
// CHECK: dealloc [[RES]] : memref<?x10xf32>
|
|
// CHECK-NOT: dealloc [[RET_RES]] : memref<?x10xf32>
|
|
|
|
// CHECK: return [[RET_RES]] : memref<?x10xf32>
|
|
}
|
|
|
|
func @test_tanh_tanh(%arg0 : tensor<?x10xf32>) -> tensor<*xf32> {
|
|
%0 = "onnx.Tanh"(%arg0) : (tensor<?x10xf32>) -> tensor<*xf32>
|
|
%1 = "onnx.Tanh"(%0) : (tensor<*xf32>) -> tensor<*xf32>
|
|
"std.return"(%1) : (tensor<*xf32>) -> ()
|
|
|
|
// CHECK-LABEL: test_tanh_tanh
|
|
/// First Tanh
|
|
// CHECK: [[DIM_0:%.+]] = dim %arg0, 0 : memref<?x10xf32>
|
|
// CHECK: [[RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
|
|
// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
|
|
// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
|
|
// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
|
|
// CHECK: } : () -> (!krnl.loop, !krnl.loop)
|
|
// CHECK: [[DIM_2:%.+]] = dim %arg0, 0 : memref<?x10xf32>
|
|
// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg1 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg2 = 0 to 10) {
|
|
// CHECK: [[LOAD:%.+]] = load %arg0[%arg1, %arg2] : memref<?x10xf32>
|
|
// CHECK: [[ZERO:%.+]] = constant {{0.+}} : f32
|
|
// CHECK: [[NLOAD:%.+]] = subf [[ZERO]], [[LOAD]] : f32
|
|
// CHECK: [[EXP:%.+]] = exp [[LOAD]] : f32
|
|
// CHECK: [[NEXP:%.+]] = exp [[NLOAD]] : f32
|
|
// CHECK: [[DIVIDEND:%.+]] = subf [[EXP]], [[NEXP]] : f32
|
|
// CHECK: [[DIVISOR:%.+]] = addf [[EXP]], [[NEXP]] : f32
|
|
// CHECK: [[TANH_RES:%.+]] = divf [[DIVIDEND]], [[DIVISOR]] : f32
|
|
// CHECK: store [[TANH_RES]], [[RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
|
|
/// Second Tanh
|
|
// CHECK: [[DIM_0:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
|
|
// CHECK: [[RET_RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
|
|
// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
|
|
// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
|
|
// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
|
|
// CHECK: } : () -> (!krnl.loop, !krnl.loop)
|
|
// CHECK: [[DIM_2:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
|
|
// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg1 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg2 = 0 to 10) {
|
|
// CHECK: [[LOAD:%.+]] = load [[RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
// CHECK: [[ZERO:%.+]] = constant {{0.+}} : f32
|
|
// CHECK: [[NLOAD:%.+]] = subf [[ZERO]], [[LOAD]] : f32
|
|
// CHECK: [[EXP:%.+]] = exp [[LOAD]] : f32
|
|
// CHECK: [[NEXP:%.+]] = exp [[NLOAD]] : f32
|
|
// CHECK: [[DIVIDEND:%.+]] = subf [[EXP]], [[NEXP]] : f32
|
|
// CHECK: [[DIVISOR:%.+]] = addf [[EXP]], [[NEXP]] : f32
|
|
// CHECK: [[TANH_RES:%.+]] = divf [[DIVIDEND]], [[DIVISOR]] : f32
|
|
// CHECK: store [[TANH_RES]], [[RET_RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
|
|
/// Dealloc of first result.
|
|
// CHECK: dealloc [[RES]] : memref<?x10xf32>
|
|
// CHECK-NOT: dealloc [[RET_RES]] : memref<?x10xf32>
|
|
|
|
// CHECK: return [[RET_RES]] : memref<?x10xf32>
|
|
}
|
|
|
|
func @test_sinh_sinh(%arg0 : tensor<?x10xf32>) -> tensor<*xf32> {
|
|
%0 = "onnx.Sinh"(%arg0) : (tensor<?x10xf32>) -> tensor<*xf32>
|
|
%1 = "onnx.Sinh"(%0) : (tensor<*xf32>) -> tensor<*xf32>
|
|
"std.return"(%1) : (tensor<*xf32>) -> ()
|
|
|
|
// CHECK-LABEL: test_sinh_sinh
|
|
/// First Sinh
|
|
// CHECK: [[DIM_0:%.+]] = dim %arg0, 0 : memref<?x10xf32>
|
|
// CHECK: [[RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
|
|
// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
|
|
// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
|
|
// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
|
|
// CHECK: } : () -> (!krnl.loop, !krnl.loop)
|
|
// CHECK: [[DIM_2:%.+]] = dim %arg0, 0 : memref<?x10xf32>
|
|
// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg1 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg2 = 0 to 10) {
|
|
// CHECK: [[LOAD:%.+]] = load %arg0[%arg1, %arg2] : memref<?x10xf32>
|
|
// CHECK: [[ZERO:%.+]] = constant {{0.+}} : f32
|
|
// CHECK: [[TWO:%.+]] = constant {{2.+}} : f32
|
|
// CHECK: [[NLOAD:%.+]] = subf [[ZERO]], [[LOAD]] : f32
|
|
// CHECK: [[EXP:%.+]] = exp [[LOAD]] : f32
|
|
// CHECK: [[NEXP:%.+]] = exp [[NLOAD]] : f32
|
|
// CHECK: [[DIVIDEND:%.+]] = subf [[EXP]], [[NEXP]] : f32
|
|
// CHECK: [[SINH_RES:%.+]] = divf [[DIVIDEND]], [[TWO]] : f32
|
|
// CHECK: store [[SINH_RES]], [[RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
|
|
/// Second Sinh
|
|
// CHECK: [[DIM_0:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
|
|
// CHECK: [[RET_RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
|
|
// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
|
|
// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
|
|
// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
|
|
// CHECK: } : () -> (!krnl.loop, !krnl.loop)
|
|
// CHECK: [[DIM_2:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
|
|
// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg1 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg2 = 0 to 10) {
|
|
// CHECK: [[LOAD:%.+]] = load [[RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
// CHECK: [[ZERO:%.+]] = constant {{0.+}} : f32
|
|
// CHECK: [[TWO:%.+]] = constant {{2.+}} : f32
|
|
// CHECK: [[NLOAD:%.+]] = subf [[ZERO]], [[LOAD]] : f32
|
|
// CHECK: [[EXP:%.+]] = exp [[LOAD]] : f32
|
|
// CHECK: [[NEXP:%.+]] = exp [[NLOAD]] : f32
|
|
// CHECK: [[DIVIDEND:%.+]] = subf [[EXP]], [[NEXP]] : f32
|
|
// CHECK: [[SINH_RES:%.+]] = divf [[DIVIDEND]], [[TWO]] : f32
|
|
// CHECK: store [[SINH_RES]], [[RET_RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
|
|
/// Dealloc of first result.
|
|
// CHECK: dealloc [[RES]] : memref<?x10xf32>
|
|
// CHECK-NOT: dealloc [[RET_RES]] : memref<?x10xf32>
|
|
|
|
// CHECK: return [[RET_RES]] : memref<?x10xf32>
|
|
}
|
|
|
|
func @test_cosh_cosh(%arg0 : tensor<?x10xf32>) -> tensor<*xf32> {
|
|
%0 = "onnx.Cosh"(%arg0) : (tensor<?x10xf32>) -> tensor<*xf32>
|
|
%1 = "onnx.Cosh"(%0) : (tensor<*xf32>) -> tensor<*xf32>
|
|
"std.return"(%1) : (tensor<*xf32>) -> ()
|
|
|
|
// CHECK-LABEL: test_cosh_cosh
|
|
/// First Cosh
|
|
// CHECK: [[DIM_0:%.+]] = dim %arg0, 0 : memref<?x10xf32>
|
|
// CHECK: [[RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
|
|
// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
|
|
// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
|
|
// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
|
|
// CHECK: } : () -> (!krnl.loop, !krnl.loop)
|
|
// CHECK: [[DIM_2:%.+]] = dim %arg0, 0 : memref<?x10xf32>
|
|
// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg1 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg2 = 0 to 10) {
|
|
// CHECK: [[LOAD:%.+]] = load %arg0[%arg1, %arg2] : memref<?x10xf32>
|
|
// CHECK: [[ZERO:%.+]] = constant {{0.+}} : f32
|
|
// CHECK: [[TWO:%.+]] = constant {{2.+}} : f32
|
|
// CHECK: [[NLOAD:%.+]] = subf [[ZERO]], [[LOAD]] : f32
|
|
// CHECK: [[EXP:%.+]] = exp [[LOAD]] : f32
|
|
// CHECK: [[NEXP:%.+]] = exp [[NLOAD]] : f32
|
|
// CHECK: [[DIVIDEND:%.+]] = addf [[EXP]], [[NEXP]] : f32
|
|
// CHECK: [[COSH_RES:%.+]] = divf [[DIVIDEND]], [[TWO]] : f32
|
|
// CHECK: store [[COSH_RES]], [[RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
|
|
/// Second Cosh
|
|
// CHECK: [[DIM_0:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
|
|
// CHECK: [[RET_RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
|
|
// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
|
|
// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
|
|
// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
|
|
// CHECK: } : () -> (!krnl.loop, !krnl.loop)
|
|
// CHECK: [[DIM_2:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
|
|
// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg1 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg2 = 0 to 10) {
|
|
// CHECK: [[LOAD:%.+]] = load [[RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
// CHECK: [[ZERO:%.+]] = constant {{0.+}} : f32
|
|
// CHECK: [[TWO:%.+]] = constant {{2.+}} : f32
|
|
// CHECK: [[NLOAD:%.+]] = subf [[ZERO]], [[LOAD]] : f32
|
|
// CHECK: [[EXP:%.+]] = exp [[LOAD]] : f32
|
|
// CHECK: [[NEXP:%.+]] = exp [[NLOAD]] : f32
|
|
// CHECK: [[DIVIDEND:%.+]] = addf [[EXP]], [[NEXP]] : f32
|
|
// CHECK: [[COSH_RES:%.+]] = divf [[DIVIDEND]], [[TWO]] : f32
|
|
// CHECK: store [[COSH_RES]], [[RET_RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
|
|
/// Dealloc of first result.
|
|
// CHECK: dealloc [[RES]] : memref<?x10xf32>
|
|
// CHECK-NOT: dealloc [[RET_RES]] : memref<?x10xf32>
|
|
|
|
// CHECK: return [[RET_RES]] : memref<?x10xf32>
|
|
}
|
|
|
|
func @test_sigmoid_sigmoid(%arg0 : tensor<?x10xf32>) -> tensor<*xf32> {
|
|
%0 = "onnx.Sigmoid"(%arg0) : (tensor<?x10xf32>) -> tensor<*xf32>
|
|
%1 = "onnx.Sigmoid"(%0) : (tensor<*xf32>) -> tensor<*xf32>
|
|
"std.return"(%1) : (tensor<*xf32>) -> ()
|
|
|
|
// CHECK-LABEL: test_sigmoid_sigmoid
|
|
/// First Sigmoid
|
|
// CHECK: [[DIM_0:%.+]] = dim %arg0, 0 : memref<?x10xf32>
|
|
// CHECK: [[RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
|
|
// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
|
|
// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
|
|
// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
|
|
// CHECK: } : () -> (!krnl.loop, !krnl.loop)
|
|
// CHECK: [[DIM_2:%.+]] = dim %arg0, 0 : memref<?x10xf32>
|
|
// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg1 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg2 = 0 to 10) {
|
|
// CHECK: [[LOAD:%.+]] = load %arg0[%arg1, %arg2] : memref<?x10xf32>
|
|
// CHECK: [[ZERO:%.+]] = constant {{0.+}} : f32
|
|
// CHECK: [[ONE:%.+]] = constant {{1.+}} : f32
|
|
// CHECK: [[NLOAD:%.+]] = subf [[ZERO]], [[LOAD]] : f32
|
|
// CHECK: [[NEXP:%.+]] = exp [[NLOAD]] : f32
|
|
// CHECK: [[DIVISOR:%.+]] = addf [[ONE]], [[NEXP]] : f32
|
|
// CHECK: [[SIGMOID_RES:%.+]] = divf [[ONE]], [[DIVISOR]] : f32
|
|
// CHECK: store [[SIGMOID_RES]], [[RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
|
|
/// Second Sigmoid
|
|
// CHECK: [[DIM_0:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
|
|
// CHECK: [[RET_RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
|
|
// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
|
|
// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
|
|
// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
|
|
// CHECK: } : () -> (!krnl.loop, !krnl.loop)
|
|
// CHECK: [[DIM_2:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
|
|
// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg1 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg2 = 0 to 10) {
|
|
// CHECK: [[LOAD:%.+]] = load [[RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
// CHECK: [[ZERO:%.+]] = constant {{0.+}} : f32
|
|
// CHECK: [[ONE:%.+]] = constant {{1.+}} : f32
|
|
// CHECK: [[NLOAD:%.+]] = subf [[ZERO]], [[LOAD]] : f32
|
|
// CHECK: [[NEXP:%.+]] = exp [[NLOAD]] : f32
|
|
// CHECK: [[DIVISOR:%.+]] = addf [[ONE]], [[NEXP]] : f32
|
|
// CHECK: [[SIGMOID_RES:%.+]] = divf [[ONE]], [[DIVISOR]] : f32
|
|
// CHECK: store [[SIGMOID_RES]], [[RET_RES]][%arg1, %arg2] : memref<?x10xf32>
|
|
|
|
/// Dealloc of first result.
|
|
// CHECK: dealloc [[RES]] : memref<?x10xf32>
|
|
// CHECK-NOT: dealloc [[RET_RES]] : memref<?x10xf32>
|
|
|
|
// CHECK: return [[RET_RES]] : memref<?x10xf32>
|
|
}
|
|
|
|
func @test_relu_relu(%arg0 : tensor<?x10xf32>) -> tensor<*xf32> {
|
|
%0 = "onnx.Relu"(%arg0) : (tensor<?x10xf32>) -> tensor<*xf32>
|
|
%1 = "onnx.Relu"(%0) : (tensor<*xf32>) -> tensor<*xf32>
|
|
"std.return"(%1) : (tensor<*xf32>) -> ()
|
|
|
|
// CHECK-LABEL: test_relu_relu
|
|
/// First Relu
|
|
// CHECK: [[DIM_0:%.+]] = dim %arg0, 0 : memref<?x10xf32>
|
|
// CHECK: [[RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
|
|
// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
|
|
// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
|
|
// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
|
|
// CHECK: } : () -> (!krnl.loop, !krnl.loop)
|
|
// CHECK: [[DIM_2:%.+]] = dim %arg0, 0 : memref<?x10xf32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg1 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg2 = 0 to 10) {
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// CHECK: [[LOAD:%.+]] = load %arg0[%arg1, %arg2] : memref<?x10xf32>
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// CHECK: [[ZERO:%.+]] = constant {{0.+}} : f32
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// CHECK: [[LTZERO:%.+]] = cmpf "olt", [[LOAD]], [[ZERO]] : f32
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// CHECK: [[RELU_RES:%.+]] = select [[LTZERO]], [[ZERO]], [[LOAD]] : f32
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// CHECK: store [[RELU_RES]], [[RES]][%arg1, %arg2] : memref<?x10xf32>
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/// Second Relu
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// CHECK: [[DIM_0:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
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// CHECK: [[RET_RES:%.+]] = alloc([[DIM_0]]) : memref<?x10xf32>
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// CHECK: [[DEF_LOOPS:%.+]]:2 = krnl.define_loops 2
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// CHECK: [[OPT_LOOPS:%.+]]:2 = krnl.optimize_loops {
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// CHECK: krnl.return_loops [[DEF_LOOPS]]#0, [[DEF_LOOPS]]#1
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// CHECK: } : () -> (!krnl.loop, !krnl.loop)
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// CHECK: [[DIM_2:%.+]] = dim [[RES]], 0 : memref<?x10xf32>
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// CHECK: krnl.iterate([[OPT_LOOPS]]#0, [[OPT_LOOPS]]#1) with ([[DEF_LOOPS]]#0 -> %arg1 = 0 to [[DIM_2]], [[DEF_LOOPS]]#1 -> %arg2 = 0 to 10) {
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// CHECK: [[LOAD:%.+]] = load [[RES]][%arg1, %arg2] : memref<?x10xf32>
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// CHECK: [[ZERO:%.+]] = constant {{0.+}} : f32
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// CHECK: [[LTZERO:%.+]] = cmpf "olt", [[LOAD]], [[ZERO]] : f32
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// CHECK: [[RELU_RES:%.+]] = select [[LTZERO]], [[ZERO]], [[LOAD]] : f32
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// CHECK: store [[RELU_RES]], [[RET_RES]][%arg1, %arg2] : memref<?x10xf32>
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/// Dealloc of first result.
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// CHECK: dealloc [[RES]] : memref<?x10xf32>
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// CHECK-NOT: dealloc [[RET_RES]] : memref<?x10xf32>
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// CHECK: return [[RET_RES]] : memref<?x10xf32>
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}
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