| // RUN: mlir-opt %s -test-linalg-transform-patterns=test-linalg-to-vector-patterns -split-input-file | FileCheck %s |
| |
| // ----- |
| |
| // CHECK-LABEL: contraction_dot |
| func @contraction_dot(%A: memref<1584xf32>, %B: memref<1584xf32>, %C: memref<f32>) { |
| |
| // CHECK: arith.mulf %{{.*}}, %{{.*}} : vector<1584xf32> |
| // CHECK: vector.multi_reduction #vector.kind<add>, %{{.*}} [0] : vector<1584xf32> to f32 |
| // CHECK: arith.addf %{{.*}}, %{{.*}} : f32 |
| linalg.dot ins(%A, %B: memref<1584xf32>, memref<1584xf32>) |
| outs(%C: memref<f32>) |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: contraction_matvec |
| func @contraction_matvec(%A: memref<1584x1584xf32>, %B: memref<1584xf32>, %C: memref<1584xf32>) { |
| |
| // CHECK: arith.mulf %{{.*}}, %{{.*}} : vector<1584x1584xf32> |
| // CHECK: vector.multi_reduction #vector.kind<add>, %{{.*}} [1] : vector<1584x1584xf32> to vector<1584xf32> |
| // CHECK: arith.addf %{{.*}}, %{{.*}} : vector<1584xf32> |
| linalg.matvec ins(%A, %B: memref<1584x1584xf32>, memref<1584xf32>) |
| outs(%C: memref<1584xf32>) |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: contraction_matmul |
| func @contraction_matmul(%A: memref<1584x1584xf32>, %B: memref<1584x1584xf32>, %C: memref<1584x1584xf32>) { |
| // CHECK: arith.mulf %{{.*}}, %{{.*}} : vector<1584x1584x1584xf32> |
| // CHECK: vector.multi_reduction #vector.kind<add>, %{{.*}} [2] : vector<1584x1584x1584xf32> to vector<1584x1584xf32> |
| // CHECK: arith.addf %{{.*}}, %{{.*}} : vector<1584x1584xf32> |
| linalg.matmul ins(%A, %B: memref<1584x1584xf32>, memref<1584x1584xf32>) |
| outs(%C: memref<1584x1584xf32>) |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: contraction_batch_matmul |
| func @contraction_batch_matmul(%A: memref<1584x1584x1584xf32>, %B: memref<1584x1584x1584xf32>, %C: memref<1584x1584x1584xf32>) { |
| // CHECK: arith.mulf %{{.*}}, %{{.*}} : vector<1584x1584x1584x1584xf32> |
| // CHECK: vector.multi_reduction #vector.kind<add>, %{{.*}} [3] : vector<1584x1584x1584x1584xf32> to vector<1584x1584x1584xf32> |
| // CHECK: arith.addf %{{.*}}, %{{.*}} : vector<1584x1584x1584xf32> |
| linalg.batch_matmul |
| ins(%A, %B: memref<1584x1584x1584xf32>, memref<1584x1584x1584xf32>) |
| outs(%C: memref<1584x1584x1584xf32>) |
| return |
| } |
| |
| // ----- |
| |
| #matmul_trait = { |
| args_in = 2, |
| args_out = 1, |
| indexing_maps = [ |
| affine_map<(m, n, k) -> (m, k)>, |
| affine_map<(m, n, k) -> (k, n)>, |
| affine_map<(m, n, k) -> (m, n)> |
| ], |
| iterator_types = ["parallel", "parallel", "reduction"] |
| } |
| |
| // CHECK-LABEL: func @vectorization_test |
| func @vectorization_test(%A: memref<8x16xf32>, %B: memref<16x32xf32>, |
| %C: memref<8x32xf32>) { |
| // CHECK: vector.transfer_read %{{.*}} : memref<8x16xf32>, vector<8x32x16xf32> |
| // CHECK: vector.transfer_read %{{.*}} : memref<16x32xf32>, vector<8x32x16xf32> |
| // CHECK: vector.transfer_read %{{.*}} : memref<8x32xf32>, vector<8x32xf32> |
| // CHECK: %[[MUL:.*]] = arith.mulf %{{.*}}, %{{.*}} : vector<8x32x16xf32> |
| // CHECK: %[[R:.*]] = vector.multi_reduction #vector.kind<add>, %[[MUL]] [2] : vector<8x32x16xf32> to vector<8x32xf32> |
| // CHECK: arith.addf %[[R]], %{{.*}} : vector<8x32xf32> |
| // CHECK: vector.transfer_write %{{.*}}, %{{.*}} : vector<8x32xf32>, memref<8x32xf32> |
| linalg.generic #matmul_trait |
| ins(%A, %B : memref<8x16xf32>, memref<16x32xf32>) |
| outs(%C : memref<8x32xf32>) { |
| ^bb(%a: f32, %b: f32, %c: f32) : |
| %d = arith.mulf %a, %b: f32 |
| %e = arith.addf %c, %d: f32 |
| linalg.yield %e : f32 |
| } |
| return |
| } |
| |
| // ----- |
| |
| #matmul_transpose_out_trait = { |
| args_in = 2, |
| args_out = 1, |
| indexing_maps = [ |
| affine_map<(m, n, k) -> (m, k)>, |
| affine_map<(m, n, k) -> (k, n)>, |
| affine_map<(m, n, k) -> (n, m)> |
| ], |
| iterator_types = ["parallel", "parallel", "reduction"] |
| } |
| |
| // CHECK-LABEL: func @generic_output_transpose |
| func @generic_output_transpose(%A: memref<8x16xf32>, %B: memref<16x32xf32>, |
| %C: memref<32x8xf32>) { |
| // CHECK: vector.transfer_read %{{.*}} : memref<8x16xf32>, vector<8x32x16xf32> |
| // CHECK: vector.transfer_read %{{.*}} : memref<16x32xf32>, vector<8x32x16xf32> |
| // CHECK: vector.transfer_read %{{.*}} : memref<32x8xf32>, vector<8x32xf32> |
| // CHECK: %[[MUL:.*]] = arith.mulf %{{.*}}, %{{.*}} : vector<8x32x16xf32> |
| // CHECK: %[[R:.*]] = vector.multi_reduction #vector.kind<add>, %[[MUL]] [2] : vector<8x32x16xf32> to vector<8x32xf32> |
| // CHECK: arith.addf %[[R]], %{{.*}} : vector<8x32xf32> |
| // CHECK: vector.transfer_write %{{.*}}, %{{.*}} : vector<8x32xf32>, memref<32x8xf32> |
| linalg.generic #matmul_transpose_out_trait |
| ins(%A, %B : memref<8x16xf32>, memref<16x32xf32>) |
| outs(%C : memref<32x8xf32>) { |
| ^bb(%a: f32, %b: f32, %c: f32) : |
| %d = arith.mulf %a, %b: f32 |
| %e = arith.addf %c, %d: f32 |
| linalg.yield %e : f32 |
| } |
| return |
| } |
| |
| // ----- |
| |
| #matmul_trait = { |
| args_in = 2, |
| args_out = 1, |
| indexing_maps = [ |
| affine_map<(m, n, k) -> (m, k)>, |
| affine_map<(m, n, k) -> (k, n)>, |
| affine_map<(m, n, k) -> (m, n)> |
| ], |
| iterator_types = ["parallel", "parallel", "reduction"] |
| } |
| |
| // CHECK-LABEL: func @vectorization_test_integer |
| func @vectorization_test_integer(%A: memref<8x16xi32>, %B: memref<16x32xi32>, |
| %C: memref<8x32xi32>) { |
| // CHECK: vector.transfer_read %{{.*}} : memref<8x16xi32>, vector<8x32x16xi32> |
| // CHECK: vector.transfer_read %{{.*}} : memref<16x32xi32>, vector<8x32x16xi32> |
| // CHECK: vector.transfer_read %{{.*}} : memref<8x32xi32>, vector<8x32xi32> |
| // CHECK: %[[MUL:.*]] = arith.muli %{{.*}}, %{{.*}} : vector<8x32x16xi32> |
| // CHECK: %[[R:.*]] = vector.multi_reduction #vector.kind<add>, %[[MUL]] [2] : vector<8x32x16xi32> to vector<8x32xi32> |
| // CHECK: arith.addi %[[R]], %{{.*}} : vector<8x32xi32> |
| |
| // CHECK: vector.transfer_write %{{.*}}, %{{.*}} : vector<8x32xi32>, memref<8x32xi32> |
| linalg.generic #matmul_trait |
| ins(%A, %B : memref<8x16xi32>, memref<16x32xi32>) |
| outs(%C : memref<8x32xi32>) { |
| ^bb(%a: i32, %b: i32, %c: i32) : |
| %d = arith.muli %a, %b: i32 |
| %e = arith.addi %c, %d: i32 |
| linalg.yield %e : i32 |
| } |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @vectorization_test_2 |
| func @vectorization_test_2(%A: memref<8x16xf32>, %B: memref<16x32xf32>, |
| %C: memref<8x32xf32>) { |
| // CHECK: arith.mulf %{{.*}}, %{{.*}} : vector<8x32x16xf32> |
| // CHECK: vector.multi_reduction #vector.kind<add>, %{{.*}} [2] : vector<8x32x16xf32> to vector<8x32xf32> |
| // CHECK: arith.addf %{{.*}}, %{{.*}} : vector<8x32xf32> |
| linalg.matmul |
| ins(%A, %B: memref<8x16xf32>, memref<16x32xf32>) |
| outs(%C: memref<8x32xf32>) |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @test_vectorize_scalar_input |
| func @test_vectorize_scalar_input(%A : memref<8x16xf32>, %arg0 : f32) { |
| // CHECK: %[[V:.*]] = vector.broadcast {{.*}} : f32 to vector<8x16xf32> |
| // CHECK: vector.transfer_write %[[V]], {{.*}} : vector<8x16xf32>, memref<8x16xf32> |
| linalg.generic { |
| indexing_maps = [affine_map<(m, n) -> ()>, affine_map<(m, n) -> (m, n)>], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%arg0 : f32) |
| outs(%A: memref<8x16xf32>) { |
| ^bb(%0: f32, %1: f32) : |
| linalg.yield %0 : f32 |
| } |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @test_vectorize_fill |
| func @test_vectorize_fill(%A : memref<8x16xf32>, %arg0 : f32) { |
| // CHECK: %[[V:.*]] = vector.broadcast {{.*}} : f32 to vector<8x16xf32> |
| // CHECK: vector.transfer_write %[[V]], {{.*}} : vector<8x16xf32>, memref<8x16xf32> |
| linalg.fill(%arg0, %A) : f32, memref<8x16xf32> |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @test_vectorize_fill |
| func @test_vectorize_fill_scalar(%A : memref<f32>, %arg0 : f32) { |
| // CHECK-SAME: (%[[M:.*]]: memref<f32>, %[[val:.*]]: f32) |
| // CHECK: %[[VEC:.*]] = vector.broadcast %[[val]] : f32 to vector<1xf32> |
| // CHECK: vector.transfer_write %[[VEC]], %[[M]][] {{.*}} : vector<1xf32>, memref<f32> |
| linalg.fill(%arg0, %A) : f32, memref<f32> |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @test_vectorize_copy |
| func @test_vectorize_copy(%A : memref<8x16xf32>, %B : memref<8x16xf32>) { |
| // CHECK: %[[V:.*]] = vector.transfer_read {{.*}} : memref<8x16xf32>, vector<8x16xf32> |
| // CHECK: vector.transfer_write %[[V]], {{.*}} : vector<8x16xf32>, memref<8x16xf32> |
| linalg.copy(%A, %B) : memref<8x16xf32>, memref<8x16xf32> |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @test_vectorize_copy_scalar |
| func @test_vectorize_copy_scalar(%A : memref<f32>, %B : memref<f32>) { |
| // CHECK-SAME: (%[[A:.*]]: memref<f32>, %[[B:.*]]: memref<f32>) |
| // CHECK: %[[V:.*]] = vector.transfer_read %[[A]][]{{.*}} : memref<f32>, vector<1xf32> |
| // CHECK: %[[val:.*]] = vector.extract %[[V]][0] : vector<1xf32> |
| // CHECK: %[[VV:.*]] = vector.broadcast %[[val]] : f32 to vector<1xf32> |
| // CHECK: vector.transfer_write %[[VV]], %[[B]][] {{.*}} : vector<1xf32>, memref<f32> |
| linalg.copy(%A, %B) : memref<f32>, memref<f32> |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @test_vectorize_trailing_index |
| // CHECK-SAME: (%[[ARG0:.*]]: memref<1x2x4x8xindex>) |
| func @test_vectorize_trailing_index(%arg0: memref<1x2x4x8xindex>) { |
| // CHECK-DAG: %[[CST0:.*]] = arith.constant dense<[0, 1, 2, 3, 4, 5, 6, 7]> : vector<8xindex> |
| // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index |
| linalg.generic { |
| indexing_maps = [ |
| affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>], |
| iterator_types = ["parallel", "parallel", "parallel", "parallel"]} |
| outs(%arg0: memref<1x2x4x8xindex>) { |
| ^bb0(%arg1: index): |
| // CHECK: %[[BCST:.*]] = vector.broadcast %[[CST0]] : vector<8xindex> to vector<1x2x4x8xindex> |
| // CHECK: vector.transfer_write %[[BCST]], %[[ARG0]][%[[C0]], %[[C0]], %[[C0]], %[[C0]]] {{.*}} : vector<1x2x4x8xindex>, memref<1x2x4x8xindex> |
| %0 = linalg.index 3 : index |
| linalg.yield %0 : index |
| } |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @test_vectorize_inner_index |
| // CHECK-SAME: (%[[ARG0:.*]]: memref<1x2x4x8xindex>) |
| func @test_vectorize_inner_index(%arg0: memref<1x2x4x8xindex>) { |
| // CHECK-DAG: %[[CST0:.*]] = arith.constant dense<[0, 1]> : vector<2xindex> |
| // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index |
| linalg.generic { |
| indexing_maps = [ |
| affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>], |
| iterator_types = ["parallel", "parallel", "parallel", "parallel"]} |
| outs(%arg0: memref<1x2x4x8xindex>) { |
| ^bb0(%arg1: index): |
| // CHECK: %[[BCST:.*]] = vector.broadcast %[[CST0]] : vector<2xindex> to vector<1x8x4x2xindex> |
| // CHECK: %[[TRAN:.*]] = vector.transpose %[[BCST]], [0, 3, 2, 1] : vector<1x8x4x2xindex> to vector<1x2x4x8xindex> |
| // CHECK: vector.transfer_write %[[TRAN]], %[[ARG0]][%[[C0]], %[[C0]], %[[C0]], %[[C0]]] {{.*}} : vector<1x2x4x8xindex>, memref<1x2x4x8xindex> |
| %0 = linalg.index 1 : index |
| linalg.yield %0 : index |
| } |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @generic_vectorize |
| // CHECK-SAME: (%[[ARG0:.*]]: memref<4x256xf32>, %[[ARG1:.*]]: memref<4x256xf32>, |
| // CHECK-SAME: %[[ARG2:.*]]: memref<256xf32>, %[[ARG3:.*]]: f32) |
| func @generic_vectorize(%arg0: memref<4x256xf32>, |
| %arg1: memref<4x256xf32>, |
| %arg2: memref<256xf32>, %i: f32) { |
| // CHECK-DAG: %[[CST0:.*]] = arith.constant dense<2.000000e+00> : vector<4x256xf32> |
| // CHECK-DAG: %[[CST1:.*]] = arith.constant dense<1.000000e+00> : vector<4x256xf32> |
| // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index |
| %c1_f32 = arith.constant 1.0 : f32 |
| linalg.generic { |
| args_in = 0 : i64, |
| args_out = 10 : i64, |
| indexing_maps = [ |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%arg1, %arg2: memref<4x256xf32>, memref<256xf32>) |
| outs( |
| %arg0, %arg0, %arg0, %arg0, %arg0, %arg0, %arg0, %arg0, %arg0, %arg0 : |
| memref<4x256xf32>, memref<4x256xf32>, memref<4x256xf32>, memref<4x256xf32>, |
| memref<4x256xf32>, memref<4x256xf32>, memref<4x256xf32>, memref<4x256xf32>, |
| memref<4x256xf32>, memref<4x256xf32>) { |
| ^bb0(%arg3 : f32, %arg4 : f32, %arg5: f32, %arg6: f32, %arg7: f32, %arg8: f32, |
| // CHECK: %[[V2:.*]] = vector.transfer_read %[[ARG1]][%[[C0]], %[[C0]]], {{.*}} : memref<4x256xf32>, vector<4x256xf32> |
| // CHECK: %[[V0:.*]] = vector.transfer_read %[[ARG2]][%[[C0]]], {{.*}} : memref<256xf32>, vector<4x256xf32> |
| // CHECK: %[[V3:.*]] = vector.transfer_read %[[ARG0]][%[[C0]], %[[C0]]], {{.*}} : memref<4x256xf32>, vector<4x256xf32> |
| // CHECK: %[[V1:.*]] = vector.transfer_read %[[ARG0]][%[[C0]], %[[C0]]], {{.*}} : memref<4x256xf32>, vector<4x256xf32> |
| %arg9 : f32, %arg10 : f32, %arg11 : f32, %arg12 : f32, %arg13 : f32, |
| %arg14 : f32): |
| // CHECK: %[[ADD:.*]] = arith.addf %[[V0]], %[[V1]] : vector<4x256xf32> |
| %6 = arith.addf %arg4, %arg6 : f32 |
| // CHECK: %[[CMP:.*]] = arith.cmpf ogt, %[[V2]], %[[V1]] : vector<4x256xf32> |
| %7 = arith.cmpf ogt, %arg3, %arg6 : f32 |
| // CHECK: %[[ARG3B:.*]] = vector.broadcast %[[ARG3]] : f32 to vector<4x256xf32> |
| %8 = arith.constant 2.0 : f32 |
| // CHECK: %[[DIV:.*]] = arith.divf %[[V3]], %[[ARG3B]] : vector<4x256xf32> |
| %9 = arith.divf %arg5, %i : f32 |
| // CHECK: %[[EXP:.*]] = math.exp2 %[[V3]] : vector<4x256xf32> |
| %10 = math.exp2 %arg5 : f32 |
| // CHECK: %[[MUL:.*]] = arith.mulf %[[V3]], %[[CST0]] : vector<4x256xf32> |
| %11 = arith.mulf %arg5, %8 : f32 |
| // CHECK: %[[RSQRT:.*]] = math.rsqrt %[[V3]] : vector<4x256xf32> |
| %12 = math.rsqrt %arg5 : f32 |
| // CHECK: %[[SEL:.*]] = select %[[CMP]], %[[V3]], %[[V1]] : vector<4x256xi1>, vector<4x256xf32> |
| %13 = select %7, %arg5, %arg6 : f32 |
| // CHECK: %[[SUB:.*]] = arith.subf %[[V3]], %[[V0]] : vector<4x256xf32> |
| %14 = arith.subf %arg5, %arg4 : f32 |
| // CHECK: %[[TAN:.*]] = math.tanh %[[V3]] : vector<4x256xf32> |
| %15 = math.tanh %arg5 : f32 |
| // CHECK: vector.transfer_write %[[ADD]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, memref<4x256xf32> |
| // CHECK: vector.transfer_write %[[CST0]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, memref<4x256xf32> |
| // CHECK: vector.transfer_write %[[CST1]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, memref<4x256xf32> |
| // CHECK: vector.transfer_write %[[DIV]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, memref<4x256xf32> |
| // CHECK: vector.transfer_write %[[EXP]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, memref<4x256xf32> |
| // CHECK: vector.transfer_write %[[MUL]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, memref<4x256xf32> |
| // CHECK: vector.transfer_write %[[RSQRT]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, memref<4x256xf32> |
| // CHECK: vector.transfer_write %[[SEL]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, memref<4x256xf32> |
| // CHECK: vector.transfer_write %[[SUB]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, memref<4x256xf32> |
| // CHECK: vector.transfer_write %[[TAN]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, memref<4x256xf32> |
| linalg.yield %6, %8, %c1_f32, %9, %10, %11, %12, %13, %14, %15 : f32, f32, |
| f32, f32, f32, f32, f32, f32, f32, f32 |
| } |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @generic_vectorize_tensor |
| // CHECK-SAME: (%[[ARG0:.*]]: tensor<4x256xf32>, %[[ARG1:.*]]: tensor<4x256xf32>, |
| // CHECK-SAME: %[[ARG2:.*]]: tensor<256xf32>, %[[ARG3:.*]]: f32) |
| func @generic_vectorize_tensor(%arg0: tensor<4x256xf32>, |
| %arg1: tensor<4x256xf32>, %arg2: tensor<256xf32>, |
| %i: f32) -> (tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, |
| tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, |
| tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>) { |
| %c1_f32 = arith.constant 1.0 : f32 |
| %r:10 = linalg.generic { |
| indexing_maps = [ |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%arg1, %arg2: tensor<4x256xf32>, tensor<256xf32>) |
| outs( |
| %arg0, %arg0, %arg0, %arg0, %arg0, %arg0, %arg0, %arg0, %arg0, %arg0 : |
| tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, |
| tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, |
| tensor<4x256xf32>, tensor<4x256xf32>) { |
| ^bb0(%arg3 : f32, %arg4 : f32, %arg5: f32, %arg6: f32, %arg7: f32, %arg8: f32, |
| %arg9 : f32, %arg10 : f32, %arg11 : f32, %arg12 : f32, %arg13 : f32, |
| %arg14 : f32): |
| // CHECK-DAG: %[[CST0:.*]] = arith.constant dense<2.000000e+00> : vector<4x256xf32> |
| // CHECK-DAG: %[[CST1:.*]] = arith.constant dense<1.000000e+00> : vector<4x256xf32> |
| // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index |
| // CHECK: %[[V2:.*]] = vector.transfer_read %[[ARG1]][%[[C0]], %[[C0]]], {{.*}} : tensor<4x256xf32>, vector<4x256xf32> |
| // CHECK: %[[V0:.*]] = vector.transfer_read %[[ARG2]][%[[C0]]], {{.*}} : tensor<256xf32>, vector<4x256xf32> |
| // CHECK: %[[V3:.*]] = vector.transfer_read %[[ARG0]][%[[C0]], %[[C0]]], {{.*}} : tensor<4x256xf32>, vector<4x256xf32> |
| // CHECK: %[[V1:.*]] = vector.transfer_read %[[ARG0]][%[[C0]], %[[C0]]], {{.*}} : tensor<4x256xf32>, vector<4x256xf32> |
| // CHECK: %[[ADD:.*]] = arith.addf %[[V0]], %[[V1]] : vector<4x256xf32> |
| %6 = arith.addf %arg4, %arg6 : f32 |
| // CHECK: %[[CMP:.*]] = arith.cmpf ogt, %[[V2]], %[[V1]] : vector<4x256xf32> |
| %7 = arith.cmpf ogt, %arg3, %arg6 : f32 |
| // CHECK: %[[ARG3B:.*]] = vector.broadcast %[[ARG3]] : f32 to vector<4x256xf32> |
| %8 = arith.constant 2.0 : f32 |
| // CHECK: %[[DIV:.*]] = arith.divf %[[V3]], %[[ARG3B]] : vector<4x256xf32> |
| %9 = arith.divf %arg5, %i : f32 |
| // CHECK: %[[EXP:.*]] = math.exp2 %[[V3]] : vector<4x256xf32> |
| %10 = math.exp2 %arg5 : f32 |
| // CHECK: %[[MUL:.*]] = arith.mulf %[[V3]], %[[CST0]] : vector<4x256xf32> |
| %11 = arith.mulf %arg5, %8 : f32 |
| // CHECK: %[[RSQRT:.*]] = math.rsqrt %[[V3]] : vector<4x256xf32> |
| %12 = math.rsqrt %arg5 : f32 |
| // CHECK: %[[SEL:.*]] = select %[[CMP]], %[[V3]], %[[V1]] : vector<4x256xi1>, vector<4x256xf32> |
| %13 = select %7, %arg5, %arg6 : f32 |
| // CHECK: %[[SUB:.*]] = arith.subf %[[V3]], %[[V0]] : vector<4x256xf32> |
| %14 = arith.subf %arg5, %arg4 : f32 |
| // CHECK: %[[TAN:.*]] = math.tanh %[[V3]] : vector<4x256xf32> |
| %15 = math.tanh %arg5 : f32 |
| // CHECK: %[[R0:.*]] = vector.transfer_write %[[ADD]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, tensor<4x256xf32> |
| // CHECK: %[[R1:.*]] = vector.transfer_write %[[CST0]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, tensor<4x256xf32> |
| // CHECK: %[[R2:.*]] = vector.transfer_write %[[CST1]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, tensor<4x256xf32> |
| // CHECK: %[[R3:.*]] = vector.transfer_write %[[DIV]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, tensor<4x256xf32> |
| // CHECK: %[[R4:.*]] = vector.transfer_write %[[EXP]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, tensor<4x256xf32> |
| // CHECK: %[[R5:.*]] = vector.transfer_write %[[MUL]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, tensor<4x256xf32> |
| // CHECK: %[[R6:.*]] = vector.transfer_write %[[RSQRT]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, tensor<4x256xf32> |
| // CHECK: %[[R7:.*]] = vector.transfer_write %[[SEL]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, tensor<4x256xf32> |
| // CHECK: %[[R8:.*]] = vector.transfer_write %[[SUB]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, tensor<4x256xf32> |
| // CHECK: %[[R9:.*]] = vector.transfer_write %[[TAN]], %[[ARG0]][%[[C0]], %[[C0]]] {{.*}} : vector<4x256xf32>, tensor<4x256xf32> |
| linalg.yield %6, %8, %c1_f32, %9, %10, %11, %12, %13, %14, %15 : f32, f32, |
| f32, f32, f32, f32, f32, f32, f32, f32 |
| } -> (tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, |
| tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, |
| tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>) |
| // CHECK: return %[[R0]], %[[R1]], %[[R2]], %[[R3]], %[[R4]], %[[R5]], %[[R6]], %[[R7]], %[[R8]], %[[R9]] : tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32> |
| return %r#0, %r#1, %r#2, %r#3, %r#4, %r#5, %r#6, %r#7, %r#8, %r#9: |
| tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, |
| tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32>, |
| tensor<4x256xf32>, tensor<4x256xf32>, tensor<4x256xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-DAG: #[[$MAP0:.*]] = affine_map<(d0, d1) -> (d0, 0, 0, d1)> |
| // CHECK-DAG: #[[$MAP1:.*]] = affine_map<(d0) -> (d0, 0, 0, 0)> |
| // CHECK-DAG: #[[$MAP2:.*]] = affine_map<(d0) -> (0, 0, d0, 0)> |
| // CHECK-DAG: #[[$MAP3:.*]] = affine_map<(d0, d1) -> (d1, 0, d0, 0)> |
| // CHECK: func @generic_vectorize_broadcast_transpose |
| // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index |
| // CHECK-DAG: %[[CF:.*]] = arith.constant 0.000000e+00 : f32 |
| // CHECK: %[[V0:.*]] = vector.transfer_read %{{.*}}[%[[C0]], %[[C0]]], %[[CF]] {in_bounds = [true, true, true, true], permutation_map = #[[$MAP0]]} : memref<4x4xf32>, vector<4x4x4x4xf32> |
| // CHECK: %[[V1:.*]] = vector.transfer_read %{{.*}}[%[[C0]]], %[[CF]] {in_bounds = [true, true, true, true], permutation_map = #[[$MAP1]]} : memref<4xf32>, vector<4x4x4x4xf32> |
| // CHECK: %[[V2:.*]] = vector.transfer_read %{{.*}}[%[[C0]]], %[[CF]] {in_bounds = [true, true, true, true], permutation_map = #[[$MAP2]]} : memref<4xf32>, vector<4x4x4x4xf32> |
| // CHECK: %[[V3:.*]] = vector.transfer_read %{{.*}}[%[[C0]], %[[C0]]], %[[CF]] {in_bounds = [true, true, true, true], permutation_map = #[[$MAP3]]} : memref<4x4xf32>, vector<4x4x4x4xf32> |
| // CHECK: %[[SUB:.*]] = arith.subf %[[V0]], %[[V1]] : vector<4x4x4x4xf32> |
| // CHECK: %[[ADD0:.*]] = arith.addf %[[V2]], %[[SUB]] : vector<4x4x4x4xf32> |
| // CHECK: %[[ADD1:.*]] = arith.addf %[[V3]], %[[ADD0]] : vector<4x4x4x4xf32> |
| // CHECK: vector.transfer_write %[[ADD1]], {{.*}} : vector<4x4x4x4xf32>, memref<4x4x4x4xf32> |
| func @generic_vectorize_broadcast_transpose( |
| %A: memref<4xf32>, %B: memref<4x4xf32>, %C: memref<4x4x4x4xf32>) { |
| linalg.generic { |
| indexing_maps = [affine_map<(d0, d1, d2, d3) -> (d0, d3)>, |
| affine_map<(d0, d1, d2, d3) -> (d0)>, |
| affine_map<(d0, d1, d2, d3) -> (d2)>, |
| affine_map<(d0, d1, d2, d3) -> (d2, d0)>, |
| affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>], |
| iterator_types = ["parallel", "parallel", "parallel", "parallel"]} |
| ins(%B, %A, %A, %B: memref<4x4xf32>, memref<4xf32>, memref<4xf32>, memref<4x4xf32>) |
| outs(%C : memref<4x4x4x4xf32>) { |
| ^bb0(%arg0: f32, %arg1: f32, %arg2: f32, %arg3: f32, %arg4: f32): // no predecessors |
| %s = arith.subf %arg0, %arg1 : f32 |
| %a = arith.addf %arg2, %s : f32 |
| %b = arith.addf %arg3, %a : f32 |
| linalg.yield %b : f32 |
| } |
| return |
| } |
| |
| // ----- |
| |
| // Test different input maps. |
| #matmul_trait = { |
| indexing_maps = [ |
| affine_map<(d0, d1, d2, d3) -> (d1, d0)>, |
| affine_map<(d0, d1, d2, d3) -> (d3, d1)>, |
| affine_map<(d0, d1, d2, d3) -> (d3, d1, d0, d2)>, |
| affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| ], |
| iterator_types = ["parallel", "parallel", "parallel", "parallel"] |
| } |
| |
| // CHECK-DAG: #[[MAP0:.*]] = affine_map<(d0, d1) -> (d1, d0, 0, 0)> |
| // CHECK-DAG: #[[MAP1:.*]] = affine_map<(d0, d1) -> (0, d1, 0, d0)> |
| // CHECK-DAG: #[[MAP2:.*]] = affine_map<(d0, d1, d2, d3) -> (d2, d1, d3, d0)> |
| // CHECK: func @vectorization_transpose |
| // CHECK: vector.transfer_read {{.*}}{in_bounds = [true, true, true, true], permutation_map = #[[MAP0]]} : memref<14x7xf32>, vector<7x14x8x16xf32> |
| // CHECK: vector.transfer_read {{.*}}{in_bounds = [true, true, true, true], permutation_map = #[[MAP1]]} : memref<16x14xf32>, vector<7x14x8x16xf32> |
| // CHECK: vector.transfer_read {{.*}}{in_bounds = [true, true, true, true], permutation_map = #[[MAP2]]} : memref<16x14x7x8xf32>, vector<7x14x8x16xf32> |
| // CHECK: arith.addf {{.*}} : vector<7x14x8x16xf32> |
| // CHECK: arith.addf {{.*}} : vector<7x14x8x16xf32> |
| // CHECK: vector.transfer_write {{.*}} : vector<7x14x8x16xf32>, memref<7x14x8x16xf32> |
| func @vectorization_transpose(%A: memref<14x7xf32>, %B: memref<16x14xf32>, |
| %C: memref<16x14x7x8xf32>, %D: memref<7x14x8x16xf32>) { |
| linalg.generic #matmul_trait |
| ins(%A, %B, %C : memref<14x7xf32>, memref<16x14xf32>, memref<16x14x7x8xf32>) |
| outs(%D : memref<7x14x8x16xf32>) { |
| ^bb(%a: f32, %b: f32, %c: f32, %d: f32) : |
| %e = arith.addf %a, %b: f32 |
| %f = arith.addf %e, %c: f32 |
| linalg.yield %f : f32 |
| } |
| return |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @matmul_tensors |
| // CHECK-SAME: (%[[ARG0:.*]]: tensor<8x4xf32>, %[[ARG1:.*]]: tensor<4x12xf32>, |
| // CHECK-SAME: %[[ARG2:.*]]: tensor<8x12xf32>) -> tensor<8x12xf32> |
| func @matmul_tensors( |
| %arg0: tensor<8x4xf32>, %arg1: tensor<4x12xf32>, %arg2: tensor<8x12xf32>) |
| -> tensor<8x12xf32> { |
| // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index |
| // CHECK-DAG: %[[V0:.*]] = vector.transfer_read %[[ARG0]][%[[C0]], %[[C0]]], {{.*}} : tensor<8x4xf32>, vector<8x12x4xf32> |
| // CHECK-DAG: %[[V1:.*]] = vector.transfer_read %[[ARG1]][%[[C0]], %[[C0]]], {{.*}} : tensor<4x12xf32>, vector<8x12x4xf32> |
| // CHECK-DAG: %[[V2:.*]] = vector.transfer_read %[[ARG2]][%[[C0]], %[[C0]]], {{.*}} : tensor<8x12xf32>, vector<8x12xf32> |
| // |
| // linalg matmul lowers gets expanded to a 3D reduction, canonicalization later |
| // convert it to a 2D contract. |
| // CHECK: %[[MUL:.*]] = arith.mulf %[[V0]], %[[V1]] : vector<8x12x4xf32> |
| // CHECK: %[[R:.*]] = vector.multi_reduction #vector.kind<add>, %[[MUL]] [2] : vector<8x12x4xf32> to vector<8x12xf32> |
| // CHECK: %[[ADD:.*]] = arith.addf %[[R]], %[[V2]] : vector<8x12xf32> |
| // CHECK: %[[W:.*]] = vector.transfer_write %[[ADD]], %[[ARG2]][%[[C0]], %[[C0]]] {in_bounds = [true, true]} : vector<8x12xf32>, tensor<8x12xf32> |
| %0 = linalg.matmul ins(%arg0, %arg1: tensor<8x4xf32>, tensor<4x12xf32>) |
| outs(%arg2: tensor<8x12xf32>) |
| -> tensor<8x12xf32> |
| // CHECK: return %[[W]] : tensor<8x12xf32> |
| return %0 : tensor<8x12xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @pad_static( |
| // CHECK-SAME: %[[ARG0:.*]]: tensor<2x?x2xf32>, %[[PAD:.*]]: f32 |
| // CHECK-NOT: linalg.pad_tensor |
| // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index |
| // CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index |
| // CHECK-DAG: %[[INIT:.*]] = linalg.init_tensor [2, 3, 4] : tensor<2x3x4xf32> |
| // CHECK-DAG: %[[VEC:.*]] = vector.broadcast %[[PAD]] : f32 to vector<2x3x4xf32> |
| // CHECK: %[[FILL:.*]] = vector.transfer_write %[[VEC]], %[[INIT]]{{.*}} : vector<2x3x4xf32>, tensor<2x3x4xf32> |
| // CHECK: %[[READ:.*]] = vector.transfer_read %[[ARG0]][%[[C0]], %[[C0]], %[[C0]]], %[[PAD]] {in_bounds = [true, false, true]} : tensor<2x?x2xf32>, vector<2x3x2xf32> |
| // CHECK: %[[RESULT:.*]] = vector.transfer_write %[[READ]], %[[FILL]][%[[C0]], %[[C0]], %[[C2]]] {in_bounds = [true, true, true]} : vector<2x3x2xf32>, tensor<2x3x4xf32> |
| // CHECK: return %[[RESULT]] |
| func @pad_static(%arg0: tensor<2x?x2xf32>, %pad_value: f32) -> tensor<2x3x4xf32> { |
| %0 = linalg.pad_tensor %arg0 low[0, 0, 2] high[0, 1, 0] { |
| ^bb0(%arg1: index, %arg2: index, %arg3: index): |
| linalg.yield %pad_value : f32 |
| } : tensor<2x?x2xf32> to tensor<2x3x4xf32> |
| return %0 : tensor<2x3x4xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @pad_static_source( |
| // CHECK-SAME: %[[ARG0:.*]]: tensor<2x5x2xf32>, %[[PAD:.*]]: f32 |
| // CHECK-NOT: linalg.pad_tensor |
| // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index |
| // CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index |
| // CHECK: %[[INIT:.*]] = linalg.init_tensor [2, 6, 4] : tensor<2x6x4xf32> |
| // CHECK: %[[VEC:.*]] = vector.broadcast %[[PAD]] : f32 to vector<2x6x4xf32> |
| // CHECK: %[[FILL:.*]] = vector.transfer_write %[[VEC]], %[[INIT]][%[[C0]], %[[C0]], %[[C0]]] {in_bounds = [true, true, true]} : vector<2x6x4xf32>, tensor<2x6x4xf32> |
| // CHECK: %[[READ:.*]] = vector.transfer_read %[[ARG0]][%[[C0]], %[[C0]], %[[C0]]], %{{.*}} {in_bounds = [true, true, true]} : tensor<2x5x2xf32>, vector<2x5x2xf32> |
| // CHECK: %[[WRITE:.*]] = vector.transfer_write %[[READ]], %[[FILL]][%[[C0]], %[[C0]], %[[C2]]] {in_bounds = [true, true, true]} : vector<2x5x2xf32>, tensor<2x6x4xf32> |
| // CHECK: return %[[WRITE]] |
| func @pad_static_source(%arg0: tensor<2x5x2xf32>, %pad_value: f32) -> tensor<2x6x4xf32> { |
| %0 = linalg.pad_tensor %arg0 low[0, 0, 2] high[0, 1, 0] { |
| ^bb0(%arg1: index, %arg2: index, %arg3: index): |
| linalg.yield %pad_value : f32 |
| } : tensor<2x5x2xf32> to tensor<2x6x4xf32> |
| return %0 : tensor<2x6x4xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @pad_static_dynamic( |
| // CHECK-SAME: %[[SRC:.*]]: tensor<1x2x2x?xf32>, %[[LOW:.*]]: index, %[[HIGH:.*]]: index |
| // CHECK-NOT: linalg.pad_tensor |
| // CHECK-DAG: %[[C2:.*]] = arith.constant 2 : index |
| // CHECK-DAG: %[[C3:.*]] = arith.constant 3 : index |
| // CHECK-DAG: %[[C5:.*]] = arith.constant 5 : index |
| // CHECK: %[[V0:.*]] = arith.addi %[[LOW]], %[[C2]] : index |
| // CHECK: %[[V1:.*]] = arith.addi %[[V0]], %[[C3]] : index |
| // CHECK: %[[V2:.*]] = arith.addi %[[HIGH]], %[[C5]] : index |
| // CHECK: %[[DIM3:.*]] = tensor.dim %[[SRC]], %[[C3]] : tensor<1x2x2x?xf32> |
| // CHECK: %[[V4:.*]] = arith.addi %[[DIM3]], %[[C3]] : index |
| // CHECK: %[[V5:.*]] = arith.addi %[[V4]], %[[C2]] : index |
| // CHECK: %[[INIT:.*]] = linalg.init_tensor [6, %[[V1]], %[[V2]], %[[V5]]] : tensor<6x?x?x?xf32> |
| // CHECK: %[[FILL:.*]] = linalg.fill(%{{.*}}, %[[INIT]]) : f32, tensor<6x?x?x?xf32> -> tensor<6x?x?x?xf32> |
| // CHECK: %[[SRCDIM:.*]] = tensor.dim %[[SRC]], %[[C3]] : tensor<1x2x2x?xf32> |
| // CHECK: %[[RESULT:.*]] = tensor.insert_slice %[[SRC]] into %[[FILL]][2, %[[LOW]], 3, 3] [1, 2, 2, %[[SRCDIM]]] [1, 1, 1, 1] : tensor<1x2x2x?xf32> into tensor<6x?x?x?xf32> |
| // CHECK: return %[[RESULT]] |
| func @pad_static_dynamic(%arg0: tensor<1x2x2x?xf32>, %low: index, %high: index, |
| %pad_value: f32) -> tensor<6x?x?x?xf32> { |
| %0 = linalg.pad_tensor %arg0 low[2, %low, 3, 3] high[3, 3, %high, 2] { |
| ^bb0(%arg1: index, %arg2: index, %arg3: index, %arg4: index): |
| linalg.yield %pad_value : f32 |
| } : tensor<1x2x2x?xf32> to tensor<6x?x?x?xf32> |
| return %0 : tensor<6x?x?x?xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @pad_and_transfer_read |
| // CHECK-SAME: %[[ARG0:.*]]: tensor<5x6xf32> |
| // CHECK-NOT: linalg.pad_tensor |
| // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index |
| // CHECK-DAG: %[[C5:.*]] = arith.constant 5.0 |
| // CHECK: %[[RESULT:.*]] = vector.transfer_read %[[ARG0]][%[[C0]], %[[C0]]], %[[C5]] : tensor<5x6xf32>, vector<7x9xf32> |
| // CHECK: return %[[RESULT]] |
| func @pad_and_transfer_read(%arg0: tensor<5x6xf32>) -> vector<7x9xf32> { |
| %c0 = arith.constant 0 : index |
| %c5 = arith.constant 5.0 : f32 |
| %c6 = arith.constant 6.0 : f32 |
| %0 = linalg.pad_tensor %arg0 low[0, 0] high[5, 7] { |
| ^bb0(%arg1: index, %arg2: index): |
| linalg.yield %c5 : f32 |
| } : tensor<5x6xf32> to tensor<10x13xf32> |
| %1 = vector.transfer_read %0[%c0, %c0], %c6 |
| : tensor<10x13xf32>, vector<7x9xf32> |
| return %1 : vector<7x9xf32> |
| } |
| |
| // ----- |
| |
| func private @make_vector() -> vector<7x9xf32> |
| |
| // CHECK-LABEL: func @pad_and_transfer_write_static |
| // CHECK-SAME: %[[ARG0:.*]]: tensor<5x6xf32> |
| // CHECK-NOT: linalg.pad_tensor |
| // CHECK: %[[C0:.*]] = arith.constant 0 : index |
| // CHECK: %[[VEC0:.*]] = call @make_vector() : () -> vector<7x9xf32> |
| // CHECK: %[[RESULT:.*]] = vector.transfer_write %[[VEC0]], %[[ARG0]][%[[C0]], %[[C0]]] : vector<7x9xf32>, tensor<5x6xf32> |
| // CHECK: return %[[RESULT]] |
| func @pad_and_transfer_write_static( |
| %arg0: tensor<5x6xf32>) -> tensor<5x6xf32> { |
| %c0 = arith.constant 0 : index |
| %c5 = arith.constant 5.0 : f32 |
| %0 = linalg.pad_tensor %arg0 low[0, 0] high[5, 7] { |
| ^bb0(%arg2: index, %arg3: index): |
| linalg.yield %c5 : f32 |
| } : tensor<5x6xf32> to tensor<10x13xf32> |
| %1 = call @make_vector() : () -> vector<7x9xf32> |
| %2 = vector.transfer_write %1, %0[%c0, %c0] |
| : vector<7x9xf32>, tensor<10x13xf32> |
| %3 = tensor.extract_slice %2[0, 0] [5, 6] [1, 1] : tensor<10x13xf32> to tensor<5x6xf32> |
| return %3 : tensor<5x6xf32> |
| } |
| |
| // ----- |
| |
| func private @make_vector() -> vector<7x9xf32> |
| |
| // CHECK-LABEL: func @pad_and_transfer_write_dynamic_static |
| // CHECK-SAME: %[[ARG0:.*]]: tensor<?x?xf32>, %[[SIZE:.*]]: index, %[[PADDING:.*]]: index |
| // CHECK-NOT: linalg.pad_tensor |
| // CHECK: %[[C0:.*]] = arith.constant 0 : index |
| // CHECK: %[[SUB:.*]] = tensor.extract_slice %[[ARG0]][0, 0] [%[[SIZE]], 6] [1, 1] : tensor<?x?xf32> to tensor<?x6xf32> |
| // CHECK: %[[VEC0:.*]] = call @make_vector() : () -> vector<7x9xf32> |
| // CHECK: %[[RESULT:.*]] = vector.transfer_write %[[VEC0]], %[[SUB]][%[[C0]], %[[C0]]] : vector<7x9xf32>, tensor<?x6xf32> |
| // CHECK: return %[[RESULT]] |
| func @pad_and_transfer_write_dynamic_static( |
| %arg0: tensor<?x?xf32>, %size: index, %padding: index) -> tensor<?x6xf32> { |
| %c0 = arith.constant 0 : index |
| %c5 = arith.constant 5.0 : f32 |
| %s = tensor.extract_slice %arg0[0, 0] [%size, 6] [1, 1] |
| : tensor<?x?xf32> to tensor<?x6xf32> |
| %0 = linalg.pad_tensor %s low[0, 0] high[%padding, 7] { |
| ^bb0(%arg2: index, %arg3: index): |
| linalg.yield %c5 : f32 |
| } : tensor<?x6xf32> to tensor<?x13xf32> |
| %1 = call @make_vector() : () -> vector<7x9xf32> |
| %2 = vector.transfer_write %1, %0[%c0, %c0] |
| : vector<7x9xf32>, tensor<?x13xf32> |
| %3 = tensor.extract_slice %2[0, 0] [%size, 6] [1, 1] : tensor<?x13xf32> to tensor<?x6xf32> |
| return %3 : tensor<?x6xf32> |
| } |
| |
| // ----- |
| |
| func private @make_vector() -> tensor<12x13xf32> |
| |
| // CHECK-LABEL: func @pad_and_insert_slice |
| // CHECK-SAME: %[[ARG0:.*]]: tensor<5x6xf32> |
| // CHECK-NOT: linalg.pad_tensor |
| // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index |
| // CHECK-DAG: %[[C5:.*]] = arith.constant 5.0 |
| // CHECK: %[[VEC0:.*]] = call @make_vector() : () -> tensor<12x13xf32> |
| // CHECK: %[[READ:.*]] = vector.transfer_read %[[ARG0]][%[[C0]], %[[C0]]], %[[C5]] : tensor<5x6xf32>, vector<7x9xf32> |
| // CHECK: %[[WRITE:.*]] = vector.transfer_write %[[READ]], %[[VEC0]][%[[C0]], %[[C0]]] {in_bounds = [true, true]} : vector<7x9xf32>, tensor<12x13xf32> |
| // CHECK: return %[[WRITE]] |
| func @pad_and_insert_slice( |
| %arg0: tensor<5x6xf32>) -> tensor<12x13xf32> { |
| %c0 = arith.constant 0 : index |
| %c5 = arith.constant 5.0 : f32 |
| %0 = linalg.pad_tensor %arg0 low[0, 0] high[2, 3] { |
| ^bb0(%arg2: index, %arg3: index): |
| linalg.yield %c5 : f32 |
| } : tensor<5x6xf32> to tensor<7x9xf32> |
| %1 = call @make_vector() : () -> tensor<12x13xf32> |
| %r = tensor.insert_slice %0 into %1[0, 0][7, 9][1, 1] : tensor<7x9xf32> into tensor<12x13xf32> |
| return %r : tensor<12x13xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @pad_tensor_non_const_pad_value |
| // CHECK-SAME: %[[ARG0:.*]]: tensor<5x6xf32> |
| // CHECK-NOT: linalg.pad_tensor |
| // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index |
| // CHECK-DAG: %[[C3:.*]] = arith.constant 3 : index |
| // CHECK-DAG: %[[C4:.*]] = arith.constant 4 : index |
| // CHECK: %[[FILL:.*]] = tensor.generate |
| // CHECK: %[[RES:.*]] = arith.mulf |
| // CHECK: tensor.yield %[[RES]] : f32 |
| // CHECK: %[[READ:.*]] = vector.transfer_read %[[ARG0]][%[[C0]], %[[C0]]], %{{.*}} {in_bounds = [true, true]} : tensor<5x6xf32>, vector<5x6xf32> |
| // CHECK: %[[WRITE:.*]] = vector.transfer_write %[[READ]], %[[FILL]][%[[C3]], %[[C4]]] {in_bounds = [true, true]} : vector<5x6xf32>, tensor<12x13xf32> |
| // CHECK: return %[[WRITE]] |
| func @pad_tensor_non_const_pad_value(%arg0: tensor<5x6xf32>) -> tensor<12x13xf32> { |
| %c0 = arith.constant 0 : index |
| %c5 = arith.constant 5.0 : f32 |
| %0 = linalg.pad_tensor %arg0 low[3, 4] high[4, 3] { |
| ^bb0(%arg1: index, %arg2: index): |
| %i1 = arith.index_cast %arg1 : index to i32 |
| %i2 = arith.index_cast %arg2 : index to i32 |
| %f1 = arith.sitofp %i1 : i32 to f32 |
| %f2 = arith.sitofp %i2 : i32 to f32 |
| %m = arith.mulf %f1, %f2 : f32 |
| linalg.yield %m : f32 |
| } : tensor<5x6xf32> to tensor<12x13xf32> |
| return %0 : tensor<12x13xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @sum_exp |
| func @sum_exp(%input: tensor<4x16x8xf32>, %output: tensor<4x16xf32>) |
| -> tensor<4x16xf32> |
| { |
| // CHECK: vector.transfer_read {{.*}} : tensor<4x16x8xf32>, vector<4x16x8xf32> |
| // CHECK: vector.transfer_read {{.*}} {in_bounds = [true, true]} : tensor<4x16xf32>, vector<4x16xf32> |
| // CHECK: math.exp {{.*}} : vector<4x16x8xf32> |
| // CHECK: vector.multi_reduction #vector.kind<add>, %{{.*}} [2] : vector<4x16x8xf32> to vector<4x16xf32> |
| // CHECK: addf {{.*}} : vector<4x16xf32> |
| // CHECK: vector.transfer_write {{.*}} : vector<4x16xf32>, tensor<4x16xf32> |
| // CHECK: return {{.*}} : tensor<4x16xf32> |
| %0 = linalg.generic { |
| indexing_maps = [ |
| affine_map<(d0, d1, d2) -> (d0, d1, d2)>, |
| affine_map<(d0, d1, d2) -> (d0, d1)> |
| ], |
| iterator_types = ["parallel", "parallel", "reduction"] |
| } ins(%input : tensor<4x16x8xf32>) outs(%output : tensor<4x16xf32>) { |
| ^bb0(%arg0: f32, %arg1: f32): // no predecessors |
| %1 = math.exp %arg0 : f32 |
| %2 = arith.addf %1, %arg1 : f32 |
| linalg.yield %2 : f32 |
| } -> tensor<4x16xf32> |
| return %0 : tensor<4x16xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-DAG: #[[$M1:.*]] = affine_map<(d0, d1) -> (d1, d0, 0, 0)> |
| // CHECK-DAG: #[[$M2:.*]] = affine_map<(d0, d1) -> (0, 0, d1, d0)> |
| // CHECK-DAG: #[[$M3:.*]] = affine_map<(d0, d1) -> (d1, d0)> |
| |
| // CHECK-LABEL: func @sum_exp_2 |
| func @sum_exp_2(%input: tensor<3x2xf32>, %input_2: tensor<5x4xf32>, %output: tensor<5x2xf32>) |
| -> tensor<5x2xf32> |
| { |
| // CHECK: vector.transfer_read {{.*}} {in_bounds = [true, true, true, true], permutation_map = #[[$M1]]} : tensor<3x2xf32>, vector<2x3x4x5xf32> |
| // CHECK: vector.transfer_read {{.*}} {in_bounds = [true, true, true, true], permutation_map = #[[$M2]]} : tensor<5x4xf32>, vector<2x3x4x5xf32> |
| // CHECK: vector.transfer_read {{.*}} {in_bounds = [true, true], permutation_map = #[[$M3]]} : tensor<5x2xf32>, vector<2x5xf32> |
| // CHECK: math.exp {{.*}} : vector<2x3x4x5xf32> |
| // CHECK: math.exp {{.*}} : vector<2x3x4x5xf32> |
| // CHECK: addf {{.*}} : vector<2x3x4x5xf32> |
| // CHECK: vector.multi_reduction #vector.kind<add>, {{.*}} [1, 2] : vector<2x3x4x5xf32> to vector<2x5xf32> |
| // CHECK: addf {{.*}} : vector<2x5xf32> |
| // CHECK: vector.transfer_write {{.*}} {in_bounds = [true, true], permutation_map = #[[$M3]]} : vector<2x5xf32>, tensor<5x2xf32> |
| // CHECK: return {{.*}} : tensor<5x2xf32> |
| %0 = linalg.generic { |
| indexing_maps = [ |
| affine_map<(d0, d1, d2, d3) -> (d1, d0)>, |
| affine_map<(d0, d1, d2, d3) -> (d3, d2)>, |
| affine_map<(d0, d1, d2, d3) -> (d3, d0)> |
| ], |
| iterator_types = ["parallel", "reduction", "reduction", "parallel"] |
| } ins(%input, %input_2 : tensor<3x2xf32>, tensor<5x4xf32>) outs(%output : tensor<5x2xf32>) { |
| ^bb0(%arg0: f32, %arg1: f32, %arg2: f32): // no predecessors |
| %1 = math.exp %arg0 : f32 |
| %2 = math.exp %arg1 : f32 |
| %3 = arith.addf %1, %2 : f32 |
| %4 = arith.addf %3, %arg2 : f32 |
| linalg.yield %4 : f32 |
| } -> tensor<5x2xf32> |
| return %0 : tensor<5x2xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @red_max_2d( |
| func @red_max_2d(%arg0: tensor<4x4xf32>) -> tensor<4xf32> { |
| // CHECK: %[[CMINF:.+]] = arith.constant dense<-3.402820e+38> : vector<4xf32> |
| // CHECK: linalg.init_tensor [4] : tensor<4xf32> |
| // CHECK: vector.transfer_write {{.*}} : vector<4xf32>, tensor<4xf32> |
| // CHECK: %[[R:.+]] = vector.multi_reduction #vector.kind<maxf>, {{.*}} [1] : vector<4x4xf32> to vector<4xf32> |
| // CHECK: maxf %[[R]], %[[CMINF]] : vector<4xf32> |
| // CHECK: vector.transfer_write {{.*}} : vector<4xf32>, tensor<4xf32> |
| %ident = arith.constant -3.40282e+38 : f32 |
| %init = linalg.init_tensor [4] : tensor<4xf32> |
| %fill = linalg.fill(%ident, %init) : f32, tensor<4xf32> -> tensor<4xf32> |
| %red = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0)>], |
| iterator_types = ["parallel", "reduction"]} |
| ins(%arg0 : tensor<4x4xf32>) outs(%fill : tensor<4xf32>) { |
| ^bb0(%in0: f32, %out0: f32): // no predecessors |
| %max = arith.maxf %in0, %out0 : f32 |
| linalg.yield %max : f32 |
| } -> tensor<4xf32> |
| return %red : tensor<4xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @red_min_2d( |
| func @red_min_2d(%arg0: tensor<4x4xf32>) -> tensor<4xf32> { |
| // CHECK: %[[CMAXF:.+]] = arith.constant dense<3.402820e+38> : vector<4xf32> |
| // CHECK: linalg.init_tensor [4] : tensor<4xf32> |
| // CHECK: vector.transfer_write {{.*}} : vector<4xf32>, tensor<4xf32> |
| // CHECK: vector.transfer_read {{.*}} : tensor<4x4xf32>, vector<4x4xf32> |
| // CHECK: %[[R:.+]] = vector.multi_reduction #vector.kind<minf>, {{.*}} [1] : vector<4x4xf32> to vector<4xf32> |
| // CHECK: arith.minf %[[R]], %[[CMAXF]] : vector<4xf32> |
| // CHECK: vector.transfer_write {{.*}} : vector<4xf32>, tensor<4xf32> |
| %maxf32 = arith.constant 3.40282e+38 : f32 |
| %init = linalg.init_tensor [4] : tensor<4xf32> |
| %fill = linalg.fill(%maxf32, %init) : f32, tensor<4xf32> -> tensor<4xf32> |
| %red = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0)>], |
| iterator_types = ["parallel", "reduction"]} |
| ins(%arg0 : tensor<4x4xf32>) outs(%fill : tensor<4xf32>) { |
| ^bb0(%in0: f32, %out0: f32): // no predecessors |
| %min = arith.minf %out0, %in0 : f32 |
| linalg.yield %min : f32 |
| } -> tensor<4xf32> |
| return %red : tensor<4xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @red_mul_2d( |
| func @red_mul_2d(%arg0: tensor<4x4xf32>) -> tensor<4xf32> { |
| // CHECK: linalg.init_tensor [4] : tensor<4xf32> |
| // CHECK: vector.transfer_write {{.*}} : vector<4xf32>, tensor<4xf32> |
| // CHECK: vector.transfer_read {{.*}} : tensor<4x4xf32>, vector<4x4xf32> |
| // CHECK: vector.multi_reduction #vector.kind<mul>, {{.*}} [1] : vector<4x4xf32> to vector<4xf32> |
| // CHECK: mulf {{.*}} : vector<4xf32> |
| // CHECK: vector.transfer_write {{.*}} : vector<4xf32>, tensor<4xf32> |
| %ident = arith.constant 1.0 : f32 |
| %init = linalg.init_tensor [4] : tensor<4xf32> |
| %fill = linalg.fill(%ident, %init) : f32, tensor<4xf32> -> tensor<4xf32> |
| %red = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0)>], |
| iterator_types = ["parallel", "reduction"]} |
| ins(%arg0 : tensor<4x4xf32>) outs(%fill : tensor<4xf32>) { |
| ^bb0(%in0: f32, %out0: f32): // no predecessors |
| %mul = arith.mulf %in0, %out0 : f32 |
| linalg.yield %mul : f32 |
| } -> tensor<4xf32> |
| return %red : tensor<4xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @red_or_2d( |
| func @red_or_2d(%arg0: tensor<4x4xi1>) -> tensor<4xi1> { |
| // CHECK: linalg.init_tensor [4] : tensor<4xi1> |
| // CHECK: vector.transfer_write {{.*}} : vector<4xi1>, tensor<4xi1> |
| // CHECK: vector.transfer_read {{.*}} : tensor<4x4xi1>, vector<4x4xi1> |
| // CHECK: vector.multi_reduction #vector.kind<or>, {{.*}} [1] : vector<4x4xi1> to vector<4xi1> |
| // CHECK: vector.transfer_write {{.*}} : vector<4xi1>, tensor<4xi1> |
| %ident = arith.constant false |
| %init = linalg.init_tensor [4] : tensor<4xi1> |
| %fill = linalg.fill(%ident, %init) : i1, tensor<4xi1> -> tensor<4xi1> |
| %red = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0)>], |
| iterator_types = ["parallel", "reduction"]} |
| ins(%arg0 : tensor<4x4xi1>) outs(%fill : tensor<4xi1>) { |
| ^bb0(%in0: i1, %out0: i1): // no predecessors |
| %or = arith.ori %in0, %out0 : i1 |
| linalg.yield %or : i1 |
| } -> tensor<4xi1> |
| return %red : tensor<4xi1> |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @red_and_2d( |
| func @red_and_2d(%arg0: tensor<4x4xi1>) -> tensor<4xi1> { |
| // CHECK: linalg.init_tensor [4] : tensor<4xi1> |
| // CHECK: vector.transfer_write {{.*}} : vector<4xi1>, tensor<4xi1> |
| // CHECK: vector.transfer_read {{.*}} : tensor<4x4xi1>, vector<4x4xi1> |
| // CHECK: vector.multi_reduction #vector.kind<and>, {{.*}} [1] : vector<4x4xi1> to vector<4xi1> |
| // CHECK: vector.transfer_write {{.*}} : vector<4xi1>, tensor<4xi1> |
| %ident = arith.constant true |
| %init = linalg.init_tensor [4] : tensor<4xi1> |
| %fill = linalg.fill(%ident, %init) : i1, tensor<4xi1> -> tensor<4xi1> |
| %red = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0)>], |
| iterator_types = ["parallel", "reduction"]} |
| ins(%arg0 : tensor<4x4xi1>) outs(%fill : tensor<4xi1>) { |
| ^bb0(%in0: i1, %out0: i1): // no predecessors |
| %and = arith.andi %in0, %out0 : i1 |
| linalg.yield %and : i1 |
| } -> tensor<4xi1> |
| return %red : tensor<4xi1> |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @red_xor_2d( |
| func @red_xor_2d(%arg0: tensor<4x4xi1>) -> tensor<4xi1> { |
| // CHECK: linalg.init_tensor [4] : tensor<4xi1> |
| // CHECK: vector.transfer_write {{.*}} : vector<4xi1>, tensor<4xi1> |
| // CHECK: vector.transfer_read {{.*}} : tensor<4x4xi1>, vector<4x4xi1> |
| // CHECK: vector.multi_reduction #vector.kind<xor>, {{.*}} [1] : vector<4x4xi1> to vector<4xi1> |
| // CHECK: vector.transfer_write {{.*}} : vector<4xi1>, tensor<4xi1> |
| %ident = arith.constant false |
| %init = linalg.init_tensor [4] : tensor<4xi1> |
| %fill = linalg.fill(%ident, %init) : i1, tensor<4xi1> -> tensor<4xi1> |
| %red = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0)>], |
| iterator_types = ["parallel", "reduction"]} |
| ins(%arg0 : tensor<4x4xi1>) outs(%fill : tensor<4xi1>) { |
| ^bb0(%in0: i1, %out0: i1): // no predecessors |
| %xor = arith.xori %in0, %out0 : i1 |
| linalg.yield %xor : i1 |
| } -> tensor<4xi1> |
| return %red : tensor<4xi1> |
| } |
| |
| // ----- |
| |
| // CHECK-DAG: #[[$M5:.*]] = affine_map<(d0, d1) -> (d0, 0)> |
| |
| // CHECK-LABEL: func @explicit_broadcast( |
| func @explicit_broadcast(%arg0: tensor<4x4xf32>, %arg1: tensor<4x1xf32>) -> tensor<4x4xf32> { |
| // CHECK: vector.transfer_read {{.*}} {in_bounds = [true, true]} : tensor<4x4xf32>, vector<4x4xf32> |
| // CHECK: vector.transfer_read {{.*}} {in_bounds = [true, true], permutation_map = #[[$M5]]} : tensor<4x1xf32>, vector<4x4xf32> |
| // CHECK: subf {{.*}} : vector<4x4xf32> |
| // CHECK: vector.transfer_write {{.*}} {in_bounds = [true, true]} : vector<4x4xf32>, tensor<4x4xf32> |
| %c0 = arith.constant 0.0 : f32 |
| %init = linalg.init_tensor [4, 4] : tensor<4x4xf32> |
| %fill = linalg.fill(%c0, %init) : f32, tensor<4x4xf32> -> tensor<4x4xf32> |
| %red = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, 0)>, |
| affine_map<(d0, d1) -> (d0, d1)>], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%arg0, %arg1 : tensor<4x4xf32>, tensor<4x1xf32>) |
| outs(%fill : tensor<4x4xf32>) { |
| ^bb0(%arg7: f32, %arg8: f32, %arg9: f32): |
| %40 = arith.subf %arg7, %arg8 : f32 |
| linalg.yield %40 : f32 |
| } -> tensor<4x4xf32> |
| return %red : tensor<4x4xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-DAG: #[[$M6:.*]] = affine_map<(d0, d1) -> (d0, 0)> |
| |
| // CHECK-LABEL: func @fused_broadcast_red_2d |
| func @fused_broadcast_red_2d(%arg0: tensor<4x4xf32>, %arg1: tensor<4x1xf32>) -> tensor<4xf32> { |
| // CHECK: vector.transfer_read {{.*}} {in_bounds = [true, true]} : tensor<4x4xf32>, vector<4x4xf32> |
| // CHECK: vector.transfer_read {{.*}} {in_bounds = [true, true], permutation_map = #[[$M6]]} : tensor<4x1xf32>, vector<4x4xf32> |
| // CHECK: subf {{.*}} : vector<4x4xf32> |
| // CHECK: math.exp {{.*}} : vector<4x4xf32> |
| // CHECK: vector.multi_reduction #vector.kind<add>, {{.*}} : vector<4x4xf32> to vector<4xf32> |
| // CHECK: addf {{.*}} : vector<4xf32> |
| // CHECK: vector.transfer_write {{.*}} {in_bounds = [true]} : vector<4xf32>, tensor<4xf32> |
| %c0 = arith.constant 0.0 : f32 |
| %init = linalg.init_tensor [4] : tensor<4xf32> |
| %fill = linalg.fill(%c0, %init) : f32, tensor<4xf32> -> tensor<4xf32> |
| %red = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0, 0)>, |
| affine_map<(d0, d1) -> (d0)>], |
| iterator_types = ["parallel", "reduction"]} |
| ins(%arg0, %arg1 : tensor<4x4xf32>, tensor<4x1xf32>) |
| outs(%fill : tensor<4xf32>) { |
| ^bb0(%arg7: f32, %arg8: f32, %arg9: f32): |
| %40 = arith.subf %arg7, %arg8 : f32 |
| %41 = math.exp %40 : f32 |
| %42 = arith.addf %41, %arg9 : f32 |
| linalg.yield %42 : f32 |
| } -> tensor<4xf32> |
| return %red : tensor<4xf32> |
| } |
| |
| // ----- |
| |
| // CHECK-LABEL: func @reduce_1d( |
| // CHECK-SAME: %[[A:.*]]: tensor<32xf32> |
| func @reduce_1d(%arg0: tensor<32xf32>) -> tensor<f32> { |
| // CHECK-DAG: %[[F0_v1:.*]] = arith.constant dense<0.000000e+00> : vector<1xf32> |
| // CHECK-DAG: %[[F0:.*]] = arith.constant 0.000000e+00 : f32 |
| // CHECK-DAG: %[[C0:.*]] = arith.constant 0 : index |
| %f0 = arith.constant 0.000000e+00 : f32 |
| |
| // CHECK: %[[init:.*]] = linalg.init_tensor [] : tensor<f32> |
| %0 = linalg.init_tensor [] : tensor<f32> |
| |
| // CHECK: %[[f:.*]] = vector.transfer_write %[[F0_v1]], %[[init]][] |
| // CHECK-SAME: : vector<1xf32>, tensor<f32> |
| %1 = linalg.fill(%f0, %0) : f32, tensor<f32> -> tensor<f32> |
| // CHECK: %[[r:.*]] = vector.transfer_read %[[A]][%[[C0]]] |
| // CHECK-SAME: : tensor<32xf32>, vector<32xf32> |
| // CHECK: %[[red:.*]] = vector.multi_reduction #vector.kind<add>, %[[r]] [0] |
| // CHECK-SAME: : vector<32xf32> to f32 |
| // CHECK: %[[a:.*]] = arith.addf %[[red]], %[[F0]] : f32 |
| // CHECK: %[[red_v1:.*]] = vector.broadcast %[[a]] : f32 to vector<1xf32> |
| // CHECK: %[[res:.*]] = vector.transfer_write %[[red_v1]], %[[f]][] |
| // CHECK-SAME: : vector<1xf32>, tensor<f32> |
| %2 = linalg.generic { |
| indexing_maps = [affine_map<(d0) -> (d0)>, |
| affine_map<(d0) -> ()>], |
| iterator_types = ["reduction"]} |
| ins(%arg0 : tensor<32xf32>) |
| outs(%1 : tensor<f32>) { |
| ^bb0(%a: f32, %b: f32): // no predecessors |
| %3 = arith.addf %a, %b : f32 |
| linalg.yield %3 : f32 |
| } -> tensor<f32> |
| |
| return %2 : tensor<f32> |
| } |
