| // RUN: iree-opt -split-input-file -iree-stream-transformation-pipeline -iree-hal-transformation-pipeline %s | IreeFileCheck %s |
| // RUN: iree-opt -split-input-file -iree-stream-transformation-pipeline -iree-hal-transformation-pipeline -iree-llvm-link-embedded=false %s | IreeFileCheck %s |
| |
| #map = affine_map<(d0) -> (d0)> |
| |
| module attributes { |
| hal.device.targets = [ |
| #hal.device.target<"dylib", { |
| executable_targets = [ |
| #hal.executable.target<"llvm", "embedded-elf-x86_64"> |
| ] |
| }> |
| ] |
| } { |
| |
| stream.executable public @add_dispatch_0 { |
| stream.executable.export @add_dispatch_0 |
| builtin.module { |
| func @add_dispatch_0(%arg0_binding: !stream.binding, %arg1_binding: !stream.binding, %arg2_binding: !stream.binding) { |
| %c0 = arith.constant 0 : index |
| %arg0 = stream.binding.subspan %arg0_binding[%c0] : !stream.binding -> !flow.dispatch.tensor<readonly:16xf32> |
| %arg1 = stream.binding.subspan %arg1_binding[%c0] : !stream.binding -> !flow.dispatch.tensor<readonly:16xf32> |
| %arg2 = stream.binding.subspan %arg2_binding[%c0] : !stream.binding -> !flow.dispatch.tensor<writeonly:16xf32> |
| %0 = linalg.init_tensor [16] : tensor<16xf32> |
| %1 = flow.dispatch.tensor.load %arg0, offsets=[], sizes=[], strides=[] : !flow.dispatch.tensor<readonly:16xf32> -> tensor<16xf32> |
| %2 = flow.dispatch.tensor.load %arg1, offsets=[], sizes=[], strides=[] : !flow.dispatch.tensor<readonly:16xf32> -> tensor<16xf32> |
| %3 = linalg.generic {indexing_maps = [affine_map<(d0) -> (d0)>, affine_map<(d0) -> (d0)>, affine_map<(d0) -> (d0)>], iterator_types = ["parallel"]} ins(%1, %2 : tensor<16xf32>, tensor<16xf32>) outs(%0 : tensor<16xf32>) { |
| ^bb0(%arg3: f32, %arg4: f32, %arg5: f32): // no predecessors |
| %4 = arith.addf %arg3, %arg4 : f32 |
| linalg.yield %4 : f32 |
| } -> tensor<16xf32> |
| flow.dispatch.tensor.store %3, %arg2, offsets=[], sizes=[], strides=[] : tensor<16xf32> -> !flow.dispatch.tensor<writeonly:16xf32> |
| return |
| } |
| } |
| } |
| |
| } |
| |
| // CHECK: hal.executable.binary public @embedded_elf_x86_64 |
| // CHECK-SAME: data = dense |
| // CHECK-SAME: format = "embedded-elf-x86_64" |
