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1# RUN: %PYTHON %s | FileCheck %s2 3from mlir.ir import *4import mlir.ir as ir5from mlir.dialects import gpu, func, arith, math6from mlir.extras import types as T7import mlir.dialects.gpu.passes8from mlir.passmanager import *9 10 11def run(f):12    print("\nTEST:", f.__name__)13    with Context(), Location.unknown():14        f()15    return f16 17 18# CHECK-LABEL: testGPUPass19#       CHECK: SUCCESS20@run21def testGPUPass():22    PassManager.parse("any(gpu-kernel-outlining)")23    print("SUCCESS")24 25 26# CHECK-LABEL: testMMAElementWiseAttr27@run28def testMMAElementWiseAttr():29    module = Module.create()30    with InsertionPoint(module.body):31        gpu.BlockDimOp(gpu.Dimension.y)32    # CHECK: %block_dim_y = gpu.block_dim  y33    print(module)34    pass35 36 37# CHECK-LABEL: testObjectAttr38@run39def testObjectAttr():40    target = Attribute.parse("#nvvm.target")41    format = gpu.CompilationTarget.Fatbin42    object = b"BC\xc0\xde5\x14\x00\x00\x05\x00\x00\x00b\x0c0$MY\xbef"43    properties = DictAttr.get({"O": IntegerAttr.get(IntegerType.get_signless(32), 2)})44    o = gpu.ObjectAttr.get(target, format, object, properties)45    # CHECK: #gpu.object<#nvvm.target, properties = {O = 2 : i32}, "BC\C0\DE5\14\00\00\05\00\00\00b\0C0$MY\BEf">46    print(o)47    assert o.object == object48 49    o = gpu.ObjectAttr.get(target, format, object)50    # CHECK: #gpu.object<#nvvm.target, "BC\C0\DE5\14\00\00\05\00\00\00b\0C0$MY\BEf">51    print(o)52 53    object = (54        b"//\n// Generated by LLVM NVPTX Back-End\n//\n\n.version 6.0\n.target sm_50"55    )56    o = gpu.ObjectAttr.get(target, format, object)57    # CHECK: #gpu.object<#nvvm.target, "//\0A// Generated by LLVM NVPTX Back-End\0A//\0A\0A.version 6.0\0A.target sm_50">58    print(o)59    assert o.object == object60 61    object = b"BC\xc0\xde5\x14\x00\x00\x05\x00\x00\x00b\x0c0$MY\xbef"62    kernelTable = Attribute.parse(63        '#gpu.kernel_table<[#gpu.kernel_metadata<"kernel", () -> ()>]>'64    )65    o = gpu.ObjectAttr.get(target, format, object, kernels=kernelTable)66    # CHECK: #gpu.object<#nvvm.target, kernels = <[#gpu.kernel_metadata<"kernel", () -> ()>]>, "BC\C0\DE5\14\00\00\05\00\00\00b\0C0$MY\BEf">67    print(o)68    assert o.kernels == kernelTable69 70 71# CHECK-LABEL: testGPUFuncOp72@run73def testGPUFuncOp():74    assert gpu.GPUFuncOp.__doc__ is not None75    module = Module.create()76    with InsertionPoint(module.body):77        gpu_module_name = StringAttr.get("gpu_module")78        gpumodule = gpu.GPUModuleOp(gpu_module_name)79        block = gpumodule.bodyRegion.blocks.append()80 81        def builder(func: gpu.GPUFuncOp) -> None:82            gpu.GlobalIdOp(gpu.Dimension.x)83            gpu.ReturnOp([])84 85        with InsertionPoint(block):86            name = StringAttr.get("kernel0")87            func_type = ir.FunctionType.get(inputs=[], results=[])88            type_attr = TypeAttr.get(func_type)89            func = gpu.GPUFuncOp(type_attr, name)90            func.attributes["sym_name"] = name91            func.attributes["gpu.kernel"] = UnitAttr.get()92 93            try:94                func.entry_block95                assert False, "Expected RuntimeError"96            except RuntimeError as e:97                assert (98                    str(e)99                    == "Entry block does not exist for kernel0. Do you need to call the add_entry_block() method on this GPUFuncOp?"100                )101 102            block = func.add_entry_block()103            with InsertionPoint(block):104                builder(func)105 106            try:107                func.add_entry_block()108                assert False, "Expected RuntimeError"109            except RuntimeError as e:110                assert str(e) == "Entry block already exists for kernel0"111 112            func = gpu.GPUFuncOp(113                func_type,114                sym_name="kernel1",115                kernel=True,116                body_builder=builder,117                known_block_size=[1, 2, 3],118                known_grid_size=DenseI32ArrayAttr.get([4, 5, 6]),119            )120 121            assert func.name.value == "kernel1"122            assert func.function_type.value == func_type123            assert func.arg_attrs == None124            assert func.res_attrs == None125            assert func.arguments == []126            assert func.entry_block == func.body.blocks[0]127            assert func.is_kernel128            assert func.known_block_size == DenseI32ArrayAttr.get(129                [1, 2, 3]130            ), func.known_block_size131            assert func.known_grid_size == DenseI32ArrayAttr.get(132                [4, 5, 6]133            ), func.known_grid_size134 135            func = gpu.GPUFuncOp(136                ir.FunctionType.get(inputs=[T.index()], results=[]),137                sym_name="non_kernel_func",138                body_builder=builder,139                arg_attrs=[{"gpu.some_attribute": ir.StringAttr.get("foo")}],140            )141            assert not func.is_kernel142            assert func.known_block_size is None143            assert func.known_grid_size is None144 145    print(module)146 147    # CHECK: gpu.module @gpu_module148    # CHECK: gpu.func @kernel0() kernel {149    # CHECK:   %[[VAL_0:.*]] = gpu.global_id  x150    # CHECK:   gpu.return151    # CHECK: }152    # CHECK: gpu.func @kernel1() kernel attributes153    # CHECK-SAME: known_block_size = array<i32: 1, 2, 3>154    # CHECK-SAME: known_grid_size = array<i32: 4, 5, 6>155    # CHECK:   %[[VAL_0:.*]] = gpu.global_id  x156    # CHECK:   gpu.return157    # CHECK: }158    # CHECK:   gpu.func @non_kernel_func(159    # CHECK-SAME:      %[[ARG0:.*]]: index {gpu.some_attribute = "foo"}) {160    # CHECK:           %[[GLOBAL_ID_0:.*]] = gpu.global_id  x161    # CHECK:           gpu.return162    # CHECK:         }163 164 165# CHECK-LABEL: testGPULaunchFuncOp166@run167def testGPULaunchFuncOp():168    module = Module.create()169 170    module.operation.attributes["gpu.container_module"] = UnitAttr.get()171    with InsertionPoint(module.body):172        gpu_module = gpu.GPUModuleOp("gpu_module")173        block = gpu_module.bodyRegion.blocks.append()174 175    with InsertionPoint(block):176        gpu_func = gpu.GPUFuncOp(177            FunctionType.get([], []),178            "kernel",179            body_builder=lambda func: gpu.return_([]),180            kernel=True,181        )182 183    with InsertionPoint(module.body):184        host = func.FuncOp(type=FunctionType.get([], []), name="host")185 186    with InsertionPoint(host.add_entry_block()):187        c1 = arith.constant(T.index(), 1)188        grid_sizes = (1, 1, 1)189        block_sizes = (1, 1, 1)190        token = gpu.wait()191        token = gpu.launch_func(192            async_dependencies=[token],193            kernel=[gpu_module.sym_name.value, gpu_func.name.value],194            grid_size=grid_sizes,195            block_size=block_sizes,196            kernel_operands=[],197        )198        gpu.wait(async_dependencies=[token])199        func.ReturnOp([])200 201    print(module)202 203    # CHECK-LABEL:   gpu.module @gpu_module {204    # CHECK:           gpu.func @kernel() kernel {205    # CHECK:             gpu.return206    # CHECK:           }207    # CHECK:         }208 209    # CHECK-LABEL:   func.func @host() {210    # CHECK:           %[[CONSTANT_0:.*]] = arith.constant 1 : index211    # CHECK:           %[[WAIT_0:.*]] = gpu.wait async212    # CHECK:           %[[CONSTANT_1:.*]] = arith.constant 1 : index213    # CHECK:           %[[CONSTANT_2:.*]] = arith.constant 1 : index214    # CHECK:           %[[CONSTANT_3:.*]] = arith.constant 1 : index215    # CHECK:           %[[CONSTANT_4:.*]] = arith.constant 1 : index216    # CHECK:           %[[CONSTANT_5:.*]] = arith.constant 1 : index217    # CHECK:           %[[CONSTANT_6:.*]] = arith.constant 1 : index218    # CHECK:           %[[LAUNCH_FUNC_0:.*]] = gpu.launch_func async {{\[}}%[[WAIT_0]]] @gpu_module::@kernel blocks in (%[[CONSTANT_1]], %[[CONSTANT_2]], %[[CONSTANT_3]]) threads in (%[[CONSTANT_4]], %[[CONSTANT_5]], %[[CONSTANT_6]])219    # CHECK:           %[[WAIT_1:.*]] = gpu.wait async {{\[}}%[[LAUNCH_FUNC_0]]]220    # CHECK:           return221    # CHECK:         }222 223 224# CHECK-LABEL: testGPULaunchOp225@run226def testGPULaunchOp():227    module = Module.create()228 229    with InsertionPoint(module.body):230        host = func.FuncOp(type=FunctionType.get([T.f32()], []), name="gpu_printf")231 232    entry_block = host.add_entry_block()233    with InsertionPoint(entry_block):234        c1 = arith.constant(T.index(), 1)235        grid_sizes = (c1, c1, c1)236        block_sizes = (c1, c1, c1)237 238        launch = gpu.launch(grid_sizes, block_sizes)239 240    op = launch(lambda *args: gpu.printf("%f", args[0]))241 242    with InsertionPoint(entry_block):243        func.ReturnOp([])244 245    print(module)246 247    # CHECK-LABEL:   func.func @gpu_printf(248    # CHECK-SAME:      %[[ARG0:.*]]: f32) {249    # CHECK:           %[[CONSTANT_0:.*]] = arith.constant 1 : index250    # CHECK:           gpu.launch blocks(%[[VAL_0:.*]], %[[VAL_1:.*]], %[[VAL_2:.*]]) in (%[[VAL_3:.*]] = %[[CONSTANT_0]], %[[VAL_4:.*]] = %[[CONSTANT_0]], %[[VAL_5:.*]] = %[[CONSTANT_0]]) threads(%[[VAL_6:.*]], %[[VAL_7:.*]], %[[VAL_8:.*]]) in (%[[VAL_9:.*]] = %[[CONSTANT_0]], %[[VAL_10:.*]] = %[[CONSTANT_0]], %[[VAL_11:.*]] = %[[CONSTANT_0]]) {251    # CHECK:             gpu.printf "%[[VAL_12:.*]]", %[[VAL_0]] : index252    # CHECK:             gpu.terminator253    # CHECK:           }254    # CHECK:           return255    # CHECK:         }256