tests/python/codegen/test_target_codegen_extern.py

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import tvm
from tvm import te
import numpy as np
import tvm.testing
import pytest
from tvm import tir


@tvm.testing.uses_gpu
def test_add_pipeline():
    nn = 64
    max_threads = 4
    n = tvm.runtime.convert(nn)
    A = te.placeholder((n,), name="A")

    def extern_generator(ins, outs):
        """Manually write the IR for the extern function, add pipeline"""
        ib = tvm.tir.ir_builder.create()
        with ib.for_range(0, (n + 1) // 2) as i:
            ib.emit(
                outs[0].vstore(
                    i * 2, ins[0].vload(i * 2, "float32x2") + tvm.tir.const(1, "float32x2")
                )
            )
        return ib.get()

    def extern_generator_gpu(ins, outs):
        """Manually write the IR for the extern function, add pipeline"""
        ib = tvm.tir.ir_builder.create()
        bx = te.thread_axis("blockIdx.x")
        tx = te.thread_axis("threadIdx.x")
        ib.scope_attr(bx, "thread_extent", (nn + max_threads - 1) // max_threads)
        ib.scope_attr(tx, "thread_extent", max_threads)
        idx = bx.var * max_threads + tx.var
        with ib.if_scope(ib.likely(idx < n)):
            ib.emit(
                outs[0].vstore(
                    idx * 2, ins[0].vload(idx * 2, "float32x2") + tvm.tir.const(1, "float32x2")
                )
            )
        return ib.get()

    C_cpu = te.extern(A.shape, [A], extern_generator, name="C")
    C_gpu = te.extern(A.shape, [A], extern_generator_gpu, name="C")

    # Create IRModules directly
    mod_cpu = tvm.IRModule.from_expr(te.create_prim_func([A, C_cpu]))
    mod_gpu = tvm.IRModule.from_expr(te.create_prim_func([A, C_gpu]))

    def check_target(target):
        if not tvm.testing.device_enabled(target):
            return
        mod = mod_gpu if target in ["opencl", "cuda"] else mod_cpu
        C = C_gpu if target in ["opencl", "cuda"] else C_cpu
        # build and invoke the kernel.
        f = tvm.compile(mod, target=target)
        dev = tvm.device(target, 0)
        # launch the kernel.
        n = nn
        a = tvm.runtime.tensor(np.random.uniform(size=n).astype(A.dtype), dev)
        c = tvm.runtime.tensor(np.zeros(n, dtype=C.dtype), dev)
        f(a, c)
        tvm.testing.assert_allclose(c.numpy(), a.numpy() + 1)

    check_target("llvm")
    check_target("opencl")
    check_target("cuda")


def test_pack_buffer_simple():
    nn = 1024
    n = tvm.runtime.convert(nn)
    A = te.placeholder((n,), name="A")

    def extern_generator(ins, outs):
        """Manually write the IR for the extern function, add pipeline."""
        return tvm.tir.call_packed("my_extern_array_func1", ins[0], outs[0])

    C = te.extern(A.shape, [A], extern_generator, name="C")

    # Create IRModule directly
    mod = tvm.IRModule.from_expr(te.create_prim_func([A, C]))

    @tvm.register_global_func
    def my_extern_array_func1(aa, bb):
        aa.copyto(bb)

    def check_target(target):
        if not tvm.testing.device_enabled(target):
            return
        # build and invoke the kernel.
        f = tvm.compile(mod, target=target)
        dev = tvm.cpu(0)
        # launch the kernel.
        n = nn
        a = tvm.runtime.tensor(np.random.uniform(size=n).astype(A.dtype), dev)
        c = tvm.runtime.tensor(np.zeros(n, dtype=C.dtype), dev)

        f(a, c)
        tvm.testing.assert_allclose(c.numpy(), a.numpy())

    check_target("llvm")


@pytest.mark.skip("LEGACY-TO-FIX: limitation of create_prim_func with intermediate buffer")
def test_pack_buffer_intermediate():
    nn = 1024
    n = tvm.runtime.convert(nn)
    A = te.placeholder((n,), name="A")
    B = te.compute((n,), lambda i: A[i] + 1, name="B")

    def extern_generator(ins, outs):
        """Manually write the IR for the extern function, add pipeline."""
        return tvm.tir.call_packed("my_extern_array_func2", ins[0], outs[0])

    C = te.extern(B.shape, [B], extern_generator, name="C")
    mod = tvm.IRModule.from_expr(te.create_prim_func([A, C]))

    def check_target(target):
        if not tvm.testing.device_enabled(target):
            return
        # build and invoke the kernel.
        f = tvm.compile(mod, target=target)
        dev = tvm.cpu(0)
        # launch the kernel.
        n = nn
        a = tvm.runtime.tensor(np.random.uniform(size=n).astype(A.dtype), dev)
        c = tvm.runtime.tensor(np.zeros(n, dtype=C.dtype), dev)

        @tvm.register_global_func
        def my_extern_array_func2(aa, bb):
            assert aa.shape == a.shape
            tvm.testing.assert_allclose(aa.numpy(), a.numpy() + 1)
            aa.copyto(bb)

        f(a, c)
        tvm.testing.assert_allclose(c.numpy(), a.numpy() + 1)

    check_target("llvm")


if __name__ == "__main__":
    test_pack_buffer_simple()
    test_pack_buffer_intermediate()
    test_add_pipeline()