tests/python/relax/backend/clml/utils.py

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"""Run utils for CLML integration operator tests"""
import pytest
import numpy as np
import json
import tvm
import tvm.testing
import copy

from tvm import relax, rpc
from tvm.relax import transform
from tvm import dlight as dl
from tvm.contrib import utils, ndk
from tvm.relax.backend.adreno.clml import OpenCLMLOffLoad


def build_and_run(
    mod,
    inputs_np,
    target,
    rpc=None,
    load_path="vm_library.so",
    clml_enable=False,
):
    tgt = tvm.target.Target(target, host="llvm -mtriple=aarch64-linux-gnu")
    pipeline = relax.pipeline.get_default_pipeline(tgt)
    mod = pipeline(mod)
    if rpc:
        ex = tvm.compile(mod, tgt)
        temp = utils.tempdir()
        path = temp.relpath(load_path)
        path = "./" + load_path
        ex.export_library(path, fcompile=ndk.create_shared, options=["-shared", "-fPIC", "-lm"])
        rpc.upload(path)
        rexec = rpc.load_module(load_path)
        dev = rpc.cl(0)
        vm = relax.VirtualMachine(rexec, dev)
    else:
        ex = tvm.compile(mod, target)
        dev = tvm.device(target, 0)
        vm = relax.VirtualMachine(ex, dev)

    f = vm["main"]
    inputs = [tvm.runtime.tensor(inp, dev) for inp in inputs_np]
    vm.set_input("main", *inputs)
    vm.invoke_stateful("main")
    tvm_output = vm.get_outputs("main")
    return tvm_output.numpy()


def run_compare(mod, inputs, params_np, rpc=None):
    clml_mod = copy.deepcopy(mod)
    mod = tvm.relax.transform.BindParams("main", params_np)(mod)
    clml_mod = tvm.relax.transform.BindParams("main", params_np)(clml_mod)

    if not rpc:
        return

    ref = build_and_run(
        mod,
        inputs,
        tvm.target.adreno(),
        rpc=rpc,
        load_path="vm_library_opencl.so",
    )
    out = build_and_run(
        clml_mod,
        inputs,
        tvm.target.adreno(clml=True),
        rpc=rpc,
        load_path="vm_library_clml.so",
        clml_enable=True,
    )
    np.testing.assert_allclose(out, ref, rtol=1e-5, atol=1e-5)