# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import numpy as np import tvm from tvm.runtime import profiler_vm from tvm import relay from tvm.relay.testing import mlp @tvm.testing.parametrize_targets def test_basic(dev, target): mod, params = mlp.get_workload(batch_size=1) if not profiler_vm.enabled(): return exe = relay.vm.compile(mod, target, params=params) code, lib = exe.save() des_exe = tvm.runtime.vm.Executable.load_exec(code, lib) vm = profiler_vm.VirtualMachineProfiler(des_exe, dev) data = np.random.rand(1, 1, 28, 28).astype("float32") res = vm.profile(tvm.nd.array(data), func_name="main") assert "softmax" in str(res) def test_vm_reshape_and_copy(): target = "llvm" dev = tvm.gpu() x_np = np.random.uniform(size=(8, 16)).astype("float32") x = relay.var("x", shape=(8, 16), dtype="float32") y = relay.reshape(x, [-1, 4, 8]) mod = tvm.IRModule() mod["main"] = relay.Function([x], y) with tvm.transform.PassContext(opt_level=3): exec = relay.vm.compile(mod, "llvm") assert "reshape_tensor" in exec.bytecode vm = profiler_vm.VirtualMachineProfiler(exec, dev) vm.profile(tvm.nd.array(x_np)) if __name__ == "__main__": import sys import pytest sys.exit(pytest.main([__file__] + sys.argv[1:]))