tqchen commented on a change in pull request #4532: [RUNTIME] Support standardize runtime module URL: https://github.com/apache/incubator-tvm/pull/4532#discussion_r360658500
########## File path: tests/python/unittest/test_runtime_module_export.py ########## @@ -0,0 +1,208 @@ +# 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. +from tvm import relay +from tvm.relay import testing +import tvm + +from tvm.contrib import util +header_file_dir_path = util.tempdir() + + +def gen_engine_header(): + code = r''' + #ifndef _ENGINE_H_ + #define _ENGINE_H_ + #include <cstdint> + #include <string> + #include <sstream> + #include <vector> + class Engine { + }; + + #endif + ''' + header_file = header_file_dir_path.relpath("gcc_engine.h") + with open(header_file, 'w') as f: + f.write(code) + + +def generate_engine_module(): + code = r''' + #include <tvm/runtime/c_runtime_api.h> + #include <dlpack/dlpack.h> + #include "gcc_engine.h" + + extern "C" void gcc_1_(float* gcc_input4, float* gcc_input5, + float* gcc_input6, float* gcc_input7, float* out) { + Engine engine; + } + ''' + gen_engine_header() + csource_module = tvm.module.csource_module_create(code, "cc") + return csource_module + + +def test_mod_export(): + def verify_gpu_mod_export(obj_format): + for device in ["llvm", "cuda"]: + if not tvm.module.enabled(device): + print("skip because %s is not enabled..." % device) + return + + resnet18_mod, resnet18_params = relay.testing.resnet.get_workload(num_layers=18) + resnet50_mod, resnet50_params = relay.testing.resnet.get_workload(num_layers=50) + with relay.build_config(opt_level=3): + _, resnet18_gpu_lib, _ = relay.build_module.build(resnet18_mod, "cuda", params=resnet18_params) + _, resnet50_cpu_lib, _ = relay.build_module.build(resnet50_mod, "llvm", params=resnet50_params) + + from tvm.contrib import util + temp = util.tempdir() + if obj_format == ".so": + file_name = "deploy_lib.so" + else: + assert obj_format == ".tar" + file_name = "deploy_lib.tar" + path_lib = temp.relpath(file_name) + resnet18_gpu_lib.imported_modules[0].import_module(resnet50_cpu_lib) + resnet18_gpu_lib.export_library(path_lib) + loaded_lib = tvm.module.load(path_lib) + assert loaded_lib.type_key == "library" + assert loaded_lib.imported_modules[0].type_key == "cuda" + assert loaded_lib.imported_modules[0].imported_modules[0].type_key == "library" + + def verify_multi_dso_mod_export(obj_format): + for device in ["llvm"]: + if not tvm.module.enabled(device): + print("skip because %s is not enabled..." % device) + return + + resnet18_mod, resnet18_params = relay.testing.resnet.get_workload(num_layers=18) + with relay.build_config(opt_level=3): + _, resnet18_cpu_lib, _ = relay.build_module.build(resnet18_mod, "llvm", params=resnet18_params) + + A = tvm.placeholder((1024,), name='A') + B = tvm.compute(A.shape, lambda *i: A(*i) + 1.0, name='B') + s = tvm.create_schedule(B.op) + f = tvm.build(s, [A, B], "llvm", name="myadd") + from tvm.contrib import util + temp = util.tempdir() + if obj_format == ".so": + file_name = "deploy_lib.so" + else: + assert obj_format == ".tar" + file_name = "deploy_lib.tar" + path_lib = temp.relpath(file_name) + resnet18_cpu_lib.import_module(f) + resnet18_cpu_lib.export_library(path_lib) + loaded_lib = tvm.module.load(path_lib) + assert loaded_lib.type_key == "library" + assert loaded_lib.imported_modules[0].type_key == "library" + + def verify_json_import_dso(obj_format): + for device in ["llvm"]: + if not tvm.module.enabled(device): + print("skip because %s is not enabled..." % device) + return + + # Get subgraph Json. + subgraph_json = ("json_rt_0\n" + + "input 0 10 10\n" + + "input 1 10 10\n" + + "input 2 10 10\n" + + "input 3 10 10\n" + + "add 4 inputs: 0 1 shape: 10 10\n" + + "sub 5 inputs: 4 2 shape: 10 10\n" + + "mul 6 inputs: 5 3 shape: 10 10\n" + + "json_rt_1\n" + + "input 0 10 10\n" + + "input 1 10 10\n" + + "input 2 10 10\n" + + "input 3 10 10\n" + + "add 4 inputs: 0 1 shape: 10 10\n" + + "sub 5 inputs: 4 2 shape: 10 10\n" + + "mul 6 inputs: 5 3 shape: 10 10") + + from tvm.contrib import util + temp = util.tempdir() + subgraph_path = temp.relpath('subgraph.examplejson') + with open(subgraph_path, 'w') as f: + f.write(subgraph_json) + + # Get Json and module. + A = tvm.placeholder((1024,), name='A') + B = tvm.compute(A.shape, lambda *i: A(*i) + 1.0, name='B') + s = tvm.create_schedule(B.op) + f = tvm.build(s, [A, B], "llvm", name="myadd") + try: + ext_lib = tvm.module.load(subgraph_path, "examplejson") + except: + print("skip because Loader of examplejson is not presented") + return + ext_lib.import_module(f) + if obj_format == ".so": + file_name = "deploy_lib.so" + else: + assert obj_format == ".tar" + file_name = "deploy_lib.tar" + path_lib = temp.relpath(file_name) + ext_lib.export_library(path_lib) + lib = tvm.module.load(path_lib) + assert lib.type_key == "examplejson" + assert lib.imported_modules[0].type_key == "library" + + def verify_multi_c_mod_export(): Review comment: can we test the case where there are two c modules? so far seems there is only one, we can build another one for sub ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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