lhutton1 commented on a change in pull request #4933: [Relay] Target annotation for external codegen URL: https://github.com/apache/incubator-tvm/pull/4933#discussion_r383821438
########## File path: tests/python/relay/test_annotate_target.py ########## @@ -0,0 +1,152 @@ +# 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. +"""Unit tests for annotating external targets.""" +import os +import sys +import numpy as np +import pytest + +import tvm +import tvm.relay.testing +import tvm.relay.transform as transform +from tvm import relay +from tvm import runtime +from tvm.contrib import util + + +def check_result(mod, map_inputs, out_shape, result, tol=1e-5, target="llvm", + ctx=tvm.cpu(), params=None): + if sys.platform == "win32": + print("Skip test on Windows for now") + return + + def update_lib(lib): + test_dir = os.path.dirname(os.path.realpath(os.path.expanduser(__file__))) + source_dir = os.path.join(test_dir, "..", "..", "..") + contrib_path = os.path.join(source_dir, "src", "runtime", "contrib") + + kwargs = {} + kwargs["options"] = ["-O2", "-std=c++11", "-I" + contrib_path] + tmp_path = util.tempdir() + lib_name = 'lib.so' + lib_path = tmp_path.relpath(lib_name) + lib.export_library(lib_path, fcompile=False, **kwargs) + lib = runtime.load_module(lib_path) + + return lib + + def check_vm_result(): + with relay.build_config(opt_level=3, disabled_pass=["AlterOpLayout"]): + exe = relay.vm.compile(mod, target=target, params=params) + code, lib = exe.save() + lib = update_lib(lib) + exe = runtime.vm.Executable.load_exec(code, lib) + vm = runtime.vm.VirtualMachine(exe) + vm.init(ctx) + out = vm.run(**map_inputs) + tvm.testing.assert_allclose(out.asnumpy(), result, rtol=tol, atol=tol) + + def check_graph_runtime_result(): + with relay.build_config(opt_level=3, disabled_pass=["AlterOpLayout"]): + json, lib, param = relay.build(mod, target=target, params=params) + lib = update_lib(lib) + rt_mod = tvm.contrib.graph_runtime.create(json, lib, ctx) + + for name, data in map_inputs.items(): + rt_mod.set_input(name, data) + rt_mod.set_input(**param) + rt_mod.run() + out = tvm.nd.empty(out_shape, ctx=ctx) + out = rt_mod.get_output(0, out) + + tvm.testing.assert_allclose(out.asnumpy(), result, rtol=tol, atol=tol) + + check_vm_result() + check_graph_runtime_result() + + +def test_extern_dnnl(): + if not tvm.get_global_func("relay.ext.dnnl", True): + print("skip because DNNL codegen is not available") + return + + dtype = 'float32' + ishape = (1, 32, 14, 14) + w1shape = (32, 1, 3, 3) + data = relay.var('data', shape=(ishape), dtype=dtype) + weight1 = relay.var('weight1', shape=(w1shape), dtype=dtype) + depthwise_conv2d_1 = relay.nn.conv2d(data, + weight1, + kernel_size=(3, 3), + padding=(1, 1), + groups=32) + depthwise_conv2d_2 = relay.nn.conv2d(depthwise_conv2d_1, + weight1, + kernel_size=(3, 3), + padding=(1, 1), + groups=32) + out = relay.add(depthwise_conv2d_1, depthwise_conv2d_2) + + f = relay.Function([data, weight1], out) + + mod = tvm.IRModule.from_expr(f) + mod = transform.AnnotateTarget("dnnl")(mod) + mod = transform.PartitionGraph()(mod) + + ref_mod = tvm.IRModule() + ref_mod['main'] = f + + i_data = np.random.uniform(0, 1, ishape).astype(dtype) + w1_data = np.random.uniform(0, 1, w1shape).astype(dtype) + + print('generating reference') + ref_ex = relay.create_executor("graph", mod=ref_mod, ctx=tvm.cpu()) + ref_res = ref_ex.evaluate()(i_data, w1_data) + print('finished reference generation') + + check_result(mod, {"data": i_data, "weight1": w1_data}, + (1, 32, 14, 14), ref_res.asnumpy(), tol=1e-5) + + +def test_extern_dnnl_mobilenet(): + if not tvm.get_global_func("relay.ext.dnnl", True): + print("skip because DNNL codegen is not available") + return + + dtype = 'float32' + ishape = (1, 3, 224, 224) + mod, params = relay.testing.mobilenet.get_workload( + batch_size=1, dtype='float32') + + mod = transform.AnnotateTarget("dnnl")(mod) + mod = transform.PartitionGraph()(mod) + i_data = np.random.uniform(0, 1, ishape).astype(dtype) + + print('generating reference') Review comment: These updates are probably not necessary? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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