# -*- coding: utf-8 -*- # MegEngine is Licensed under the Apache License, Version 2.0 (the "License") # # Copyright (c) 2014-2020 Megvii Inc. All rights reserved. # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied import json import os import tempfile import pytest from megengine import Parameter from megengine import distributed as dist from megengine import tensor from megengine.jit import trace from megengine.module import Module from megengine.utils.profiler import Profiler, scope class Simple(Module): def __init__(self): super().__init__() self.a = Parameter([1.23], dtype="float32") def forward(self, x): x = x * self.a return x @pytest.mark.parametrize("format", ["chrome_timeline.json", "memory_flow.svg"]) @pytest.mark.parametrize( "trace_mode", [True, False, None], ids=["symbolic", "no-symbolic", "no-trace"] ) @pytest.mark.require_ngpu(1) def test_profiler(format, trace_mode): tempdir = tempfile.TemporaryDirectory() profile_prefix = tempdir.name profile_path = os.path.join(profile_prefix, "{}.{}".format(os.getpid(), format)) def infer(): with scope("my_scope"): oup = Simple()(tensor([1.23], dtype="float32")) return oup if trace_mode: infer = trace(symbolic=trace_mode)(infer) with Profiler(profile_prefix, format=format): infer() assert os.path.exists(profile_path), "profiling results not found" if format == "chrome_timeline.json": with open(profile_path, "r") as f: events = json.load(f) if isinstance(events, dict): assert "traceEvents" in events events = events["traceEvents"] prev_ts = {} scope_count = 0 for event in events: if "dur" in event: assert event["dur"] >= 0 elif "ts" in event and "tid" in event: ts = event["ts"] tid = event["tid"] if ts != 0: assert (tid not in prev_ts) or prev_ts[tid] <= ts prev_ts[tid] = ts if "name" in event and event["name"] == "my_scope": scope_count += 1 assert scope_count > 0 and scope_count % 2 == 0 @pytest.mark.parametrize("format", ["chrome_timeline.json", "memory_flow.svg"]) @pytest.mark.parametrize( "trace_mode", [True, False, None], ids=["symbolic", "no-symbolic", "no-trace"] ) @pytest.mark.isolated_distributed @pytest.mark.require_ngpu(2) def test_profiler_dist(format, trace_mode): n_gpus = 2 tempdir = tempfile.TemporaryDirectory() profile_prefix = tempdir.name profile_path = os.path.join(profile_prefix, "{}.{}".format(os.getpid(), format)) def infer(): with scope("my_scope"): oup = Simple()(tensor([1.23], dtype="float32")) return oup if trace_mode: infer = trace(symbolic=trace_mode)(infer) @dist.launcher(n_gpus=2) def worker(): infer() with Profiler(profile_prefix, format=format): worker() assert os.path.exists(profile_path), "profiling results not found" assert len(os.listdir(tempdir.name)) == n_gpus + 1