201 lines
6.1 KiB
Python
201 lines
6.1 KiB
Python
# Copyright The PyTorch Lightning team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import time
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from pathlib import Path
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import numpy as np
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import pytest
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from pytorch_lightning.profiler import AdvancedProfiler, SimpleProfiler
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PROFILER_OVERHEAD_MAX_TOLERANCE = 0.0005
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def _get_python_cprofile_total_duration(profile):
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return sum([x.inlinetime for x in profile.getstats()])
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def _sleep_generator(durations):
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"""
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the profile_iterable method needs an iterable in which we can ensure that we're
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properly timing how long it takes to call __next__
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"""
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for duration in durations:
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time.sleep(duration)
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yield duration
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@pytest.fixture
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def simple_profiler():
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profiler = SimpleProfiler()
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return profiler
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@pytest.fixture
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def advanced_profiler(tmpdir):
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profiler = AdvancedProfiler(output_filename=os.path.join(tmpdir, "profiler.txt"))
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return profiler
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@pytest.mark.parametrize(["action", "expected"], [
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pytest.param("a", [3, 1]),
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pytest.param("b", [2]),
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pytest.param("c", [1])
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])
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def test_simple_profiler_durations(simple_profiler, action, expected):
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"""Ensure the reported durations are reasonably accurate."""
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for duration in expected:
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with simple_profiler.profile(action):
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time.sleep(duration)
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# different environments have different precision when it comes to time.sleep()
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# see: https://github.com/PyTorchLightning/pytorch-lightning/issues/796
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np.testing.assert_allclose(
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simple_profiler.recorded_durations[action], expected, rtol=0.2
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)
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@pytest.mark.parametrize(["action", "expected"], [
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pytest.param("a", [3, 1]),
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pytest.param("b", [2]),
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pytest.param("c", [1])
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])
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def test_simple_profiler_iterable_durations(simple_profiler, action, expected):
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"""Ensure the reported durations are reasonably accurate."""
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iterable = _sleep_generator(expected)
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for _ in simple_profiler.profile_iterable(iterable, action):
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pass
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# we exclude the last item in the recorded durations since that's when StopIteration is raised
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np.testing.assert_allclose(
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simple_profiler.recorded_durations[action][:-1], expected, rtol=0.2
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)
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def test_simple_profiler_overhead(simple_profiler, n_iter=5):
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"""Ensure that the profiler doesn't introduce too much overhead during training."""
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for _ in range(n_iter):
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with simple_profiler.profile("no-op"):
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pass
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durations = np.array(simple_profiler.recorded_durations["no-op"])
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assert all(durations < PROFILER_OVERHEAD_MAX_TOLERANCE)
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def test_simple_profiler_describe(caplog, simple_profiler):
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"""Ensure the profiler won't fail when reporting the summary."""
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simple_profiler.describe()
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assert "Profiler Report" in caplog.text
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def test_simple_profiler_value_errors(simple_profiler):
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"""Ensure errors are raised where expected."""
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action = "test"
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with pytest.raises(ValueError):
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simple_profiler.stop(action)
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simple_profiler.start(action)
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with pytest.raises(ValueError):
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simple_profiler.start(action)
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simple_profiler.stop(action)
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@pytest.mark.parametrize(["action", "expected"], [
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pytest.param("a", [3, 1]),
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pytest.param("b", [2]),
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pytest.param("c", [1])
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])
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def test_advanced_profiler_durations(advanced_profiler, action, expected):
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for duration in expected:
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with advanced_profiler.profile(action):
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time.sleep(duration)
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# different environments have different precision when it comes to time.sleep()
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# see: https://github.com/PyTorchLightning/pytorch-lightning/issues/796
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recored_total_duration = _get_python_cprofile_total_duration(
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advanced_profiler.profiled_actions[action]
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)
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expected_total_duration = np.sum(expected)
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np.testing.assert_allclose(
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recored_total_duration, expected_total_duration, rtol=0.2
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)
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@pytest.mark.parametrize(["action", "expected"], [
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pytest.param("a", [3, 1]),
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pytest.param("b", [2]),
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pytest.param("c", [1])
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])
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def test_advanced_profiler_iterable_durations(advanced_profiler, action, expected):
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"""Ensure the reported durations are reasonably accurate."""
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iterable = _sleep_generator(expected)
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for _ in advanced_profiler.profile_iterable(iterable, action):
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pass
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recored_total_duration = _get_python_cprofile_total_duration(
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advanced_profiler.profiled_actions[action]
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)
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expected_total_duration = np.sum(expected)
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np.testing.assert_allclose(
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recored_total_duration, expected_total_duration, rtol=0.2
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)
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def test_advanced_profiler_overhead(advanced_profiler, n_iter=5):
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"""
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ensure that the profiler doesn't introduce too much overhead during training
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"""
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for _ in range(n_iter):
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with advanced_profiler.profile("no-op"):
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pass
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action_profile = advanced_profiler.profiled_actions["no-op"]
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total_duration = _get_python_cprofile_total_duration(action_profile)
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average_duration = total_duration / n_iter
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assert average_duration < PROFILER_OVERHEAD_MAX_TOLERANCE
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def test_advanced_profiler_describe(tmpdir, advanced_profiler):
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"""
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ensure the profiler won't fail when reporting the summary
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"""
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# record at least one event
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with advanced_profiler.profile("test"):
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pass
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# log to stdout and print to file
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advanced_profiler.describe()
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data = Path(advanced_profiler.output_fname).read_text()
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assert len(data) > 0
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def test_advanced_profiler_value_errors(advanced_profiler):
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"""Ensure errors are raised where expected."""
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action = "test"
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with pytest.raises(ValueError):
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advanced_profiler.stop(action)
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advanced_profiler.start(action)
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advanced_profiler.stop(action)
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