feat(profiling): add support for pytorch profiling

[sanchda]

PR does

• Patches torch.profiler.profile class by adding our own on_trace_ready handler
• Adds GPU time/flops/memory samples via libdatadog interface in on_trace_ready event handler
• Ensures that libdd exporter is enabled if pytorch is enabled
• changelog entry
• Is there a minimum python version?
  • the biggest requirement is that the current pytorch profiler API which we instrument was introduced in torch version 1.9 (https://pytorch.org/blog/pytorch-1.9-released/), do we just want to document or we could disable the instrumentation if we detect an outdated version with torch.__version__

Still need

• Probably should make experimental/beta collectors not part of the ALL template
• Some documentation on needed user configuration, conflicting features, gotchas

Checklist

• [x] Change(s) are motivated and described in the PR description
• [x] Testing strategy is described if automated tests are not included in the PR
• [x] Risks are described (performance impact, potential for breakage, maintainability)
• [x] Change is maintainable (easy to change, telemetry, documentation)
• [x] Library release note guidelines are followed or label changelog/no-changelog is set
• [x] Documentation is included (in-code, generated user docs, public corp docs)
• [x] Backport labels are set (if applicable)
• [x] If this PR changes the public interface, I've notified @DataDog/apm-tees.

Reviewer Checklist

• [ ] Title is accurate
• [ ] All changes are related to the pull request's stated goal
• [ ] Description motivates each change
• [ ] Avoids breaking API changes
• [ ] Testing strategy adequately addresses listed risks
• [ ] Change is maintainable (easy to change, telemetry, documentation)
• [ ] Release note makes sense to a user of the library
• [ ] Author has acknowledged and discussed the performance implications of this PR as reported in the benchmarks PR comment
• [ ] Backport labels are set in a manner that is consistent with the release branch maintenance policy

[pr-commenter[bot]]

Benchmarks

Benchmark execution time: 2024-12-13 22:37:43

Comparing candidate commit 939321620d0038de3709bef2722e96539737cd64 in PR branch peterg17/pytorch_profiling_integration2 with baseline commit 1dd528c0ef5d04e2b095f61d8a15e8fc15cbb00a in branch main.

Found 0 performance improvements and 0 performance regressions! Performance is the same for 394 metrics, 2 unstable metrics.

[datadog-dd-trace-py-rkomorn[bot]]

Datadog Report

Branch report: peterg17/pytorch_profiling_integration2 Commit report: 28ed224 Test service: dd-trace-py

:white_check_mark: 0 Failed, 389 Passed, 1219 Skipped, 44m 19.55s Total duration (42m 52.03s time saved)

[github-actions[bot]]

This pull request has been automatically closed after a period of inactivity. After this much time, it will likely be easier to open a new pull request with the same changes than to update this one from the base branch. Please comment or reopen if you think this pull request was closed in error.

[github-actions[bot]]

CODEOWNERS have been resolved as:

.github/workflows/pytorch_gpu_tests.yml                                 @DataDog/python-guild @DataDog/apm-core-python
ddtrace/profiling/collector/pytorch.py                                  @DataDog/profiling-python
docs/pytorch_metric.png                                                 @DataDog/python-guild
releasenotes/notes/profiling-add-pytorch-integration-0683123b7bb83f99.yaml  @DataDog/apm-python
tests/profiling_v2/simple_program_pytorch_gpu.py                        @DataDog/profiling-python
tests/profiling_v2/test_pytorch.py                                      @DataDog/profiling-python
ddtrace/internal/datadog/profiling/dd_wrapper/include/ddup_interface.hpp  @DataDog/profiling-python
ddtrace/internal/datadog/profiling/dd_wrapper/include/libdatadog_helpers.hpp  @DataDog/profiling-python
ddtrace/internal/datadog/profiling/dd_wrapper/include/sample.hpp        @DataDog/profiling-python
ddtrace/internal/datadog/profiling/dd_wrapper/include/types.hpp         @DataDog/profiling-python
ddtrace/internal/datadog/profiling/dd_wrapper/src/ddup_interface.cpp    @DataDog/profiling-python
ddtrace/internal/datadog/profiling/dd_wrapper/src/profile.cpp           @DataDog/profiling-python
ddtrace/internal/datadog/profiling/dd_wrapper/src/sample.cpp            @DataDog/profiling-python
ddtrace/internal/datadog/profiling/ddup/_ddup.pyi                       @DataDog/profiling-python
ddtrace/internal/datadog/profiling/ddup/_ddup.pyx                       @DataDog/profiling-python
ddtrace/profiling/profiler.py                                           @DataDog/profiling-python
ddtrace/settings/profiling.py                                           @DataDog/profiling-python
docs/advanced_usage.rst                                                 @DataDog/python-guild
docs/spelling_wordlist.txt                                              @DataDog/python-guild
hatch.toml                                                              @DataDog/python-guild

[datadog-dd-trace-py-rkomorn[bot]]

Datadog Report

Branch report: peterg17/pytorch_profiling_integration2 Commit report: a4492b7 Test service: dd-trace-py

:white_check_mark: 0 Failed, 769 Passed, 699 Skipped, 15m 20.28s Total duration (58m 16.46s time saved)