Back out "[Kineto] Initialize libkineto profilers during torch init process during pybind set-up (#112623)" (#116201)
Summary:
This diff needs to be backed out because TorchBench llama_v2_7b_16h has a cublas init error.
https://github.com/pytorch/benchmark/actions/runs/7266269668/job/19797677485?pr=2095
Test Plan: CI
Differential Revision: D52339142
Pull Request resolved: https://github.com/pytorch/pytorch/pull/116201
Approved by: https://github.com/xuzhao9
diff --git a/test/test_testing.py b/test/test_testing.py
index 12ef27c..b8f7c57 100644
--- a/test/test_testing.py
+++ b/test/test_testing.py
@@ -18,7 +18,7 @@
from torch.testing import make_tensor
from torch.testing._internal.common_utils import \
- (IS_FBCODE, IS_JETSON, IS_LINUX, IS_MACOS, IS_SANDCASTLE, IS_WINDOWS, TestCase, run_tests, slowTest,
+ (IS_FBCODE, IS_JETSON, IS_MACOS, IS_SANDCASTLE, IS_WINDOWS, TestCase, run_tests, slowTest,
parametrize, subtest, instantiate_parametrized_tests, dtype_name, TEST_WITH_ROCM, decorateIf)
from torch.testing._internal.common_device_type import \
(PYTORCH_TESTING_DEVICE_EXCEPT_FOR_KEY, PYTORCH_TESTING_DEVICE_ONLY_FOR_KEY, dtypes,
@@ -2319,15 +2319,6 @@
out = self._check_python_output("; ".join(commands))
self.assertEqual(out.strip(), expected)
- @unittest.skipIf(TEST_WITH_ROCM, "On-demand profiling early init not supported on ROCm")
- @unittest.skipIf(not IS_LINUX, "On-demand profiling not supported outside of Linux")
- def test_libkineto_profiler_is_initialized(self) -> None:
- # Check that the profiler is initialized at import time.
- out = self._check_python_output("""import sys; import torch;
-print(torch._C._autograd._isProfilerInitialized() if torch._C._autograd._is_use_kineto_defined() else 'True')
-""")
- self.assertEqual(out.strip(), "True")
-
class TestOpInfos(TestCase):
def test_sample_input(self) -> None:
a, b, c, d, e = (object() for _ in range(5))
diff --git a/torch/csrc/autograd/init.cpp b/torch/csrc/autograd/init.cpp
index 485986b..ce11637 100644
--- a/torch/csrc/autograd/init.cpp
+++ b/torch/csrc/autograd/init.cpp
@@ -35,10 +35,6 @@
#include <torch/csrc/utils/python_raii.h>
#include <torch/csrc/utils/python_torch_function_mode.h>
-#ifdef USE_KINETO
-#include <libkineto.h>
-#endif
-
#include <set>
#include <unordered_set>
#include <utility>
@@ -134,30 +130,6 @@
if (!ParameterClass)
return nullptr;
-#if defined(USE_KINETO) && defined(__linux__) && !defined(USE_ROCM)
- // Initialize the Kineto profilers, if they have not already.
- // DO NOT REMOVE, this is needed for on-demand profiling.
- if (!libkineto::api().isProfilerRegistered()) {
- libkineto_init(
- /*cpuOnly=*/!(at::hasCUDA() || at::hasXPU() || at::hasMTIA()),
- /*logOnError=*/true);
- libkineto::api().suppressLogMessages();
- }
- libkineto::api().initProfilerIfRegistered();
-
- // Used for unit test to check profiler was initialized.
- m.def("_isProfilerInitialized", []() {
- return libkineto::api().isProfilerInitialized();
- });
-#endif
-
- m.def("_is_use_kineto_defined", []() -> bool {
-#ifdef USE_KINETO
- return true;
-#endif
- return false;
- });
-
py::class_<LegacyEvent>(m, "ProfilerEvent")
.def("kind", &LegacyEvent::kindStr)
.def("name", [](const LegacyEvent& e) { return e.name(); })
