Remove breakpad dependency

This functionality does not seem to be used
and there are some requests to update dependency.

Add `third_party` to torch_cpu include directories if compiling with
Caffe2 support, as `caffe2/quantization/server/conv_dnnlowp_op.cc` depends on `third_party/fbgemm/src/RefImplementations.h`

Pull Request resolved: pytorch#75394
Approved by: https://github.com/janeyx99, https://github.com/seemethere

Author: malfet

.gitmodules

@@ -139,9 +139,6 @@
 [submodule "third_party/pocketfft"]
 	path = third_party/pocketfft
 	url = https://github.com/mreineck/pocketfft
-[submodule "third_party/breakpad"]
-	path = third_party/breakpad
-	url = https://github.com/driazati/breakpad.git
 [submodule "third_party/flatbuffers"]
 	path = third_party/flatbuffers
 	url = https://github.com/google/flatbuffers.git

CMakeLists.txt

@@ -207,7 +207,6 @@ cmake_dependent_option(
     "USE_CUDNN" OFF)
 option(USE_FBGEMM "Use FBGEMM (quantized 8-bit server operators)" ON)
 option(USE_KINETO "Use Kineto profiling library" ON)
-option(USE_BREAKPAD "Use breakpad crash dump library" ON)
 option(USE_CUPTI_SO "Use CUPTI as a shared library" ON)
 option(USE_FAKELOWP "Use FakeLowp operators" OFF)
 option(USE_FFMPEG "Use ffmpeg" OFF)
@@ -271,10 +270,6 @@ if(NOT DEFINED USE_VULKAN)
       "ANDROID" OFF)
 endif()
 
-if(IOS)
-  set(USE_BREAKPAD OFF)
-endif()
-
 option(USE_SLEEF_FOR_ARM_VEC256 "Use sleef for arm" OFF)
 option(USE_SOURCE_DEBUG_ON_MOBILE "Enable " ON)
 option(USE_LITE_INTERPRETER_PROFILER "Enable " ON)

caffe2/CMakeLists.txt

@@ -737,7 +737,6 @@ if(NOT INTERN_BUILD_MOBILE OR NOT BUILD_CAFFE2_MOBILE)
       ${TORCH_SRC_DIR}/csrc/api/src/optim/schedulers/step_lr.cpp
       ${TORCH_SRC_DIR}/csrc/api/src/serialize/input-archive.cpp
       ${TORCH_SRC_DIR}/csrc/api/src/serialize/output-archive.cpp
-      ${TORCH_SRC_DIR}/csrc/utils/crash_handler.cpp
     )
   endif()
 
@@ -1076,10 +1075,9 @@ if(USE_TBB)
   target_link_libraries(torch_cpu PUBLIC TBB::tbb)
 endif()
 
-if(USE_BREAKPAD)
-  target_compile_definitions(torch_cpu PRIVATE ADD_BREAKPAD_SIGNAL_HANDLER)
-  target_include_directories(torch_cpu PRIVATE ${CMAKE_CURRENT_LIST_DIR}/../third_party ${CMAKE_CURRENT_LIST_DIR}/../third_party/breakpad/src)
-  target_link_libraries(torch_cpu PRIVATE breakpad)
+if(BUILD_CAFFE2 AND BUILD_CAFFE2_OPS AND USE_FBGEMM)
+  # FIXME: quantization/server/conv_dnnlowp_op.cc depends on fbgemm/src/RefImplementations.h
+  target_include_directories(torch_cpu PRIVATE ${CMAKE_CURRENT_LIST_DIR}/../third_party)
 endif()
 
   target_include_directories(torch_cpu PRIVATE ${ATen_CPU_INCLUDE})

cmake/Dependencies.cmake

@@ -1847,10 +1847,6 @@ set_target_properties(fmt-header-only PROPERTIES INTERFACE_COMPILE_FEATURES "")
 list(APPEND Caffe2_DEPENDENCY_LIBS fmt::fmt-header-only)
 set(BUILD_SHARED_LIBS ${TEMP_BUILD_SHARED_LIBS} CACHE BOOL "Build shared libs" FORCE)
 
-if(USE_BREAKPAD)
-  add_subdirectory(${CMAKE_CURRENT_LIST_DIR}/../third_party/breakpad)
-endif()
-
 # ---[ Kineto
 # edge profiler depends on KinetoProfiler but it only does cpu
 # profiling. Thus we dont need USE_CUDA/USE_ROCM

cmake/Summary.cmake

@@ -187,7 +187,6 @@ function(caffe2_print_configuration_summary)
     message(STATUS "  SELECTED_OP_LIST    : ${SELECTED_OP_LIST}")
   endif()
   message(STATUS "  USE_DEPLOY           : ${USE_DEPLOY}")
-  message(STATUS "  USE_BREAKPAD         : ${USE_BREAKPAD}")
   message(STATUS "  Public Dependencies  : ${Caffe2_PUBLIC_DEPENDENCY_LIBS}")
   message(STATUS "  Private Dependencies : ${Caffe2_DEPENDENCY_LIBS}")
   # coreml

test/test_cpp_extensions_jit.py

@@ -10,15 +10,12 @@
 import subprocess
 import glob
 
-import textwrap
-from multiprocessing import Process
-
 import torch.testing._internal.common_utils as common
 import torch
 import torch.backends.cudnn
 import torch.utils.cpp_extension
 from torch.utils.cpp_extension import CUDA_HOME, ROCM_HOME
-from torch.testing._internal.common_utils import gradcheck, TEST_WITH_ASAN, has_breakpad
+from torch.testing._internal.common_utils import gradcheck
 
 
 TEST_CUDA = torch.cuda.is_available() and CUDA_HOME is not None
@@ -869,80 +866,6 @@ def test_custom_compound_op_autograd(self):
 
         gradcheck(torch.ops.my.add, [a, b], eps=1e-2)
 
-    @staticmethod
-    def _crash_handler_test_process(stderr_file, destination):
-        # Code to enable dumps and trigger a segfault
-        if sys.platform == "win32":
-            destination = destination.replace("\\", "\\\\")
-            csrc = textwrap.dedent(f"""
-            #include <torch/torch.h>
-            #include <locale>
-            #include <iostream>
-            #include <codecvt>
-            #include <string>
-
-            int fail() {{
-                std::wstring_convert<std::codecvt_utf8_utf16<wchar_t>> converter;
-                std::string narrow("{destination}");
-                std::wstring wide = converter.from_bytes(narrow);
-                torch::crash_handler::enable_minidumps(wide.c_str());
-
-                volatile int* bad = nullptr;
-                return *bad;
-            }}
-            """)
-        else:
-            csrc = textwrap.dedent(f"""
-            #include <torch/torch.h>
-
-            int fail() {{
-                torch::crash_handler::enable_minidumps("{destination}");
-
-                volatile int* bad = nullptr;
-                return *bad;
-            }}
-            """)
-
-        # Some special stuff to overwrite stderr for a C++ extension
-        # Copied from: https://stackoverflow.com/questions/8804893/redirect-stdout-from-python-for-c-calls
-        sys.stdout.flush()
-        newstdout = os.dup(2)
-        devnull = os.open(stderr_file, os.O_WRONLY)
-        os.dup2(devnull, 2)
-        os.close(devnull)
-        sys.stdout = os.fdopen(newstdout, 'w')
-
-        module = torch.utils.cpp_extension.load_inline(
-            name="segfault",
-            cpp_sources=csrc,
-            functions=["fail"],
-        )
-        module.fail()
-
-    @unittest.skipIf(TEST_WITH_ASAN, "ASAN disables the crash handler's signal handler")
-    @unittest.skipIf(not has_breakpad(), "Built without breakpad")
-    @unittest.skipIf(os.environ.get("TEST_CONFIG") == "force_on_cpu", "fails on force_on_cpu config, tracked w/ #65253")
-    def test_crash_handler(self):
-        with tempfile.TemporaryDirectory() as temp_dir, tempfile.NamedTemporaryFile(delete=not sys.platform == "win32") as stderr:
-            # Use multiprocessing to spin up a separate process to make catching
-            # the segfault easier
-            p = Process(target=self._crash_handler_test_process, args=(stderr.name, temp_dir))
-            p.start()
-            p.join()
-
-            with open(stderr.name) as f:
-                result = f.read().strip()
-
-            # Check that the signal handler was called
-            self.assertTrue(result.startswith(f"Wrote minidump to {temp_dir}"))
-
-            with open(result.replace("Wrote minidump to ", ""), "rb") as dump_file:
-                dump_bytes = dump_file.read()
-
-                # Check that the file has the correct magic number
-                self.assertEqual(b"MDMP", dump_bytes[0:4])
-
-
 
 if __name__ == "__main__":
     common.run_tests()

test/test_utils.py

@@ -2,8 +2,6 @@
 
 import sys
 import os
-import contextlib
-import io
 import re
 import shutil
 import random
@@ -20,7 +18,7 @@
 import torch.utils.cpp_extension
 from torch.autograd._functions.utils import check_onnx_broadcast
 from torch.onnx.symbolic_opset9 import _prepare_onnx_paddings
-from torch.testing._internal.common_utils import has_breakpad, load_tests, IS_SANDCASTLE, IS_WINDOWS, TEST_WITH_ASAN
+from torch.testing._internal.common_utils import load_tests, IS_SANDCASTLE, IS_WINDOWS
 
 # load_tests from torch.testing._internal.common_utils is used to automatically filter tests for
 # sharding on sandcastle. This line silences flake warnings
@@ -610,32 +608,6 @@ def forward(self, x):
             ms(torch.tensor([False], dtype=torch.bool))
 
 
-class TestCrashHandler(TestCase):
-    @unittest.skipIf(TEST_WITH_ASAN, "ASAN disables the crash handler's signal handler")
-    @unittest.skipIf(not has_breakpad(), "Built without breakpad")
-    def test_python_exception_writing(self):
-        with tempfile.TemporaryDirectory() as temp_dir:
-            torch.utils._crash_handler.enable_minidumps(temp_dir)
-            torch.utils._crash_handler.enable_minidumps_on_exceptions()
-
-            files = os.listdir(temp_dir)
-            self.assertEqual(len(files), 0)
-
-            f = io.StringIO()
-            with contextlib.redirect_stderr(f):
-                try:
-                    @torch.jit.script
-                    def x(i: int):
-                        return i + "2"  # type: ignore[operator]
-                except RuntimeError as e:
-                    pass
-
-            files = os.listdir(temp_dir)
-            self.assertEqual(len(files), 1)
-            self.assertTrue(files[0].endswith(".dmp"))
-            torch.utils._crash_handler.disable_minidumps()
-
-
 @unittest.skipIf(IS_SANDCASTLE, "cpp_extension is OSS only")
 class TestStandaloneCPPJIT(TestCase):
     def test_load_standalone(self):

third_party/breakpad

@@ -821,7 +821,6 @@ torch_cpp_srcs = [
     "torch/csrc/api/src/optim/schedulers/step_lr.cpp",
     "torch/csrc/api/src/serialize/input-archive.cpp",
     "torch/csrc/api/src/serialize/output-archive.cpp",
-    "torch/csrc/utils/crash_handler.cpp",
 ]
 
 libtorch_python_cuda_core_sources = [

tools/build_variables.bzl

@@ -55,7 +55,6 @@
 #include <torch/csrc/utils/tensor_new.h>
 #include <torch/csrc/utils/tensor_numpy.h>
 #include <torch/csrc/utils/python_dispatch.h>
-#include <torch/csrc/utils/crash_handler.h>
 #include <torch/csrc/utils/python_arg_parser.h>
 #include <torch/csrc/utils/pycfunction_helpers.h>
 #include <torch/csrc/lazy/python/init.h>
@@ -65,7 +64,6 @@
 #include <torch/csrc/monitor/python_init.h>
 #include <torch/csrc/onnx/init.h>
 #include <torch/csrc/utils/init.h>
-#include <torch/csrc/utils/crash_handler.h>
 #include <torch/csrc/api/include/torch/python/init.h>
 
 #ifdef USE_DISTRIBUTED
@@ -820,7 +818,6 @@ PyObject* initModule() {
   torch::monitor::initMonitorBindings(module);
   torch::impl::dispatch::initDispatchBindings(module);
   torch::throughput_benchmark::initThroughputBenchmarkBindings(module);
-  torch::crash_handler::initCrashHandlerBindings(module);
   torch::autograd::initReturnTypes(module);
   torch::autograd::initNNFunctions(module);
   torch::autograd::initFFTFunctions(module);
@@ -874,10 +871,6 @@ PyObject* initModule() {
 
   // Automatically translate errors thrown from pybind11 functions
   py::register_exception_translator([](std::exception_ptr e) { // NOLINT
-    if (torch::crash_handler::is_enabled_on_exceptions()) {
-      torch::crash_handler::write_minidump();
-    }
-
     try {
       if (e) {
         std::rethrow_exception(e);

torch/csrc/Module.cpp

@@ -5,7 +5,6 @@
 #include <torch/csrc/autograd/grad_mode.h>
 #include <torch/csrc/autograd/profiler.h>
 #include <torch/csrc/api/include/torch/types.h>
-#include <torch/csrc/utils/crash_handler.h>
 #include <cstdint>
 
 namespace torch {