Quantized ops? #15

jbondc · 2015-11-09T17:10:49Z

In the data types section, there are quantized ops
http://tensorflow.org/resources/dims_types.md#data_types

Found a note here:

tensorflow/tensorflow/cc/ops/const_op.h

Line 65 in d6357a5

// TODO(josh11b): Support other types (e.g. quantized ints, float16).

Can you explain what these are?

The text was updated successfully, but these errors were encountered:

vrv · 2015-11-09T17:14:01Z

We are working on support for operators and kernels that take quantized (fixed-point) data -- we're still working on the right APIs to expose them, and with that we'll have more documentation on why and how they are used. Stay tuned!

jbondc · 2015-11-09T17:37:00Z

Awesome, this is great work 😮
Please give my sincere thanks to 🎅

martinwicke · 2015-12-16T06:49:29Z

Closing for now. When the quantized ops come online, they'll come with documentation.

dgschwend · 2016-03-02T13:50:30Z

@vrv Any news on fixed-point / quantized data type support?
I am designing an FPGA-based accelerator for CNNs as my master thesis in the next few months. It would be awesome to be able to train the models with fixed-point weights and activations.
Do you have any roadmap for fixed-point support?

…d of 'Y' (a.k.a. "Yes"). This fixes the issue unveiled by some of the regression tests (Thank you for reporting!). (tensorflow#15)

…d of 'Y' (a.k.a. "Yes"). This fixes the issue unveiled by some of the regression tests (Thank you for reporting!). (#15)

hustqmk · 2017-06-14T02:16:12Z

@dgschwend have you find the answer?

Integrate rocPRIM 0.3.1 milestone

Keep dims in BatchNormTraining

…eature/AIFORDES-324-reduce-op-optimization to ifx/develop * commit '2f9fb5129a43e2eacc6aeac2a068ed100b8cd688': Replace macros by std functions and optimize reduce operation Removed todos Removed dead code from reduce operation Added test for untested function in reduce kernel Remove floating point values from the eval phase of the reduce kernel ops Restructured kernels for reduce operation Adjusted reduce op structure to fit into the precompiler structure

amitport · 2020-11-07T09:00:38Z

@vrv could you please reopen, point to the correct doc, or confirm that is still should be considered internal (though it is exposed in many place by now)

Sync with upstream master

On some CI nodes (typically those with higher CPU core counts 128/256), the `//tensorflow/c/eager:c_api_distributed_test_gpu` test fails on an intermitent basis. When it does fail, the failures manifests as segfault at the end of the test, with the stack dump shown at the end of this commit message. The stack dump points the finger to a routine within the MKLDNN implementation. This is further confirmed by the observation that disabling the MKLDNN based Eigen contraction kernels (for ROCm) seems to make the crash go away. related JIRA ticket - https://ontrack-internal.amd.com/browse/SWDEV-313684 A previous commit disabled the `//tensorflow/c/eager:c_api_distributed_test` unit-test only in the CPU unit-tests CI job (for the same reason). That comit cannot be reverted, because this commit disables MKLDNN based Eigen contraction kernels *only* for the ROCm build. ``` Thread 191 "c_api_distribut" received signal SIGSEGV, Segmentation fault. [Switching to thread 191 (Thread 0x7ffc777fe700 (LWP 159004))] 0x00007fff54530000 in ?? () (gdb) where #0 0x00007fff54530000 in ?? () #1 0x00007fffd5d15ae4 in dnnl::impl::cpu::x64::avx_gemm_f32::sgemm_nocopy_driver(char const*, char const*, long, long, long, float const*, float const*, long, float const*, long, float const*, float*, long, float const*, float*) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/libexternal_Smkl_Udnn_Uv1_Slibmkl_Udnn.so #2 0x00007fffd5d166e1 in dnnl::impl::cpu::x64::jit_avx_gemm_f32(int, char const*, char const*, long const*, long const*, long const*, float const*, float const*, long const*, float const*, long const*, float const*, float*, long const*, float const*) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/libexternal_Smkl_Udnn_Uv1_Slibmkl_Udnn.so #3 0x00007fffd5e277ed in dnnl_status_t dnnl::impl::cpu::x64::gemm_driver<float, float, float>(char const*, char const*, char const*, long const*, long const*, long const*, float const*, float const*, long const*, float const*, float const*, long const*, float const*, float const*, float*, long const*, float const*, bool, dnnl::impl::cpu::x64::pack_type, dnnl::impl::cpu::x64::gemm_pack_storage_t*, bool) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/libexternal_Smkl_Udnn_Uv1_Slibmkl_Udnn.so #4 0x00007fffd5665056 in dnnl::impl::cpu::extended_sgemm(char const*, char const*, long const*, long const*, long const*, float const*, float const*, long const*, float const*, long const*, float const*, float*, long const*, float const*, bool) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/libexternal_Smkl_Udnn_Uv1_Slibmkl_Udnn.so #5 0x00007fffd52fe983 in dnnl_sgemm () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/libexternal_Smkl_Udnn_Uv1_Slibmkl_Udnn.so #6 0x0000555557187b0b in Eigen::internal::TensorContractionKernel<float, float, float, long, Eigen::internal::blas_data_mapper<float, long, 0, 0, 1>, Eigen::internal::TensorContractionInputMapper<float, long, 1, Eigen::TensorEvaluator<Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer>, Eigen::internal::TensorContractionInputMapper<float, long, 0, Eigen::TensorEvaluator<Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer> >::invoke(Eigen::internal::blas_data_mapper<float, long, 0, 0, 1> const&, Eigen::internal::ColMajorBlock<float, long> const&, Eigen::internal::ColMajorBlock<float, long> const&, long, long, long, float, float) () #7 0x000055555718dc76 in Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::EvalParallelContext<Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::NoCallback, true, true, false, 0>::kernel(long, long, long, bool) () #8 0x000055555718f327 in Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::EvalParallelContext<Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::NoCallback, true, true, false, 0>::signal_kernel(long, long, long, bool, bool) () #9 0x00005555571904cb in Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::EvalParallelContext<Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::NoCallback, true, true, false, 0>::pack_rhs(long, long) () #10 0x000055555718fd69 in Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::EvalParallelContext<Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::NoCallback, true, true, false, 0>::enqueue_packing_helper(long, long, long, bool) () #11 0x00007ffff6b607a1 in Eigen::ThreadPoolTempl<tensorflow::thread::EigenEnvironment>::WorkerLoop(int) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/_U_S_Stensorflow_Sc_Seager_Cc_Uapi_Udistributed_Utest_Ugpu___Utensorflow/libtensorflow_framework.so.2 #12 0x00007ffff6b5de93 in std::_Function_handler<void (), tensorflow::thread::EigenEnvironment::CreateThread(std::function<void ()>)::{lambda()#1}>::_M_invoke(std::_Any_data const&) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/_U_S_Stensorflow_Sc_Seager_Cc_Uapi_Udistributed_Utest_Ugpu___Utensorflow/libtensorflow_framework.so.2 #13 0x00007ffff6b40107 in tensorflow::(anonymous namespace)::PThread::ThreadFn(void*) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/_U_S_Stensorflow_Sc_Seager_Cc_Uapi_Udistributed_Utest_Ugpu___Utensorflow/libtensorflow_framework.so.2 #14 0x00007fffd1ca86db in start_thread () from /lib/x86_64-linux-gnu/libpthread.so.0 #15 0x00007fffd00b471f in clone () from /lib/x86_64-linux-gnu/libc.so.6 ```

On some CI nodes (typically those with higher CPU core counts 128/256), the `//tensorflow/c/eager:c_api_distributed_test_gpu` test fails on an intermitent basis. When it does fail, the failures manifests as segfault at the end of the test, with the stack dump shown at the end of this commit message. The stack dump points the finger to a routine within the MKLDNN implementation. This is further confirmed by the observation that disabling the MKLDNN based Eigen contraction kernels (for ROCm) seems to make the crash go away. related JIRA ticket - https://ontrack-internal.amd.com/browse/SWDEV-313684 A previous commit disabled the `//tensorflow/c/eager:c_api_distributed_test` unit-test only in the CPU unit-tests CI job (for the same reason). That comit cannot be reverted, because this commit disables MKLDNN based Eigen contraction kernels *only* for the ROCm build. ``` Thread 191 "c_api_distribut" received signal SIGSEGV, Segmentation fault. [Switching to thread 191 (Thread 0x7ffc777fe700 (LWP 159004))] 0x00007fff54530000 in ?? () (gdb) where #0 0x00007fff54530000 in ?? () #1 0x00007fffd5d15ae4 in dnnl::impl::cpu::x64::avx_gemm_f32::sgemm_nocopy_driver(char const*, char const*, long, long, long, float const*, float const*, long, float const*, long, float const*, float*, long, float const*, float*) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/libexternal_Smkl_Udnn_Uv1_Slibmkl_Udnn.so tensorflow#2 0x00007fffd5d166e1 in dnnl::impl::cpu::x64::jit_avx_gemm_f32(int, char const*, char const*, long const*, long const*, long const*, float const*, float const*, long const*, float const*, long const*, float const*, float*, long const*, float const*) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/libexternal_Smkl_Udnn_Uv1_Slibmkl_Udnn.so tensorflow#3 0x00007fffd5e277ed in dnnl_status_t dnnl::impl::cpu::x64::gemm_driver<float, float, float>(char const*, char const*, char const*, long const*, long const*, long const*, float const*, float const*, long const*, float const*, float const*, long const*, float const*, float const*, float*, long const*, float const*, bool, dnnl::impl::cpu::x64::pack_type, dnnl::impl::cpu::x64::gemm_pack_storage_t*, bool) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/libexternal_Smkl_Udnn_Uv1_Slibmkl_Udnn.so tensorflow#4 0x00007fffd5665056 in dnnl::impl::cpu::extended_sgemm(char const*, char const*, long const*, long const*, long const*, float const*, float const*, long const*, float const*, long const*, float const*, float*, long const*, float const*, bool) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/libexternal_Smkl_Udnn_Uv1_Slibmkl_Udnn.so tensorflow#5 0x00007fffd52fe983 in dnnl_sgemm () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/libexternal_Smkl_Udnn_Uv1_Slibmkl_Udnn.so tensorflow#6 0x0000555557187b0b in Eigen::internal::TensorContractionKernel<float, float, float, long, Eigen::internal::blas_data_mapper<float, long, 0, 0, 1>, Eigen::internal::TensorContractionInputMapper<float, long, 1, Eigen::TensorEvaluator<Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer>, Eigen::internal::TensorContractionInputMapper<float, long, 0, Eigen::TensorEvaluator<Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::ThreadPoolDevice>, Eigen::array<long, 1ul>, Eigen::array<long, 1ul>, 4, true, false, 0, Eigen::MakePointer> >::invoke(Eigen::internal::blas_data_mapper<float, long, 0, 0, 1> const&, Eigen::internal::ColMajorBlock<float, long> const&, Eigen::internal::ColMajorBlock<float, long> const&, long, long, long, float, float) () tensorflow#7 0x000055555718dc76 in Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::EvalParallelContext<Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::NoCallback, true, true, false, 0>::kernel(long, long, long, bool) () tensorflow#8 0x000055555718f327 in Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::EvalParallelContext<Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::NoCallback, true, true, false, 0>::signal_kernel(long, long, long, bool, bool) () tensorflow#9 0x00005555571904cb in Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::EvalParallelContext<Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::NoCallback, true, true, false, 0>::pack_rhs(long, long) () tensorflow#10 0x000055555718fd69 in Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::EvalParallelContext<Eigen::TensorEvaluator<Eigen::TensorContractionOp<Eigen::array<Eigen::IndexPair<long>, 1ul> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::TensorMap<Eigen::Tensor<float const, 2, 1, long>, 16, Eigen::MakePointer> const, Eigen::NoOpOutputKernel const> const, Eigen::ThreadPoolDevice>::NoCallback, true, true, false, 0>::enqueue_packing_helper(long, long, long, bool) () tensorflow#11 0x00007ffff6b607a1 in Eigen::ThreadPoolTempl<tensorflow::thread::EigenEnvironment>::WorkerLoop(int) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/_U_S_Stensorflow_Sc_Seager_Cc_Uapi_Udistributed_Utest_Ugpu___Utensorflow/libtensorflow_framework.so.2 tensorflow#12 0x00007ffff6b5de93 in std::_Function_handler<void (), tensorflow::thread::EigenEnvironment::CreateThread(std::function<void ()>)::{lambda()#1}>::_M_invoke(std::_Any_data const&) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/_U_S_Stensorflow_Sc_Seager_Cc_Uapi_Udistributed_Utest_Ugpu___Utensorflow/libtensorflow_framework.so.2 tensorflow#13 0x00007ffff6b40107 in tensorflow::(anonymous namespace)::PThread::ThreadFn(void*) () from /root/.cache/bazel/_bazel_root/efb88f6336d9c4a18216fb94287b8d97/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/c/eager/../../../_solib_local/_U_S_Stensorflow_Sc_Seager_Cc_Uapi_Udistributed_Utest_Ugpu___Utensorflow/libtensorflow_framework.so.2 tensorflow#14 0x00007fffd1ca86db in start_thread () from /lib/x86_64-linux-gnu/libpthread.so.0 tensorflow#15 0x00007fffd00b471f in clone () from /lib/x86_64-linux-gnu/libc.so.6 ```

… to Initialize() Imported from GitHub PR openxla/xla#12228 The first time that a NormThunk is executed, it will build a cudnn execution plan. This build step can hang if a NCCL collective is running at the same time. To fix this, I've moved the build step to take place during thunk initialization. We only observe this hang when using cudnn 9. Here's a backtrace from the hang that will be fixed: ``` Thread 585 (Thread 0x7fb9391ff640 (LWP 41364) "main.py"): #0 0x00007fd3d17cffd9 in ?? () from /lib/x86_64-linux-gnu/libc.so.6 #1 0x00007fd3d17da24f in pthread_rwlock_wrlock () from /lib/x86_64-linux-gnu/libc.so.6 #2 0x00007fd070967dfe in ?? () from /lib/x86_64-linux-gnu/libcuda.so.1 #3 0x00007fd0709c928a in ?? () from /lib/x86_64-linux-gnu/libcuda.so.1 #4 0x00007f1970d76102 in ?? () from /lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.1.0 #5 0x00007f1970f2c999 in ?? () from /lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.1.0 #6 0x00007f1970a7d4ab in ?? () from /lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.1.0 #7 0x00007f1970d0a9cb in ?? () from /lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.1.0 #8 0x00007fce60b2a98c in cudnn::backend::ExecutionPlan::finalize_internal() () from /lib/x86_64-linux-gnu/libcudnn_graph.so.9.1.0 #9 0x00007fce60aefbb1 in cudnn::backend::Descriptor::finalize() () from /lib/x86_64-linux-gnu/libcudnn_graph.so.9.1.0 #10 0x00007fce60b15bec in cudnnBackendFinalize () from /lib/x86_64-linux-gnu/libcudnn_graph.so.9.1.0 #11 0x00007fd2521b8f39 in cudnn_frontend::ExecutionPlanBuilder_v8::build() () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #12 0x00007fd2521734ba in stream_executor::gpu::(anonymous namespace)::GetExecPlanFromHeuristics(cudnn_frontend::OperationGraph_v8&&, stream_executor::gpu::(anonymous namespace)::CudnnHandle const&, bool) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #13 0x00007fd25216ff9b in stream_executor::gpu::CudnnSupport::NormRunnerFromDesc(stream_executor::Stream*, stream_executor::dnn::AlgorithmDesc const&, stream_executor::dnn::NormKind, double, stream_executor::dnn::TensorDescriptor const&, stream_executor::dnn::TensorDescriptor const&, stream_executor::dnn::TensorDescriptor const&, std::optional<stream_executor::dnn::TensorDescriptor>, std::optional<stream_executor::dnn::TensorDescriptor>, std::optional<stream_executor::dnn::TensorDescriptor>, std::optional<stream_executor::dnn::TensorDescriptor>, std::optional<stream_executor::dnn::TensorDescriptor>, std::optional<stream_executor::dnn::TensorDescriptor>) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #14 0x00007fd24e36b88b in stream_executor::dnn::NormOp::RunnerFromAlgorithmDesc(stream_executor::dnn::AlgorithmDesc const&, stream_executor::dnn::NormOp::Config, stream_executor::Stream*) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #15 0x00007fd24e36ae37 in stream_executor::dnn::LazyOpRunner<stream_executor::dnn::NormOp>::GetOrCreateRunner(stream_executor::dnn::NormOp::Config, stream_executor::Stream*)::{lambda()#1}::operator()() const () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #16 0x00007fd24e36adbc in void absl::lts_20230802::base_internal::CallOnceImpl<stream_executor::dnn::LazyOpRunner<stream_executor::dnn::NormOp>::GetOrCreateRunner(stream_executor::dnn::NormOp::Config, stream_executor::Stream*)::{lambda()#1}>(std::atomic<unsigned int>*, absl::lts_20230802::base_internal::SchedulingMode, stream_executor::dnn::LazyOpRunner<stream_executor::dnn::NormOp>::GetOrCreateRunner(stream_executor::dnn::NormOp::Config, stream_executor::Stream*)::{lambda()#1}&&) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #17 0x00007fd24e36a9bd in stream_executor::dnn::LazyOpRunner<stream_executor::dnn::NormOp>::GetOrCreateRunner(stream_executor::dnn::NormOp::Config, stream_executor::Stream*) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #18 0x00007fd24e369d29 in xla::gpu::RunGpuNorm(xla::gpu::GpuNormConfig const&, stream_executor::DeviceMemoryBase const&, stream_executor::DeviceMemoryBase const&, stream_executor::DeviceMemoryBase const&, std::optional<stream_executor::DeviceMemoryBase>, std::optional<stream_executor::DeviceMemoryBase>, std::optional<stream_executor::DeviceMemoryBase>, std::optional<stream_executor::DeviceMemoryBase>, std::optional<stream_executor::DeviceMemoryBase>, std::optional<stream_executor::DeviceMemoryBase>, stream_executor::DeviceMemoryBase const&, stream_executor::Stream*, xla::gpu::RunNormOptions) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #19 0x00007fd24e368be6 in xla::gpu::NormThunk::ExecuteOnStream(xla::gpu::Thunk::ExecuteParams const&) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so ``` Copybara import of the project: -- f53533087ba1ddcf65ad7cc6268ee89de4690d15 by Trevor Morris <tmorris@nvidia.com>: Fix hang with cudnn layer norm by moving cudnn init to Initialize() Merging this change closes #12228 FUTURE_COPYBARA_INTEGRATE_REVIEW=openxla/xla#12228 from trevor-m:tmorris-norm-init f53533087ba1ddcf65ad7cc6268ee89de4690d15 PiperOrigin-RevId: 633207155

… to Initialize() Imported from GitHub PR openxla/xla#12228 The first time that a NormThunk is executed, it will build a cudnn execution plan. This build step can hang if a NCCL collective is running at the same time. To fix this, I've moved the build step to take place during thunk initialization. We only observe this hang when using cudnn 9. Here's a backtrace from the hang that will be fixed: ``` Thread 585 (Thread 0x7fb9391ff640 (LWP 41364) "main.py"): #0 0x00007fd3d17cffd9 in ?? () from /lib/x86_64-linux-gnu/libc.so.6 #1 0x00007fd3d17da24f in pthread_rwlock_wrlock () from /lib/x86_64-linux-gnu/libc.so.6 #2 0x00007fd070967dfe in ?? () from /lib/x86_64-linux-gnu/libcuda.so.1 #3 0x00007fd0709c928a in ?? () from /lib/x86_64-linux-gnu/libcuda.so.1 #4 0x00007f1970d76102 in ?? () from /lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.1.0 #5 0x00007f1970f2c999 in ?? () from /lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.1.0 #6 0x00007f1970a7d4ab in ?? () from /lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.1.0 #7 0x00007f1970d0a9cb in ?? () from /lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.1.0 #8 0x00007fce60b2a98c in cudnn::backend::ExecutionPlan::finalize_internal() () from /lib/x86_64-linux-gnu/libcudnn_graph.so.9.1.0 #9 0x00007fce60aefbb1 in cudnn::backend::Descriptor::finalize() () from /lib/x86_64-linux-gnu/libcudnn_graph.so.9.1.0 #10 0x00007fce60b15bec in cudnnBackendFinalize () from /lib/x86_64-linux-gnu/libcudnn_graph.so.9.1.0 #11 0x00007fd2521b8f39 in cudnn_frontend::ExecutionPlanBuilder_v8::build() () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #12 0x00007fd2521734ba in stream_executor::gpu::(anonymous namespace)::GetExecPlanFromHeuristics(cudnn_frontend::OperationGraph_v8&&, stream_executor::gpu::(anonymous namespace)::CudnnHandle const&, bool) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #13 0x00007fd25216ff9b in stream_executor::gpu::CudnnSupport::NormRunnerFromDesc(stream_executor::Stream*, stream_executor::dnn::AlgorithmDesc const&, stream_executor::dnn::NormKind, double, stream_executor::dnn::TensorDescriptor const&, stream_executor::dnn::TensorDescriptor const&, stream_executor::dnn::TensorDescriptor const&, std::optional<stream_executor::dnn::TensorDescriptor>, std::optional<stream_executor::dnn::TensorDescriptor>, std::optional<stream_executor::dnn::TensorDescriptor>, std::optional<stream_executor::dnn::TensorDescriptor>, std::optional<stream_executor::dnn::TensorDescriptor>, std::optional<stream_executor::dnn::TensorDescriptor>) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #14 0x00007fd24e36b88b in stream_executor::dnn::NormOp::RunnerFromAlgorithmDesc(stream_executor::dnn::AlgorithmDesc const&, stream_executor::dnn::NormOp::Config, stream_executor::Stream*) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #15 0x00007fd24e36ae37 in stream_executor::dnn::LazyOpRunner<stream_executor::dnn::NormOp>::GetOrCreateRunner(stream_executor::dnn::NormOp::Config, stream_executor::Stream*)::{lambda()#1}::operator()() const () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #16 0x00007fd24e36adbc in void absl::lts_20230802::base_internal::CallOnceImpl<stream_executor::dnn::LazyOpRunner<stream_executor::dnn::NormOp>::GetOrCreateRunner(stream_executor::dnn::NormOp::Config, stream_executor::Stream*)::{lambda()#1}>(std::atomic<unsigned int>*, absl::lts_20230802::base_internal::SchedulingMode, stream_executor::dnn::LazyOpRunner<stream_executor::dnn::NormOp>::GetOrCreateRunner(stream_executor::dnn::NormOp::Config, stream_executor::Stream*)::{lambda()#1}&&) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #17 0x00007fd24e36a9bd in stream_executor::dnn::LazyOpRunner<stream_executor::dnn::NormOp>::GetOrCreateRunner(stream_executor::dnn::NormOp::Config, stream_executor::Stream*) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #18 0x00007fd24e369d29 in xla::gpu::RunGpuNorm(xla::gpu::GpuNormConfig const&, stream_executor::DeviceMemoryBase const&, stream_executor::DeviceMemoryBase const&, stream_executor::DeviceMemoryBase const&, std::optional<stream_executor::DeviceMemoryBase>, std::optional<stream_executor::DeviceMemoryBase>, std::optional<stream_executor::DeviceMemoryBase>, std::optional<stream_executor::DeviceMemoryBase>, std::optional<stream_executor::DeviceMemoryBase>, std::optional<stream_executor::DeviceMemoryBase>, stream_executor::DeviceMemoryBase const&, stream_executor::Stream*, xla::gpu::RunNormOptions) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so #19 0x00007fd24e368be6 in xla::gpu::NormThunk::ExecuteOnStream(xla::gpu::Thunk::ExecuteParams const&) () from /usr/local/lib/python3.10/dist-packages/jaxlib/xla_extension.so ``` Copybara import of the project: -- f53533087ba1ddcf65ad7cc6268ee89de4690d15 by Trevor Morris <tmorris@nvidia.com>: Fix hang with cudnn layer norm by moving cudnn init to Initialize() Merging this change closes #12228 PiperOrigin-RevId: 633220207

…r RunBackend. Both of these call into LLVM code that reads the compiler options. Fixes the following race: ``` WARNING: ThreadSanitizer: data race (pid=869815) Read of size 1 at 0x7f8b24effc08 by thread T65: #0 llvm::cl::opt_storage<bool, false, false>::getValue() const /proc/self/cwd/external/llvm-project/llvm/include/llvm/Support/CommandLine.h:1406:38 (xla_extension.so+0xa281417) (BuildId: 7f5d2098f168c4db) #1 llvm::cl::opt_storage<bool, false, false>::operator bool() const /proc/self/cwd/external/llvm-project/llvm/include/llvm/Support/CommandLine.h:1410:38 (xla_extension.so+0xa281417) #2 llvm::CodeGenTargetMachineImpl::CodeGenTargetMachineImpl(llvm::Target const&, llvm::StringRef, llvm::Triple const&, llvm::StringRef, llvm::StringRef, llvm::TargetOptions const&, llvm::Reloc::Model, llvm::CodeModel::Model, llvm::CodeGenOptLevel) /proc/self/cwd/external/llvm-project/llvm/lib/CodeGen/CodeGenTargetMachineImpl.cpp:97:7 (xla_extension.so+0xa281417) #3 llvm::X86TargetMachine::X86TargetMachine(llvm::Target const&, llvm::Triple const&, llvm::StringRef, llvm::StringRef, llvm::TargetOptions const&, std::optional<llvm::Reloc::Model>, std::optional<llvm::CodeModel::Model>, llvm::CodeGenOptLevel, bool) /proc/self/cwd/external/llvm-project/llvm/lib/Target/X86/X86TargetMachine.cpp:236:7 (xla_extension.so+0x9803b80) (BuildId: 7f5d2098f168c4db) #4 llvm::RegisterTargetMachine<llvm::X86TargetMachine>::Allocator(llvm::Target const&, llvm::Triple const&, llvm::StringRef, llvm::StringRef, llvm::TargetOptions const&, std::optional<llvm::Reloc::Model>, std::optional<llvm::CodeModel::Model>, llvm::CodeGenOptLevel, bool) /proc/self/cwd/external/llvm-project/llvm/include/llvm/MC/TargetRegistry.h:1258:16 (xla_extension.so+0x980757a) (BuildId: 7f5d2098f168c4db) #5 llvm::Target::createTargetMachine(llvm::StringRef, llvm::StringRef, llvm::StringRef, llvm::TargetOptions const&, std::optional<llvm::Reloc::Model>, std::optional<llvm::CodeModel::Model>, llvm::CodeGenOptLevel, bool) const /proc/self/cwd/external/llvm-project/llvm/include/llvm/MC/TargetRegistry.h:462:12 (xla_extension.so+0x94ba529) (BuildId: 7f5d2098f168c4db) #6 llvm::EngineBuilder::selectTarget(llvm::Triple const&, llvm::StringRef, llvm::StringRef, llvm::SmallVectorImpl<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char>>> const&) /proc/self/cwd/external/llvm-project/llvm/lib/ExecutionEngine/TargetSelect.cpp:88:18 (xla_extension.so+0x94ba529) #7 xla::cpu::JitCompiler::InferTargetMachine(llvm::TargetOptions const&, llvm::CodeGenOptLevel, std::optional<tsl::port::CPUFeature>) /proc/self/cwd/external/xla/xla/backends/cpu/codegen/jit_compiler.cc:88:12 (xla_extension.so+0x48d070f) (BuildId: 7f5d2098f168c4db) #8 xla::cpu::CpuCompiler::RunHloPasses(std::unique_ptr<xla::HloModule, std::default_delete<xla::HloModule>>, stream_executor::StreamExecutor*, xla::Compiler::CompileOptions const&) /proc/self/cwd/external/xla/xla/service/cpu/cpu_compiler.cc:1017:3 (xla_extension.so+0x2f6dc47) (BuildId: 7f5d2098f168c4db) #9 xla::JitCompile(xla::XlaComputation const&, absl::lts_20230802::Span<xla::Shape const* const>, xla::ExecutableBuildOptions const&, xla::ExecutionOptions const&, xla::Compiler::CompileOptions const&, int, std::function<void (xla::HloModuleConfig&)>) /proc/self/cwd/external/xla/xla/pjrt/cpu/cpu_client.cc:749:3 (xla_extension.so+0x2f127e2) (BuildId: 7f5d2098f168c4db) #10 xla::TfrtCpuClient::Compile(xla::XlaComputation const&, xla::CompileOptions) /proc/self/cwd/external/xla/xla/pjrt/cpu/cpu_client.cc:842:3 (xla_extension.so+0x2f127e2) #11 xla::TfrtCpuClient::Compile(mlir::ModuleOp, xla::CompileOptions) /proc/self/cwd/external/xla/xla/pjrt/cpu/cpu_client.cc:888:10 (xla_extension.so+0x2f13da2) (BuildId: 7f5d2098f168c4db) #12 xla::ifrt::PjRtLoadedExecutable::Create(xla::ifrt::PjRtCompatibleClient*, mlir::ModuleOp, xla::CompileOptions, std::vector<tsl::RCReference<xla::ifrt::LoadedHostCallback>, std::allocator<tsl::RCReference<xla::ifrt::LoadedHostCallback>>>) /proc/self/cwd/external/xla/xla/python/pjrt_ifrt/pjrt_executable.cc:258:3 (xla_extension.so+0xdd04d77) (BuildId: 7f5d2098f168c4db) #13 xla::ifrt::PjRtCompiler::Compile(std::unique_ptr<xla::ifrt::Program, std::default_delete<xla::ifrt::Program>>, std::unique_ptr<xla::ifrt::CompileOptions, std::default_delete<xla::ifrt::CompileOptions>>) /proc/self/cwd/external/xla/xla/python/pjrt_ifrt/pjrt_compiler.cc:97:10 (xla_extension.so+0xdcfd29b) (BuildId: 7f5d2098f168c4db) #14 xla::PyClient::CompileIfrtProgram(xla::nb_class_ptr<xla::PyClient>, std::unique_ptr<xla::ifrt::Program, std::default_delete<xla::ifrt::Program>>, std::unique_ptr<xla::ifrt::CompileOptions, std::default_delete<xla::ifrt::CompileOptions>>) /proc/self/cwd/external/xla/xla/python/py_client.cc:443:5 (xla_extension.so+0xc62a228) (BuildId: 7f5d2098f168c4db) #15 xla::PyClient::Compile(xla::nb_class_ptr<xla::PyClient>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char>>, xla::CompileOptions, std::vector<nanobind::capsule, std::allocator<nanobind::capsule>>) /proc/self/cwd/external/xla/xla/python/py_client.cc:466:10 (xla_extension.so+0xc62b514) (BuildId: 7f5d2098f168c4db) Previous write of size 1 at 0x7f8b24effc08 by thread T66 (mutexes: write M0): #0 void llvm::cl::opt_storage<bool, false, false>::setValue<bool>(bool const&, bool) /proc/self/cwd/external/llvm-project/llvm/include/llvm/Support/CommandLine.h:1401:11 (xla_extension.so+0x100bace9) (BuildId: 7f5d2098f168c4db) #1 void llvm::cl::opt<bool, false, llvm::cl::parser<bool>>::setDefaultImpl<bool, void>() /proc/self/cwd/external/llvm-project/llvm/include/llvm/Support/CommandLine.h (xla_extension.so+0x100bace9) #2 llvm::cl::opt<bool, false, llvm::cl::parser<bool>>::setDefault() /proc/self/cwd/external/llvm-project/llvm/include/llvm/Support/CommandLine.h:1474:32 (xla_extension.so+0x100bace9) #3 llvm::cl::Option::reset() /proc/self/cwd/external/llvm-project/llvm/lib/Support/CommandLine.cpp:460:3 (xla_extension.so+0x100cac0e) (BuildId: 7f5d2098f168c4db) #4 (anonymous namespace)::CommandLineParser::ResetAllOptionOccurrences() /proc/self/cwd/external/llvm-project/llvm/lib/Support/CommandLine.cpp:1478:17 (xla_extension.so+0x100cac0e) #5 llvm::cl::ResetAllOptionOccurrences() /proc/self/cwd/external/llvm-project/llvm/lib/Support/CommandLine.cpp:2831:17 (xla_extension.so+0x100caa72) (BuildId: 7f5d2098f168c4db) #6 xla::llvm_ir::LLVMCommandLineOptionsLock::LLVMCommandLineOptionsLock(std::vector<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char>>, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char>>>> const&) /proc/self/cwd/external/xla/xla/service/llvm_ir/llvm_command_line_options.cc:70:5 (xla_extension.so+0x91d69f4) (BuildId: 7f5d2098f168c4db) #7 xla::cpu::CpuCompiler::RunBackend(std::unique_ptr<xla::HloModule, std::default_delete<xla::HloModule>>, stream_executor::StreamExecutor*, xla::Compiler::CompileOptions const&) /proc/self/cwd/external/xla/xla/service/cpu/cpu_compiler.cc:1727:39 (xla_extension.so+0x2f781c8) (BuildId: 7f5d2098f168c4db) #8 xla::JitCompile(xla::XlaComputation const&, absl::lts_20230802::Span<xla::Shape const* const>, xla::ExecutableBuildOptions const&, xla::ExecutionOptions const&, xla::Compiler::CompileOptions const&, int, std::function<void (xla::HloModuleConfig&)>) /proc/self/cwd/external/xla/xla/pjrt/cpu/cpu_client.cc:754:19 (xla_extension.so+0x2f12883) (BuildId: 7f5d2098f168c4db) #9 xla::TfrtCpuClient::Compile(xla::XlaComputation const&, xla::CompileOptions) /proc/self/cwd/external/xla/xla/pjrt/cpu/cpu_client.cc:842:3 (xla_extension.so+0x2f12883) #10 xla::TfrtCpuClient::Compile(mlir::ModuleOp, xla::CompileOptions) /proc/self/cwd/external/xla/xla/pjrt/cpu/cpu_client.cc:888:10 (xla_extension.so+0x2f13da2) (BuildId: 7f5d2098f168c4db) #11 xla::ifrt::PjRtLoadedExecutable::Create(xla::ifrt::PjRtCompatibleClient*, mlir::ModuleOp, xla::CompileOptions, std::vector<tsl::RCReference<xla::ifrt::LoadedHostCallback>, std::allocator<tsl::RCReference<xla::ifrt::LoadedHostCallback>>>) /proc/self/cwd/external/xla/xla/python/pjrt_ifrt/pjrt_executable.cc:258:3 (xla_extension.so+0xdd04d77) (BuildId: 7f5d2098f168c4db) #12 xla::ifrt::PjRtCompiler::Compile(std::unique_ptr<xla::ifrt::Program, std::default_delete<xla::ifrt::Program>>, std::unique_ptr<xla::ifrt::CompileOptions, std::default_delete<xla::ifrt::CompileOptions>>) /proc/self/cwd/external/xla/xla/python/pjrt_ifrt/pjrt_compiler.cc:97:10 (xla_extension.so+0xdcfd29b) (BuildId: 7f5d2098f168c4db) #13 xla::PyClient::CompileIfrtProgram(xla::nb_class_ptr<xla::PyClient>, std::unique_ptr<xla::ifrt::Program, std::default_delete<xla::ifrt::Program>>, std::unique_ptr<xla::ifrt::CompileOptions, std::default_delete<xla::ifrt::CompileOptions>>) /proc/self/cwd/external/xla/xla/python/py_client.cc:443:5 (xla_extension.so+0xc62a228) (BuildId: 7f5d2098f168c4db) #14 xla::PyClient::Compile(xla::nb_class_ptr<xla::PyClient>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char>>, xla::CompileOptions, std::vector<nanobind::capsule, std::allocator<nanobind::capsule>>) /proc/self/cwd/external/xla/xla/python/py_client.cc:466:10 (xla_extension.so+0xc62b514) (BuildId: 7f5d2098f168c4db) ``` PiperOrigin-RevId: 707655482

…r RunBackend. Both of these call into LLVM code that reads the compiler options. Fixes the following race: ``` WARNING: ThreadSanitizer: data race (pid=869815) Read of size 1 at 0x7f8b24effc08 by thread T65: #0 llvm::cl::opt_storage<bool, false, false>::getValue() const /proc/self/cwd/external/llvm-project/llvm/include/llvm/Support/CommandLine.h:1406:38 (xla_extension.so+0xa281417) (BuildId: 7f5d2098f168c4db) #1 llvm::cl::opt_storage<bool, false, false>::operator bool() const /proc/self/cwd/external/llvm-project/llvm/include/llvm/Support/CommandLine.h:1410:38 (xla_extension.so+0xa281417) #2 llvm::CodeGenTargetMachineImpl::CodeGenTargetMachineImpl(llvm::Target const&, llvm::StringRef, llvm::Triple const&, llvm::StringRef, llvm::StringRef, llvm::TargetOptions const&, llvm::Reloc::Model, llvm::CodeModel::Model, llvm::CodeGenOptLevel) /proc/self/cwd/external/llvm-project/llvm/lib/CodeGen/CodeGenTargetMachineImpl.cpp:97:7 (xla_extension.so+0xa281417) #3 llvm::X86TargetMachine::X86TargetMachine(llvm::Target const&, llvm::Triple const&, llvm::StringRef, llvm::StringRef, llvm::TargetOptions const&, std::optional<llvm::Reloc::Model>, std::optional<llvm::CodeModel::Model>, llvm::CodeGenOptLevel, bool) /proc/self/cwd/external/llvm-project/llvm/lib/Target/X86/X86TargetMachine.cpp:236:7 (xla_extension.so+0x9803b80) (BuildId: 7f5d2098f168c4db) #4 llvm::RegisterTargetMachine<llvm::X86TargetMachine>::Allocator(llvm::Target const&, llvm::Triple const&, llvm::StringRef, llvm::StringRef, llvm::TargetOptions const&, std::optional<llvm::Reloc::Model>, std::optional<llvm::CodeModel::Model>, llvm::CodeGenOptLevel, bool) /proc/self/cwd/external/llvm-project/llvm/include/llvm/MC/TargetRegistry.h:1258:16 (xla_extension.so+0x980757a) (BuildId: 7f5d2098f168c4db) #5 llvm::Target::createTargetMachine(llvm::StringRef, llvm::StringRef, llvm::StringRef, llvm::TargetOptions const&, std::optional<llvm::Reloc::Model>, std::optional<llvm::CodeModel::Model>, llvm::CodeGenOptLevel, bool) const /proc/self/cwd/external/llvm-project/llvm/include/llvm/MC/TargetRegistry.h:462:12 (xla_extension.so+0x94ba529) (BuildId: 7f5d2098f168c4db) #6 llvm::EngineBuilder::selectTarget(llvm::Triple const&, llvm::StringRef, llvm::StringRef, llvm::SmallVectorImpl<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char>>> const&) /proc/self/cwd/external/llvm-project/llvm/lib/ExecutionEngine/TargetSelect.cpp:88:18 (xla_extension.so+0x94ba529) #7 xla::cpu::JitCompiler::InferTargetMachine(llvm::TargetOptions const&, llvm::CodeGenOptLevel, std::optional<tsl::port::CPUFeature>) /proc/self/cwd/external/xla/xla/backends/cpu/codegen/jit_compiler.cc:88:12 (xla_extension.so+0x48d070f) (BuildId: 7f5d2098f168c4db) #8 xla::cpu::CpuCompiler::RunHloPasses(std::unique_ptr<xla::HloModule, std::default_delete<xla::HloModule>>, stream_executor::StreamExecutor*, xla::Compiler::CompileOptions const&) /proc/self/cwd/external/xla/xla/service/cpu/cpu_compiler.cc:1017:3 (xla_extension.so+0x2f6dc47) (BuildId: 7f5d2098f168c4db) #9 xla::JitCompile(xla::XlaComputation const&, absl::lts_20230802::Span<xla::Shape const* const>, xla::ExecutableBuildOptions const&, xla::ExecutionOptions const&, xla::Compiler::CompileOptions const&, int, std::function<void (xla::HloModuleConfig&)>) /proc/self/cwd/external/xla/xla/pjrt/cpu/cpu_client.cc:749:3 (xla_extension.so+0x2f127e2) (BuildId: 7f5d2098f168c4db) #10 xla::TfrtCpuClient::Compile(xla::XlaComputation const&, xla::CompileOptions) /proc/self/cwd/external/xla/xla/pjrt/cpu/cpu_client.cc:842:3 (xla_extension.so+0x2f127e2) #11 xla::TfrtCpuClient::Compile(mlir::ModuleOp, xla::CompileOptions) /proc/self/cwd/external/xla/xla/pjrt/cpu/cpu_client.cc:888:10 (xla_extension.so+0x2f13da2) (BuildId: 7f5d2098f168c4db) #12 xla::ifrt::PjRtLoadedExecutable::Create(xla::ifrt::PjRtCompatibleClient*, mlir::ModuleOp, xla::CompileOptions, std::vector<tsl::RCReference<xla::ifrt::LoadedHostCallback>, std::allocator<tsl::RCReference<xla::ifrt::LoadedHostCallback>>>) /proc/self/cwd/external/xla/xla/python/pjrt_ifrt/pjrt_executable.cc:258:3 (xla_extension.so+0xdd04d77) (BuildId: 7f5d2098f168c4db) #13 xla::ifrt::PjRtCompiler::Compile(std::unique_ptr<xla::ifrt::Program, std::default_delete<xla::ifrt::Program>>, std::unique_ptr<xla::ifrt::CompileOptions, std::default_delete<xla::ifrt::CompileOptions>>) /proc/self/cwd/external/xla/xla/python/pjrt_ifrt/pjrt_compiler.cc:97:10 (xla_extension.so+0xdcfd29b) (BuildId: 7f5d2098f168c4db) #14 xla::PyClient::CompileIfrtProgram(xla::nb_class_ptr<xla::PyClient>, std::unique_ptr<xla::ifrt::Program, std::default_delete<xla::ifrt::Program>>, std::unique_ptr<xla::ifrt::CompileOptions, std::default_delete<xla::ifrt::CompileOptions>>) /proc/self/cwd/external/xla/xla/python/py_client.cc:443:5 (xla_extension.so+0xc62a228) (BuildId: 7f5d2098f168c4db) #15 xla::PyClient::Compile(xla::nb_class_ptr<xla::PyClient>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char>>, xla::CompileOptions, std::vector<nanobind::capsule, std::allocator<nanobind::capsule>>) /proc/self/cwd/external/xla/xla/python/py_client.cc:466:10 (xla_extension.so+0xc62b514) (BuildId: 7f5d2098f168c4db) Previous write of size 1 at 0x7f8b24effc08 by thread T66 (mutexes: write M0): #0 void llvm::cl::opt_storage<bool, false, false>::setValue<bool>(bool const&, bool) /proc/self/cwd/external/llvm-project/llvm/include/llvm/Support/CommandLine.h:1401:11 (xla_extension.so+0x100bace9) (BuildId: 7f5d2098f168c4db) #1 void llvm::cl::opt<bool, false, llvm::cl::parser<bool>>::setDefaultImpl<bool, void>() /proc/self/cwd/external/llvm-project/llvm/include/llvm/Support/CommandLine.h (xla_extension.so+0x100bace9) #2 llvm::cl::opt<bool, false, llvm::cl::parser<bool>>::setDefault() /proc/self/cwd/external/llvm-project/llvm/include/llvm/Support/CommandLine.h:1474:32 (xla_extension.so+0x100bace9) #3 llvm::cl::Option::reset() /proc/self/cwd/external/llvm-project/llvm/lib/Support/CommandLine.cpp:460:3 (xla_extension.so+0x100cac0e) (BuildId: 7f5d2098f168c4db) #4 (anonymous namespace)::CommandLineParser::ResetAllOptionOccurrences() /proc/self/cwd/external/llvm-project/llvm/lib/Support/CommandLine.cpp:1478:17 (xla_extension.so+0x100cac0e) #5 llvm::cl::ResetAllOptionOccurrences() /proc/self/cwd/external/llvm-project/llvm/lib/Support/CommandLine.cpp:2831:17 (xla_extension.so+0x100caa72) (BuildId: 7f5d2098f168c4db) #6 xla::llvm_ir::LLVMCommandLineOptionsLock::LLVMCommandLineOptionsLock(std::vector<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char>>, std::allocator<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char>>>> const&) /proc/self/cwd/external/xla/xla/service/llvm_ir/llvm_command_line_options.cc:70:5 (xla_extension.so+0x91d69f4) (BuildId: 7f5d2098f168c4db) #7 xla::cpu::CpuCompiler::RunBackend(std::unique_ptr<xla::HloModule, std::default_delete<xla::HloModule>>, stream_executor::StreamExecutor*, xla::Compiler::CompileOptions const&) /proc/self/cwd/external/xla/xla/service/cpu/cpu_compiler.cc:1727:39 (xla_extension.so+0x2f781c8) (BuildId: 7f5d2098f168c4db) #8 xla::JitCompile(xla::XlaComputation const&, absl::lts_20230802::Span<xla::Shape const* const>, xla::ExecutableBuildOptions const&, xla::ExecutionOptions const&, xla::Compiler::CompileOptions const&, int, std::function<void (xla::HloModuleConfig&)>) /proc/self/cwd/external/xla/xla/pjrt/cpu/cpu_client.cc:754:19 (xla_extension.so+0x2f12883) (BuildId: 7f5d2098f168c4db) #9 xla::TfrtCpuClient::Compile(xla::XlaComputation const&, xla::CompileOptions) /proc/self/cwd/external/xla/xla/pjrt/cpu/cpu_client.cc:842:3 (xla_extension.so+0x2f12883) #10 xla::TfrtCpuClient::Compile(mlir::ModuleOp, xla::CompileOptions) /proc/self/cwd/external/xla/xla/pjrt/cpu/cpu_client.cc:888:10 (xla_extension.so+0x2f13da2) (BuildId: 7f5d2098f168c4db) #11 xla::ifrt::PjRtLoadedExecutable::Create(xla::ifrt::PjRtCompatibleClient*, mlir::ModuleOp, xla::CompileOptions, std::vector<tsl::RCReference<xla::ifrt::LoadedHostCallback>, std::allocator<tsl::RCReference<xla::ifrt::LoadedHostCallback>>>) /proc/self/cwd/external/xla/xla/python/pjrt_ifrt/pjrt_executable.cc:258:3 (xla_extension.so+0xdd04d77) (BuildId: 7f5d2098f168c4db) #12 xla::ifrt::PjRtCompiler::Compile(std::unique_ptr<xla::ifrt::Program, std::default_delete<xla::ifrt::Program>>, std::unique_ptr<xla::ifrt::CompileOptions, std::default_delete<xla::ifrt::CompileOptions>>) /proc/self/cwd/external/xla/xla/python/pjrt_ifrt/pjrt_compiler.cc:97:10 (xla_extension.so+0xdcfd29b) (BuildId: 7f5d2098f168c4db) #13 xla::PyClient::CompileIfrtProgram(xla::nb_class_ptr<xla::PyClient>, std::unique_ptr<xla::ifrt::Program, std::default_delete<xla::ifrt::Program>>, std::unique_ptr<xla::ifrt::CompileOptions, std::default_delete<xla::ifrt::CompileOptions>>) /proc/self/cwd/external/xla/xla/python/py_client.cc:443:5 (xla_extension.so+0xc62a228) (BuildId: 7f5d2098f168c4db) #14 xla::PyClient::Compile(xla::nb_class_ptr<xla::PyClient>, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char>>, xla::CompileOptions, std::vector<nanobind::capsule, std::allocator<nanobind::capsule>>) /proc/self/cwd/external/xla/xla/python/py_client.cc:466:10 (xla_extension.so+0xc62b514) (BuildId: 7f5d2098f168c4db) ``` PiperOrigin-RevId: 707721170

teamdandelion added the type:docs-bug Document issues label Nov 9, 2015

vrv mentioned this issue Dec 12, 2015

What is quantized data type? For instance qint8, quint8, qint32 #494

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martinwicke closed this as completed Dec 16, 2015

alphaf52 mentioned this issue Apr 19, 2016

recurrent layer on top of convolution layer fails with GPU #2015

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wangyongliang mentioned this issue Apr 27, 2016

core dump when import tensorflow #2129

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This was referenced Jul 10, 2016

Segmentation fault on tensorflow 0.9.0 #2773

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Segmentation fault, import tensorflow, tensorflow 0.9, mac osx #3263

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pmousoul mentioned this issue Sep 11, 2016

Error malloc(): memory corruption #3442

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danielgordon10 mentioned this issue Dec 10, 2016

Running summary call crashes sporadically #6195

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aseuteurideu mentioned this issue Dec 13, 2016

in debug mode, got Assertion `cudaGetLastError() == cudaSuccess' failed #6285

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Hvass-Labs mentioned this issue Jan 9, 2017

Feature suggestion: Loss Normalization #6414

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GeorgianaPetria mentioned this issue Jan 31, 2017

TensorFlow demo app crashes with my own model #4451

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mkabra mentioned this issue Feb 14, 2017

Seg fault when using tf session with opencv 3 #7378

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bluezone2015 mentioned this issue Mar 8, 2017

import tensorflow Segmentation fault (core dumped) #8197

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gunan pushed a commit that referenced this issue Mar 30, 2017

Fixed calling libxsmm_spmdm_* by supplying 'T' for "transpose" instea…

709e9c4

…d of 'Y' (a.k.a. "Yes"). This fixes the issue unveiled by some of the regression tests (Thank you for reporting!). (#15)

sschaetz referenced this issue in ButterflyNetwork/tensorflow Apr 6, 2017

Add Bias and Activations (#15)

9994aea

hexujun mentioned this issue Apr 10, 2017

android libtensorflow_inference.so run crash (signal 6 (SIGABRT)) #9096

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zhangdingfei mentioned this issue Jun 21, 2017

tensorflow-1.2.0 import tensorflow Segmentation fault #10870

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sj6077 mentioned this issue Aug 11, 2017

RDMA+verbs stuck in some nodes #12035

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jakiechris mentioned this issue Sep 4, 2017

protobuf crashes at runtime when loading tensor lib. #12794

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zhangbo5891001 mentioned this issue Nov 29, 2017

[BUG]Out-of-Bounds Read in DecodeBmpOp class(tensorflow/core/kernels/decode_bmp_op.cc) #14959

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samhodge mentioned this issue May 22, 2018

Unknown TF crash on OSX in C++ Application, works fine on another machine, other operating systems #19426

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ychen404 mentioned this issue Aug 19, 2018

Not able to port a 6-layered mobilenet tflite model to mobile #21368

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chengdianxuezi mentioned this issue Nov 1, 2019

Bug: tensorflow-gpu takes long time before beginning to compute #18652

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arielbenitah mentioned this issue Nov 10, 2019

TensorRT Segmentation Fault During Conversion #34136

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yanceyblog mentioned this issue Nov 28, 2019

armeabi-v7a libtensorflowlite_jni.so：signal 7 (SIGBUS), code 1 (BUS_ADRALN), fault addr 0xeef5445f #34669

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cjolivier01 referenced this issue in Cerebras/tensorflow Dec 6, 2019

Merge pull request #15 from iotamudelta/rocprim-master

869b110

Integrate rocPRIM 0.3.1 milestone

Rubix982 mentioned this issue Apr 18, 2020

Unable To Find Relevant Documentation For Quantization from python/tf/dtype/DType #38673

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amitDaMan mentioned this issue May 8, 2020

Speech Command Recognition example crashes with GPUDelegate #38991

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summacod mentioned this issue Jun 18, 2020

populateTypeInferenceInfo hits assertion when generating type inference interface for tf_ops #40559

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denise-k pushed a commit to plaidml/tensorflow that referenced this issue Aug 28, 2020

Merge pull request tensorflow#15 from dgkutnic/dgkutnic/keepdims

3f7c40a

Keep dims in BatchNormTraining

This was referenced Sep 24, 2020

Didnt find op for builtin opcode 'RESIZE_NEAREST_NEIGHBOR' version '3' #43291

Closed

null pointer dereference Error in TF2.3.0 with runforMultipleInputOutput #43657

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This was referenced Nov 2, 2020

Undefined symbols for architecture arm64 when loading TensorFlowLiteSelectTfOps on iOS device #41948

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crashed at TfLiteInterpreterCreate #44513

Closed

jakobkruse1 pushed a commit to jakobkruse1/tensorflow that referenced this issue Mar 2, 2021

Merge pull request tensorflow#15 from tensorflow/master

cb277fb

Sync with upstream master

dinkdeep mentioned this issue Apr 7, 2021

Segmentation fault in tf-opt while running a tf dialect mlir file #48365

Closed

rsanthanam-amd mentioned this issue Jul 1, 2021

[ROCm] This change replaces the original assert for detecting multiple #49232

Closed

DavidvSon1 mentioned this issue Oct 3, 2021

Segmentation fault when invoking TFLite interpreter on basic quantized model tensorflow/model-optimization#857

Open

goddie1 mentioned this issue Mar 10, 2022

tensorflow core while do stdthread create #55186

Closed

ivankxt mentioned this issue Jun 12, 2023

Get deadlock after Predict(cuda10.0, cudnn7.6.5, Tesla T4 GPU) #60841

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lyz1005 mentioned this issue Oct 26, 2023

Interpreter run crash #62240

Closed

spacycoder mentioned this issue Dec 11, 2023

Why does my full integer quantized tflite model crash when loaded? #62618

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ramonhollands mentioned this issue Jun 30, 2024

Tflite model fails on Android GPU delegate due to 'null pointer dereference' #70664

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Quantized ops? #15

Quantized ops? #15

jbondc commented Nov 9, 2015

vrv commented Nov 9, 2015

jbondc commented Nov 9, 2015

martinwicke commented Dec 16, 2015

dgschwend commented Mar 2, 2016

hustqmk commented Jun 14, 2017

amitport commented Nov 7, 2020 •

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Quantized ops? #15

Quantized ops? #15

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jbondc commented Nov 9, 2015

vrv commented Nov 9, 2015

jbondc commented Nov 9, 2015

martinwicke commented Dec 16, 2015

dgschwend commented Mar 2, 2016

hustqmk commented Jun 14, 2017

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