Typo in getting started guide #9

maccam912 · 2015-11-09T16:36:49Z

http://tensorflow.org/get_started/basic_usage.md#variables

In the code example, 1 is being added to "counter", which is named "var" initially, but referred to as "state" later. My guess is that these are meant to refer to the same thing, and a typo in one of the variable names made it into the example code.

mdda · 2015-11-09T18:48:55Z

Apparently the fix has already been put into their pipeline.

vrv · 2015-11-09T18:51:31Z

I just pushed the fix in db0b5da

Thanks!

…d vocabulary and vocabulary processor to transform documents.

Fixes tensorflow#9: Neural translation

Continue working on neural translation model tensorflow#9. Added language model example tensorflow#64

Small update

* Upgraded to libxsmm 1.6.5 * Enable the use of libxsmm for matrix multiplications * Enable the use of libxsmm to speedup 1x1 convolutions (which are computed using matrix multiplications) * integrated LIBXSMM 1.7

* Fixed libxsmm_config_arguments: Fixed the incorrect value supposed to trigger auto-prefetch. Fixed the 0-threshold, which is now accounted for in LIBXSMM (by just populating the default threshold). The problem arised from the assumption "threshold: fallback to BLAS if n*m*k above this", which is wrong (the threshold populates an upper bound until which JIT code is generated). The previous configuration perhaps caused all sorts of issues due to other values derived from the 0-threshold. Note, explicitly JIT'ting code is/was never subject to a threshold. * Upgraded to libxsmm 1.6.5 * Enable the use of libxsmm for matrix multiplications * Enable the use of libxsmm to speedup 1x1 convolutions (which are computed using matrix multiplications) * Fixed libxsmm_config_arguments in libxsmm.BUILD (tensorflow#7) * Fixed libxsmm_config_arguments: Fixed the incorrect value supposed to trigger auto-prefetch. Fixed the 0-threshold, which is now accounted for in LIBXSMM (by just populating the default threshold). The problem arised from the assumption "threshold: fallback to BLAS if n*m*k above this", which is wrong (the threshold populates an upper bound until which JIT code is generated). The previous configuration perhaps caused all sorts of issues due to other values derived from the 0-threshold. Note, explicitly JIT'ting code is/was never subject to a threshold. * Make use of TensorFlow's allocation infrastructure even when using LIBXSMM allocation functions. In particular, the (cached) libxsmm_spmdm_init now relies on TF's cpu_allocator(). For C++ code, one can use a libxsmm_scoped_allocator<kind> in order to (temporarily) setup a different allocation mechanism. For instance, using libxsmm_tf_allocator<libxsmm_scratch_allocator> changes LIBXSMM's scratch allocator to rely on TensorFlow. The libxsmm_tf_allocator provides two kinds of c'tors: (1) the no-argument variant adopts TF's cpu_allocator(), whereas the one-argument form (2) adopts the allocator from the given OpKernelContext. Changing the allocator in LIBXSMM with pending buffers (from different allocators) is valid, and all other services in LIBXSMM's "malloc domain" work regardless of the allocation mechanism (e.g., libxsmm_malloc_size). * Simply renamed API items in order to follow changes in LIBXSMM 1.7. This is incomplete as more changes/adjustments are needed. * Account for removed non-check API. * Include libxsmm_malloc.h now that libxsmm_tf_allocator is used. * Renamed libxsmm_dnn_create_conv_handle to libxsmm_dnn_create_conv_layer. * Renamed LIBXSMM_DNN_CONV_FORMAT_* to LIBXSMM_DNN_TENSOR_FORMAT_*. * Renamed libxsmm_dnn_destroy_conv_handle to libxsmm_dnn_destroy_conv_layer. * Include missing header file (libxsmm_malloc.h). * Renamed LIBXSMM_DNN_CONV_KIND_* to LIBXSMM_DNN_COMPUTE_KIND_*. * Account for the fact that datatype_in/out is now only datatype (libxsmm_dnn_conv_desc structure). * Updated to new libxsmm_dnn_link_* functions. * Updated to use new libxsmm_dnn_bind_* functions. * Fixed calling libxsmm_dnn_transpose_filter. * Updates in preparation of LIBXSMM 1.7 (tensorflow#8) * Fixed libxsmm_config_arguments: Fixed the incorrect value supposed to trigger auto-prefetch. Fixed the 0-threshold, which is now accounted for in LIBXSMM (by just populating the default threshold). The problem arised from the assumption "threshold: fallback to BLAS if n*m*k above this", which is wrong (the threshold populates an upper bound until which JIT code is generated). The previous configuration perhaps caused all sorts of issues due to other values derived from the 0-threshold. Note, explicitly JIT'ting code is/was never subject to a threshold. * Upgraded to libxsmm 1.6.5 * Enable the use of libxsmm for matrix multiplications * Enable the use of libxsmm to speedup 1x1 convolutions (which are computed using matrix multiplications) * Make use of TensorFlow's allocation infrastructure even when using LIBXSMM allocation functions. In particular, the (cached) libxsmm_spmdm_init now relies on TF's cpu_allocator(). For C++ code, one can use a libxsmm_scoped_allocator<kind> in order to (temporarily) setup a different allocation mechanism. For instance, using libxsmm_tf_allocator<libxsmm_scratch_allocator> changes LIBXSMM's scratch allocator to rely on TensorFlow. The libxsmm_tf_allocator provides two kinds of c'tors: (1) the no-argument variant adopts TF's cpu_allocator(), whereas the one-argument form (2) adopts the allocator from the given OpKernelContext. Changing the allocator in LIBXSMM with pending buffers (from different allocators) is valid, and all other services in LIBXSMM's "malloc domain" work regardless of the allocation mechanism (e.g., libxsmm_malloc_size). * Simply renamed API items in order to follow changes in LIBXSMM 1.7. This is incomplete as more changes/adjustments are needed. * Account for removed non-check API. * Include libxsmm_malloc.h now that libxsmm_tf_allocator is used. * Renamed libxsmm_dnn_create_conv_handle to libxsmm_dnn_create_conv_layer. * Renamed LIBXSMM_DNN_CONV_FORMAT_* to LIBXSMM_DNN_TENSOR_FORMAT_*. * Renamed libxsmm_dnn_destroy_conv_handle to libxsmm_dnn_destroy_conv_layer. * Include missing header file (libxsmm_malloc.h). * Renamed LIBXSMM_DNN_CONV_KIND_* to LIBXSMM_DNN_COMPUTE_KIND_*. * Account for the fact that datatype_in/out is now only datatype (libxsmm_dnn_conv_desc structure). * Updated to new libxsmm_dnn_link_* functions. * Updated to use new libxsmm_dnn_bind_* functions. * Fixed calling libxsmm_dnn_transpose_filter. * integrated LIBXSMM 1.7 * support for LIBXSMM 1.7 (tensorflow#9) * Upgraded to libxsmm 1.6.5 * Enable the use of libxsmm for matrix multiplications * Enable the use of libxsmm to speedup 1x1 convolutions (which are computed using matrix multiplications) * integrated LIBXSMM 1.7 * updated LIBXSMM to 1.7.1 * updated to LIBXSMM 1.7.1 (tensorflow#10) * Upgraded to libxsmm 1.6.5 * Enable the use of libxsmm for matrix multiplications * Enable the use of libxsmm to speedup 1x1 convolutions (which are computed using matrix multiplications) * integrated LIBXSMM 1.7 * updated LIBXSMM to 1.7.1 * merge alheinecke master (tensorflow#11) * Upgraded to libxsmm 1.6.5 * Enable the use of libxsmm for matrix multiplications * Enable the use of libxsmm to speedup 1x1 convolutions (which are computed using matrix multiplications) * integrated LIBXSMM 1.7 * updated LIBXSMM to 1.7.1 * Take new translation units into account (LIBXSMM 1.8). * Account for adjusted header dependency in LIBXSMM (TODO: API to avoid incl. header from LIBXSMM's src). * Trigger rebuild if template changed (LIBXSMM).

Update master from upstream

added xcore implementation of micro_time timer functions

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 ```

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vrv closed this as completed Nov 9, 2015

astellato mentioned this issue Nov 18, 2015

Android App Crash On Start #280

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wchan mentioned this issue Jan 7, 2016

failed to query current context: CUDA_ERROR_DEINITIALIZED #713

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ilblackdragon added a commit to ilblackdragon/tensorflow that referenced this issue Mar 9, 2016

Working on tensorflow#9: Added preprocessing for text: tokenizer, wor…

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…d vocabulary and vocabulary processor to transform documents.

ilblackdragon added a commit to ilblackdragon/tensorflow that referenced this issue Mar 9, 2016

Merge pull request tensorflow#66 from google/neural-translation

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Fixes tensorflow#9: Neural translation

ilblackdragon added a commit to ilblackdragon/tensorflow that referenced this issue Mar 9, 2016

Merge pull request tensorflow#74 from tensorflow/neural-translation

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Continue working on neural translation model tensorflow#9. Added language model example tensorflow#64

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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wagonhelm mentioned this issue Jun 30, 2016

Android Tensorflow Crashes w/ Custom Graph #3117

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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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jthoth mentioned this issue Sep 16, 2016

Error with my own model trained in android demo #4407

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benoitsteiner added a commit to benoitsteiner/tensorflow that referenced this issue Nov 15, 2016

Merge pull request tensorflow#9 from lukeiwanski/master

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Small update

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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beniroquai mentioned this issue Dec 18, 2016

[Android] Put large .pb files outside of Asset-folder? [ERROR]: Check failed: message->ParseFromZeroCopyStream(&lis) #6213

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vahidk mentioned this issue Jan 27, 2017

Tensorflow freezes on iOS during Session::Run #7108

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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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Panaetius mentioned this issue Mar 20, 2017

Floating Point Exception/SIGFPE in tf.map_fn over an empty tensor #8554

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DeepakG19 mentioned this issue Sep 29, 2020

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

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fabiogeraci mentioned this issue Oct 21, 2020

TensorFlow on Dell XPS 9300 #44206

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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

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MykolaMoshak pushed a commit to tum-ei-eda/tensorflow that referenced this issue Nov 6, 2020

Merge pull request tensorflow#9 from tensorflow/master

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Update master from upstream

zhangsanfeng86 mentioned this issue Nov 11, 2020

LeakSanitizer: detected memory leaks #44714

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gnthibault mentioned this issue Nov 14, 2020

tf.data.Dataset.list_files result in segfault #44878

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sunzhe09 mentioned this issue Nov 27, 2020

ResizeBilinear op with half_pixel_centers true not support by nnapi #45207

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keithm-xmos referenced this issue in xmos/tensorflow Feb 1, 2021

Merge pull request #9 from xmos/feature/micro_profiler

0505e17

added xcore implementation of micro_time timer functions

DanielMao2015 mentioned this issue Mar 16, 2021

error about Kernel8bitNeonDotprodOutOfOrder occurs when running int8 CPU inference by tflite #47834

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limdlh mentioned this issue Apr 6, 2021

tensorflow-2.4.1 crash by pthread_mutex_lock while enable Hexagon #48325

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dinkdeep mentioned this issue Apr 7, 2021

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

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wang5566 mentioned this issue May 12, 2021

TensorRT Segmentation Fault During Conversion For Debug Mode #49139

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xieyi4650 mentioned this issue May 31, 2021

build tensorflow 1.15 from source code based on cuda 11 #49923

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rsanthanam-amd mentioned this issue Jul 1, 2021

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

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DavidvSon1 mentioned this issue Oct 3, 2021

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

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goddie1 mentioned this issue Mar 10, 2022

tensorflow core while do stdthread create #55186

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haolujun mentioned this issue Sep 28, 2022

dlopen _tensor_forest_ops.so failed cause dead lock #57886

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iammeizu mentioned this issue May 10, 2023

tensorflow1.7 hangs at LocalMaster::RunStep with tf.train.MonitoredTrainingSession in sync mode #24338

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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

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CarloWood mentioned this issue Nov 11, 2023

cuDNN, cuFFT, and cuBLAS Errors #62075

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spacycoder mentioned this issue Dec 11, 2023

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

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[xla:cpu] NFC: Remove deprecated XLA:CPU mlir based codegen part #9

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Typo in getting started guide #9

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Typo in getting started guide #9

Typo in getting started guide #9

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maccam912 commented Nov 9, 2015

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