Segmentation fault when importing tensorflow 2.12 in MacOS
@shkarupa-alex ~My guess is that you're on an arm64 device (M1, M2) and you're trying to use TF 2.12 under Rosetta using the main `tensorflow` package. The main `tensorflow` package only distributes binary wheels that require AVX2 instructions, which Rosetta does not support. In my experience, trying to run TensorFlow under Rosetta results in a segmentation fault like the one you experienced.~ (EDIT: Reply below indicates the environment is a core i7 (x86_64) machine. Using `tensorflow-macos` once it's released might still help 🤷‍♂️ )

This is at least in part a symptom of TensorFlow's unusual and confusing packaging practices, which results in new TensorFlow versions being released at different times for different architectures and operating systems. Instead of having a single package named `tensorflow` with binary distributions for the full set of supported architectures and operating systems, TensorFlow has three different packages, intended for use on different architectures and operating systems:
* `tensorflow`: For x86_64 processors on any operating system
* `tensorflow-macos`: For macOS systems, using either x86_64 or arm64 processors
* `tensorflow-cpu-aws`: For Linux aarch64 systems

If you want to use TensorFlow on an arm64 macOS system, you need to install `tensorflow-macos` in a native arm64 Python environment. No other combination of Python environment and TensorFlow package will work.

Unfortunately, TF 2.12 wheels have not yet been published for `tensorflow-macos`, so you'll have to wait if you want to use TF 2.12.

I'd love to someday see TF packaging return to a more conventional approach of using a single package and distributing binary wheels for each architecture and operating system as part of that single package. My guess is that there are either some challenges with TF's extremely complex build system (Bazel) or issues with TF's organizational structure that have resulted in the current package distribution approach that are unlikely to change.

If you're not particularly attached to TensorFlow, PyTorch distributes binary wheels for the most common architectures and operating systems in a single package on PyPI, and they just made their 2.0 release. I haven't tried PyTorch under Rosetta, but if that's a requirement for you it's more likely to work than TensorFlow I'm on MacOS with Core i7

>> tensorflow-macos: For macOS systems, using either x86_64 or arm64 processors
Thanks, will wait for it @shkarupa-alex,
I was able to reproduce the issue and also getting the same error which was mentioned above.
Also please have a look at the official document, currently there is no official GPU support for MacOS. 
**https://www.tensorflow.org/install/pip#macos**

It is better to post this issue here for the quick resolution and the reference.
**https://developer.apple.com/forums/thread/725592
https://developer.apple.com/forums/tags/tensorflow-metal**



```
installLibSigSegfault exception: libSegFault not found
tests/test_TFUtil.py:12: DeprecationWarning: Importing from numpy.testing.utils has been deprecated since 1.15.0, import from numpy.testing instead.
  from numpy.testing.utils import assert_almost_equal, assert_allclose
TF version: 2.11.0
Metal device set to: Apple M1 Pro


2023-03-23 17:29:40.4: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:306] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.
2023-03-23 17:29:40.4: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:272] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)
Executing: test_get_variable_grad_from_update_ops
Optimizer: <tensorflow.python.training.adam.AdamOptimizer object at 0x14e550670>
update ops: [<tf.Operation 'test_get_variable_grad_from_update_ops/Adam/update_test_get_variable_grad_from_update_ops/var/ResourceApplyAdam' type=ResourceApplyAdam>]
update op keys: ['_has_manual_control_dependencies', 'use_locking', 'T', '_class', 'use_nesterov']
update op inputs by name: ['var', 'm', 'v', 'beta1_power', 'beta2_power', 'lr', 'beta1', 'beta2', 'epsilon', 'grad']
2023-03-23 17:29:40.5: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:357] MLIR V1 optimization pass is not enabled
2023-03-23 17:29:41.5: W tensorflow/c/c_api.cc:291] Operation '{name:'test_get_variable_grad_from_update_ops/test_get_variable_grad_from_update_ops/var/Adam_1/Assign' id:60 op device:{requested: '', assigned: ''} def:{{{node test_get_variable_grad_from_update_ops/test_get_variable_grad_from_update_ops/var/Adam_1/Assign}} = AssignVariableOp[_has_manual_control_dependencies=true, dtype=DT_FLOAT, validate_shape=false](test_get_variable_grad_from_update_ops/test_get_variable_grad_from_update_ops/var/Adam_1, test_get_variable_grad_from_update_ops/test_get_variable_grad_from_update_ops/var/Adam_1/Initializer/zeros)}}' was changed by setting attribute after it was run by a session. This mutation will have no effect, and will trigger an error in the future. Either don't modify nodes after running them or create a new session.
grad: Tensor("test_get_variable_grad_from_update_ops/gradients/test_get_variable_grad_from_update_ops/sub_grad/tuple/control_dependency:0", shape=(), dtype=float32)
Optimizer: <tensorflow.python.training.gradient_descent.GradientDescentOptimizer object at 0x14e5506a0>
update ops: [<tf.Operation 'test_get_variable_grad_from_update_ops/GradientDescent/update_test_get_variable_grad_from_update_ops/var/ResourceApplyGradientDescent' type=ResourceApplyGradientDescent>]
update op keys: ['_has_manual_control_dependencies', 'use_locking', 'T', '_class']
update op inputs by name: ['var', 'alpha', 'delta']
2023-03-23 15:29:40.680: W tensorflow/c/c_api.cc:291] Operation '{name:'test_get_variable_grad_from_update_ops/test_get_variable_grad_from_update_ops/var/Adam_1/Assign' id:60 op device:{requested: '', assigned: ''} def:{{{node test_get_variable_grad_from_update_ops/test_get_variable_grad_from_update_ops/var/Adam_1/Assign}} = AssignVariableOp[_has_manual_control_dependencies=true, dtype=DT_FLOAT, validate_shape=false](test_get_variable_grad_from_update_ops/test_get_variable_grad_from_update_ops/var/Adam_1, test_get_variable_grad_from_update_ops/test_get_variable_grad_from_update_ops/var/Adam_1/Initializer/zeros)}}' was changed by setting attribute after it was run by a session. This mutation will have no effect, and will trigger an error in the future. Either don't modify nodes after running them or create a new session.
grad: Tensor("test_get_variable_grad_from_update_ops/gradients_1/test_get_variable_grad_from_update_ops/sub_grad/tuple/control_dependency:0", shape=(), dtype=float32)
Optimizer: <tensorflow.python.training.momentum.MomentumOptimizer object at 0x14e550730>
update ops: [<tf.Operation 'test_get_variable_grad_from_update_ops/Momentum/update_test_get_variable_grad_from_update_ops/var/ResourceApplyMomentum' type=ResourceApplyMomentum>]
update op keys: ['_has_manual_control_dependencies', 'use_locking', 'T', '_class', 'use_nesterov']
update op inputs by name: ['var', 'accum', 'lr', 'grad', 'momentum']
2023-03-23 19:29:40.65: W tensorflow/c/c_api.cc:291] Operation '{name:'test_get_variable_grad_from_update_ops/test_get_variable_grad_from_update_ops/var/Momentum/Assign' id:138 op device:{requested: '', assigned: ''} def:{{{node test_get_variable_grad_from_update_ops/test_get_variable_grad_from_update_ops/var/Momentum/Assign}} = AssignVariableOp[_has_manual_control_dependencies=true, dtype=DT_FLOAT, validate_shape=false](test_get_variable_grad_from_update_ops/test_get_variable_grad_from_update_ops/var/Momentum, test_get_variable_grad_from_update_ops/test_get_variable_grad_from_update_ops/var/Momentum/Initializer/zeros)}}' was changed by setting attribute after it was run by a session. This mutation will have no effect, and will trigger an error in the future. Either don't modify nodes after running them or create a new session.
grad: Tensor("test_get_variable_grad_from_update_ops/gradients_2/test_get_variable_grad_from_update_ops/sub_grad/tuple/control_dependency:0", shape=(), dtype=float32)
Fatal Python error: Segmentation fault
```
 @tilakrayal Your logs seem to indicate that you're using TensorFlow 2.11:

> TF version: 2.11.0

Since this issue is specifically for TF 2.12, it might be worth opening a new issue for your problem I've installed `tensorflow-macos 2.12.0` and got segfault when importing tensorflow Here is lldb stack:
```bash
alex@MacBook-Pro Downloads % lldb /Users/alex/.pyenv/versions/3.8.6/bin/python x.py
(lldb) target create "/Users/alex/.pyenv/versions/3.8.6/bin/python"
Current executable set to '/Users/alex/.pyenv/versions/3.8.6/bin/python' (x86_64).
(lldb) settings set -- target.run-args  "x.py"
(lldb) run
Process 38275 launched: '/Users/alex/.pyenv/versions/3.8.6/bin/python' (x86_64)
2023-04-10 16:44:06.224255: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: SSE4.1 SSE4.2 AVX AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
Process 38275 stopped
* thread #1, queue = 'com.apple.main-thread', stop reason = EXC_BAD_ACCESS (code=1, address=0x390)
    frame #0: 0x00000001587f028c _multiarray_umath.cpython-38-darwin.so`_warn_if_cast_exists_already + 76
_multiarray_umath.cpython-38-darwin.so`:
->  0x1587f028c <+76>: movq   0x390(%rax), %rax
    0x1587f0293 <+83>: movq   0x48(%rax), %rdi
    0x1587f0297 <+87>: movq   %rbx, %rsi
    0x1587f029a <+90>: callq  0x1589f5152               ; symbol stub for: PyDict_GetItemWithError
Target 0: (python) stopped.

``` @shkarupa-alex , tensorflow-macos is a community build package and it is not officially released by google.
You can build the packahe from source for MacOs by following the instructions here https://www.tensorflow.org/install/source#macos

For Intel based MacOs, you can install tensorflow package using pip. 

Below are the screenshots for MacOS i5 using `pip install tensorflow`.

![image](https://user-images.githubusercontent.com/73069040/231263808-d136870e-dc27-43c6-bf12-b4282b972738.png)

![image](https://user-images.githubusercontent.com/73069040/231263849-f949b83f-a8b6-46ff-a385-93692c1fad32.png)
 @sachinprasadhs , i've tried to install tensorflow, tensorflow-macos and build tensorflow from source. But always get segfault (starting from r2.12, 2.11 works well from pip and source).

Here is what i got when building from source:
```bash
alex@MacBook-Pro tensorflow-r2.12 % bazel build --action_env=CUDA_VISIBLE_DEVICES=-1 --config=release_cpu_macos //tensorflow/tools/pip_package:build_pip_package 
WARNING: The following configs were expanded more than once: [v2]. For repeatable flags, repeats are counted twice and may lead to unexpected behavior.
INFO: Options provided by the client:
  Inherited 'common' options: --isatty=1 --terminal_columns=241
INFO: Reading rc options for 'build' from /Users/alex/Downloads/tensorflow-r2.12/.bazelrc:
  Inherited 'common' options: --experimental_repo_remote_exec
INFO: Reading rc options for 'build' from /Users/alex/Downloads/tensorflow-r2.12/.bazelrc:
  'build' options: --define framework_shared_object=true --define tsl_protobuf_header_only=true --define=use_fast_cpp_protos=true --define=allow_oversize_protos=true --spawn_strategy=standalone -c opt --announce_rc --define=grpc_no_ares=true --noincompatible_remove_legacy_whole_archive --enable_platform_specific_config --define=with_xla_support=true --config=short_logs --config=v2 --define=no_aws_support=true --define=no_hdfs_support=true --experimental_cc_shared_library --experimental_link_static_libraries_once=false --incompatible_enforce_config_setting_visibility
INFO: Reading rc options for 'build' from /Users/alex/Downloads/tensorflow-r2.12/.tf_configure.bazelrc:
  'build' options: --action_env PYTHON_BIN_PATH=/Users/alex/.pyenv/shims/python --action_env PYTHON_LIB_PATH=/Users/alex/.pyenv/versions/3.8.6/lib/python3.8/site-packages --python_path=/Users/alex/.pyenv/shims/python
INFO: Reading rc options for 'build' from /Users/alex/Downloads/tensorflow-r2.12/.bazelrc:
  'build' options: --deleted_packages=tensorflow/compiler/mlir/tfrt,tensorflow/compiler/mlir/tfrt/benchmarks,tensorflow/compiler/mlir/tfrt/jit/python_binding,tensorflow/compiler/mlir/tfrt/jit/transforms,tensorflow/compiler/mlir/tfrt/python_tests,tensorflow/compiler/mlir/tfrt/tests,tensorflow/compiler/mlir/tfrt/tests/ir,tensorflow/compiler/mlir/tfrt/tests/analysis,tensorflow/compiler/mlir/tfrt/tests/jit,tensorflow/compiler/mlir/tfrt/tests/lhlo_to_tfrt,tensorflow/compiler/mlir/tfrt/tests/lhlo_to_jitrt,tensorflow/compiler/mlir/tfrt/tests/tf_to_corert,tensorflow/compiler/mlir/tfrt/tests/tf_to_tfrt_data,tensorflow/compiler/mlir/tfrt/tests/saved_model,tensorflow/compiler/mlir/tfrt/transforms/lhlo_gpu_to_tfrt_gpu,tensorflow/core/runtime_fallback,tensorflow/core/runtime_fallback/conversion,tensorflow/core/runtime_fallback/kernel,tensorflow/core/runtime_fallback/opdefs,tensorflow/core/runtime_fallback/runtime,tensorflow/core/runtime_fallback/util,tensorflow/core/tfrt/eager,tensorflow/core/tfrt/eager/backends/cpu,tensorflow/core/tfrt/eager/backends/gpu,tensorflow/core/tfrt/eager/core_runtime,tensorflow/core/tfrt/eager/cpp_tests/core_runtime,tensorflow/core/tfrt/gpu,tensorflow/core/tfrt/run_handler_thread_pool,tensorflow/core/tfrt/runtime,tensorflow/core/tfrt/saved_model,tensorflow/core/tfrt/graph_executor,tensorflow/core/tfrt/saved_model/tests,tensorflow/core/tfrt/tpu,tensorflow/core/tfrt/utils
INFO: Found applicable config definition build:short_logs in file /Users/alex/Downloads/tensorflow-r2.12/.bazelrc: --output_filter=DONT_MATCH_ANYTHING
INFO: Found applicable config definition build:v2 in file /Users/alex/Downloads/tensorflow-r2.12/.bazelrc: --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1
INFO: Found applicable config definition build:release_cpu_macos in file /Users/alex/Downloads/tensorflow-r2.12/.bazelrc: --config=release_base --config=avx_linux
INFO: Found applicable config definition build:release_base in file /Users/alex/Downloads/tensorflow-r2.12/.bazelrc: --config=v2 --distinct_host_configuration=false
INFO: Found applicable config definition build:v2 in file /Users/alex/Downloads/tensorflow-r2.12/.bazelrc: --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1
INFO: Found applicable config definition build:avx_linux in file /Users/alex/Downloads/tensorflow-r2.12/.bazelrc: --copt=-mavx --host_copt=-mavx
INFO: Found applicable config definition build:macos in file /Users/alex/Downloads/tensorflow-r2.12/.bazelrc: --apple_platform_type=macos --copt=-DGRPC_BAZEL_BUILD --copt=-w --define=PREFIX=/usr --define=LIBDIR=$(PREFIX)/lib --define=INCLUDEDIR=$(PREFIX)/include --define=PROTOBUF_INCLUDE_PATH=$(PREFIX)/include --cxxopt=-std=c++17 --host_cxxopt=-std=c++17
INFO: Build options --action_env and --python_path have changed, discarding analysis cache.
INFO: Analyzed target //tensorflow/tools/pip_package:build_pip_package (584 packages loaded, 34021 targets configured).
INFO: Found 1 target...
ERROR: /Users/alex/Downloads/tensorflow-r2.12/tensorflow/BUILD:1591:19: Executing genrule //tensorflow:tf_python_api_gen_v2 failed: (Segmentation fault): bash failed: error executing command /bin/bash -c ... (remaining 1 argument skipped)
2023-04-11 13:22:35.852895: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
/bin/bash: line 1: 53085 Segmentation fault: 11  bazel-out/darwin-opt/bin/tensorflow/create_tensorflow.python_api_tf_python_api_gen_v2 --root_init_template=tensorflow/api_template.__init__.py --apidir=bazel-out/darwin-opt/bin/tensorflow_api/v2/ --apiname=tensorflow --apiversion=2 --compat_apiversion=1 --compat_apiversion=2 --compat_init_template=tensorflow/compat_template_v1.__init__.py --compat_init_template=tensorflow/compat_template.__init__.py --packages=tensorflow.python,tensorflow.dtensor.python.accelerator_util,tensorflow.dtensor.python.api,tensorflow.dtensor.python.config,tensorflow.dtensor.python.d_checkpoint,tensorflow.dtensor.python.d_variable,tensorflow.dtensor.python.input_util,tensorflow.dtensor.python.layout,tensorflow.dtensor.python.mesh_util,tensorflow.dtensor.python.tpu_util,tensorflow.dtensor.python.save_restore,tensorflow.lite.python.analyzer,tensorflow.lite.python.lite,tensorflow.lite.python.authoring.authoring,tensorflow.python.modules_with_exports --output_package=tensorflow._api.v2 --use_relative_imports=True --loading=static --loading=default bazel-out/darwin-opt/bin/tensorflow/_api/v2/v2.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/autograph/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/decorator/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/dispatch/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/distribute/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/distribute/combinations/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/distribute/interim/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/distribute/multi_process_runner/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/eager_context/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/feature_column/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/function/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/graph_util/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/mixed_precision/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/monitoring/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/nest/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/ops/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/smart_cond/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/test/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/test/combinations/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/tf2/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/train/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/types/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/types/data/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/saved_model/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/saved_model/load/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__internal__/tracking/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/__operators__/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/audio/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/autograph/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/autograph/experimental/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/autodiff/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/bitwise/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/config/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/config/experimental/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/config/optimizer/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/config/threading/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/data/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/data/experimental/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/data/experimental/service/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/debugging/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/debugging/experimental/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/distribute/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/distribute/cluster_resolver/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/distribute/coordinator/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/distribute/experimental/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/distribute/experimental/coordinator/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/distribute/experimental/partitioners/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/distribute/experimental/rpc/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/dtypes/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/dtypes/experimental/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/errors/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/experimental/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/experimental/extension_type/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/experimental/dtensor/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/experimental/numpy/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/experimental/numpy/random/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/experimental/tensorrt/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/experimental/dlpack/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/feature_column/__init__.py 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bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/saved_model/builder/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/saved_model/constants/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/saved_model/experimental/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/saved_model/loader/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/saved_model/main_op/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/saved_model/signature_constants/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/saved_model/signature_def_utils/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/saved_model/tag_constants/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/saved_model/utils/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/sets/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/signal/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/sparse/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/spectral/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/summary/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/sysconfig/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/test/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/test/experimental/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/tpu/experimental/embedding/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/tpu/experimental/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/tpu/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/train/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/train/experimental/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/train/queue_runner/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/types/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/types/experimental/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/user_ops/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/version/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/xla/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/xla/experimental/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/compat/v1/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/compat/v2/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/compat/v1/compat/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v1/compat/v2/compat/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v2/compat/v1/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v2/compat/v2/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v2/compat/v1/compat/__init__.py bazel-out/darwin-opt/bin/tensorflow/_api/v2/compat/v2/compat/v2/compat/__init__.py
Target //tensorflow/tools/pip_package:build_pip_package failed to build
Use --verbose_failures to see the command lines of failed build steps.
ERROR: /Users/alex/Downloads/tensorflow-r2.12/tensorflow/python/tools/BUILD:82:10 Middleman _middlemen/tensorflow_Spython_Stools_Sfreeze_Ugraph-runfiles failed: (Segmentation fault): bash failed: error executing command /bin/bash -c ... (remaining 1 argument skipped)
INFO: Elapsed time: 8442.628s, Critical Path: 700.25s
INFO: 15803 processes: 817 internal, 14986 local.
FAILED: Build did NOT complete successfully
``` Couldn't solve this issue with different hacks.
Installed clean Python 3.11 and it start works out of the box. Are you satisfied with the resolution of your issue?
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/60081">Yes</a>
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/60081">No</a>

<details><summary>Click to expand!</summary> 
 
 ### Issue Type

Bug

### Have you reproduced the bug with TF nightly?

No

### Source

binary

### Tensorflow Version

2.12

### Custom Code

No

### OS Platform and Distribution

MacOS 13.1

### Mobile device

_No response_

### Python version

3.8.6

### Bazel version

_No response_

### GCC/Compiler version

_No response_

### CUDA/cuDNN version

_No response_

### GPU model and memory

_No response_

### Current Behaviour?

```shell
Segmentation fault when importing just upgraded TF 2.12
```


### Standalone code to reproduce the issue

```shell
alex@MacBook-Pro tfmiss % python
Python 3.8.6 (default, Jun  7 2022, 10:54:52) 
[Clang 13.1.6 (clang-1316.0.21.2.5)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
```


### Relevant log output

```shell
2023-03-23 08:47:14.945316: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
zsh: segmentation fault  python
```
</details>