The kernel appears to have died. It will restart automatically.
という表示が出て止まる。
なんでかなと同じコードをターミナルから動かすと、やはり最後グラフの描画の前に
OMP: Error #15: Initializing libiomp5.dylib, but found libiomp5.dylib already initialized.
OMP: Hint This means that multiple copies of the OpenMP runtime have been linked into the program. That is dangerous, since it can degrade performance or cause incorrect results. The best thing to do is to ensure that only a single OpenMP runtime is linked into the process, e.g. by avoiding static linking of the OpenMP runtime in any library. As an unsafe, unsupported, undocumented workaround you can set the environment variable KMP_DUPLICATE_LIB_OK=TRUE to allow the program to continue to execute, but that may cause crashes or silently produce incorrect results. For more information, please see http://www.intel.com/software/products/support/.
zsh: abort python ＜ファイル名＞.py
yyyy-mm-dd hh:mm:ss: I tensorflow/core/platform/cpu_feature_guard.cc:145] This TensorFlow binary is optimized with Intel(R) MKL-DNN to use the following CPU instructions in performance critical operations: SSE4.1 SSE4.2 AVX AVX2 FMA
To enable them in non-MKL-DNN operations, rebuild TensorFlow with the appropriate compiler flags.
yyyy-mm-dd hh:mm:ss: I tensorflow/core/common_runtime/process_util.cc:115] Creating new thread pool with default inter op setting: 12. Tune using inter_op_parallelism_threads for best performance.
Traceback (most recent call last):
File "test_mul_tb.py", line 13, in <module>
sess = tf.Session()
AttributeError: module 'tensorflow' has no attribute 'Session'
[libprotobuf ERROR external/com_google_protobuf/src/google/protobuf/descriptor_database.cc:393] Invalid file descriptor data passed to EncodedDescriptorDatabase::Add().
[libprotobuf FATAL external/com_google_protobuf/src/google/protobuf/descriptor.cc:1367] CHECK failed: GeneratedDatabase()->Add(encoded_file_descriptor, size):
libc++abi.dylib: terminating with uncaught exception of type google::protobuf::FatalException: CHECK failed: GeneratedDatabase()->Add(encoded_file_descriptor, size):
zsh: abort tensorboard --logdir=./logs
というエラーが出る。
で、海外のサイトとかを見てみると、Anacondaちゃんとインストールしてあるのかといった記述をよく見る。特に、macOS Catalinaだと、ターミナルがbashではなく、zshだからanacondaが公式に出しているインストール方法使ったほうがいいと。ということで、今回はanacondaだけアンインストール（アンインストール方法は前回の記事と同じ）。その後、How to Restore Anaconda after Update to MacOS Catalinaに従って再インストール。optフォルダではなくユーザー名直下にインストールできたので、.zshrcもこのサイトの通り一度書いたものを再修正。
