$ make create-container
$ make
$ make jupyter

$ make create-image
$ make create-container
$ make
$ make jupyter

according to [https://dev.classmethod.jp/machine-learning/bert-text-embedding/]

1. access to [http://projector.tensorflow.org/]
2. upload; push load button and choose output.txt an input.txt
3. validate with t-SNE.

I almost write down work log to Dockerfile.

Some fixies to bert.

1. tf_upgrade_v2
2. adapt tf2;
   • tf.flags -> tf.compat.v1.flags
   • tf.contrib.layers.layer_norm -> tf.keras.layers.LayerNormalization
3. change tokenizer to use Juman++

• http://nlp.ist.i.kyoto-u.ac.jp/index.php?BERT%E6%97%A5%E6%9C%AC%E8%AA%9EPretrained%E3%83%A2%E3%83%87%E3%83%AB
• https://dev.classmethod.jp/machine-learning/bert-text-embedding/