categorical_columns の生成：
<![CDATA[>>> CATEGORIES = {
... 'sex': ['male', 'female'],
... 'class' : ['First', 'Second', 'Third'],
... 'deck' : ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J'],
... 'embark_town' : ['Cherbourg', 'Southhampton', 'Queenstown'],
... 'alone' : ['y', 'n']
... }
>>> categorical_columns = []
>>> for feature, vocab in CATEGORIES.items():
... cat_col = tf.feature_column.categorical_column_with_vocabulary_list(
... key=feature, vocabulary_list=vocab)
... categorical_columns.append(tf.feature_column.indicator_column(cat_col))
...
>>> ]]>
categorical_columns の内容チェック：
<![CDATA[>>> categorical_columns
[IndicatorColumn(categorical_column=VocabularyListCategoricalColumn(
key='sex',
vocabulary_list=('male', 'female'),
dtype=tf.string, default_value=-1, num_oov_buckets=0)),
IndicatorColumn(categorical_column=VocabularyListCategoricalColumn(
key='class',
vocabulary_list=('First', 'Second', 'Third'),
dtype=tf.string, default_value=-1, num_oov_buckets=0)),
IndicatorColumn(categorical_column=VocabularyListCategoricalColumn(
key='deck',
vocabulary_list=('A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J'),
dtype=tf.string, default_value=-1, num_oov_buckets=0)),
IndicatorColumn(categorical_column=VocabularyListCategoricalColumn(
key='embark_town',
vocabulary_list=('Cherbourg', 'Southhampton', 'Queenstown'),
dtype=tf.string, default_value=-1, num_oov_buckets=0)),
IndicatorColumn(categorical_column=VocabularyListCategoricalColumn(
key='alone',
vocabulary_list=('y', 'n'), dtype=tf.string,
default_value=-1, num_oov_buckets=0))]]]>
categorical_columns の機能テスト
categorical_layer を作成：
<![CDATA[>>> categorical_layer = tf.keras.layers.DenseFeatures(categorical_columns)
>>> categorical_layer
<tensorflow.python.feature_column.dense_features.DenseFeatures object at 0x6414dbb0>]]>
packed_train_data からバッチを１つとって，categorical_layer に入力：
<![CDATA[>>> for batch in packed_train_data.take(1):
... print( categorical_layer(batch).numpy()[0] )
...
Traceback (most recent call last):
File "<stdin>", line 2, in <module>
File "/home/pi/venv/lib/python3.7/site-packages/
tensorflow_core/python/keras/engine/base_layer.py",
line 913, in __call__outputs = self.call(cast_inputs, *args, **kwargs)
File "/home/pi/venv/lib/python3.7/site-packages/
tensorflow_core/python/feature_column/dense_features.py",
line 129, in call features)
ValueError: ('We expected a dictionary here. Instead we got: ',
(OrderedDict([
('sex', <tf.Tensor: shape=(5,), dtype=string, numpy=array([b'male', b'female', b'male', b'female', b'male'],
dtype=object)>),
('class', <tf.Tensor: shape=(5,), dtype=string, numpy=array([b'Third', b'First', b'Third', b'Second', b'First'],
dtype=object)>),
('deck', <tf.Tensor: shape=(5,), dtype=string, numpy=array([b'unknown', b'E', b'unknown', b'unknown', b'B'],
dtype=object)>),
('embark_town', <tf.Tensor: shape=(5,), dtype=string, numpy=array([b'Queenstown', b'Southampton',
b'Southampton', b'Southampton', b'Southampton'], dtype=object)>),
('alone', <tf.Tensor: shape=(5,), dtype=string, numpy=array([b'y', b'n', b'y', b'y', b'n'], dtype=object)>),
('numeric', <tf.Tensor: shape=(5, 4), dtype=float32, numpy=
array([[28. , 0. , 0. , 7.75],
[33. , 1. , 0. , 53.1 ],
[20. , 0. , 0. , 8.05],
[35. , 0. , 0. , 21. ],
[31. , 1. , 0. , 57. ]],
dtype=float32)>)
]),
<tf.Tensor: shape=(5,), dtype=int32, numpy=array([0, 1, 0, 1, 1])>)]]>
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