質問編集履歴
9
仮の解決方法を追加
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**参考記事**
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[https://teratail.com/questions/272051](http://teratail.com/questions/272051)
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---
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**仮の解決方法**
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作成した活性化関数の引数alphaにデフォルト値(alpha=10)を与えましたが、理想は層毎に引数を与えたいです。
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```python
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#活性化関数作成
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def palametric_softpluse(x, alpha= 10):
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return tf.math.log(alpha + tf.math.exp(alpha*x))
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#モデル作成
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def define_model():
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inputs = Input(shape=(32, 32, 3))
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x = Conv2D(64, (3, 3), padding='SAME')(inputs)
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x = Activation(palametric_softpluse)(x)
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x = Conv2D(64, (3, 3), padding='SAME')(x)
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x = Activation(palametric_softpluse)(x)
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x = Dropout(0.25)(x)
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x = MaxPooling2D()(x)
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x = Conv2D(128, (3,3), padding='SAME')(x)
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x = Activation(palametric_softpluse)(x)
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x = Conv2D(128, (3,3), padding='SAME')(x)
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x = Activation(palametric_softpluse)(x)
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x = Dropout(0.25)(x)
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x = MaxPooling2D()(x)
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x = Conv2D(256, (3,3), padding='SAME')(x)
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x = palametric_softpluse(x)
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x = Conv2D(256, (3,3), padding='SAME')(x)
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x = Activation(palametric_softpluse)(x)
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x = GlobalAveragePooling2D()(x)
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x = Dense(1024)(x)
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x = Activation(palametric_softpluse)(x)
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x = Dropout(0.25)(x)
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y = Dense(10, activation='softmax')(x)
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model = Model(inputs, y)
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# モデルのコンパイル。
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model.compile(optimizer=tf.keras.optimizers.Adam(),
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loss='categorical_crossentropy',
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metrics=['accuracy'])
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model.summary()
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return model
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model = define_model()
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```
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8
タイトル変更
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自作の活性化関数を作成し、利用したい
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自作の活性化関数を作成したい
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参考記事を参考にし
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7
活性化関数のnpをtf.mathに変更
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def palametric_softpluse(x, alpha):
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return tf.math.log(alpha +
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return tf.math.log(alpha + tf.math.exp(alpha*x))
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```
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6
修正
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**参考記事**
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[http
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[https://teratail.com/questions/272051](http://teratail.com/questions/272051)
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5
修正
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**参考記事**
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[http://https://teratail.com/questions/272051](http://teratail.com/questions/272051)
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4
参考記事修正
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**参考記事**
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[
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[テラテイル](http://https://teratail.com/questions/272051)
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3
参考記事
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**参考記事**
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[http://https://teratail.com/questions/272051](http://https://teratail.com/questions/272051)
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[http://https://teratail.com/questions/272051] (http://https://teratail.com/questions/272051)
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2
修正しました。
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**参考記事**
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[https://teratail.com/questions/272051](http://https://teratail.com/questions/272051)
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[http://https://teratail.com/questions/272051](http://https://teratail.com/questions/272051)
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関数のミス修正
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def palametric_softpluse(x, alpha):
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return tf.math.log(alpha + np.exp(alpha
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return tf.math.log(alpha + np.exp(alpha*x))
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```
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