回答編集履歴
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@@ -49,3 +49,95 @@
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## 追記
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Model.summary() で各レイヤーの出力を確認できます。
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```python
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from keras.models import Sequential
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from keras.layers import Conv2D, MaxPooling2D, Dropout, Flatten, Dense
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model = Sequential()
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model.add(Conv2D(32, kernel_size=(3, 3), activation='relu', input_shape=(28, 28, 1)))
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model.add(Conv2D(64, (3, 3), activation='relu'))
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model.add(MaxPooling2D(pool_size=(2, 2)))
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model.add(Dropout(0.25))
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model.add(Flatten())
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model.add(Dense(128, activation='relu'))
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model.add(Dropout(0.5))
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model.add(Dense(10, activation='softmax'))
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model.summary()
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```
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```python
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_________________________________________________________________
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Layer (type) Output Shape Param #
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=================================================================
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conv2d_1 (Conv2D) (None, 26, 26, 32) 320
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_________________________________________________________________
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conv2d_2 (Conv2D) (None, 24, 24, 64) 18496
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_________________________________________________________________
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max_pooling2d_1 (MaxPooling2 (None, 12, 12, 64) 0
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_________________________________________________________________
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dropout_1 (Dropout) (None, 12, 12, 64) 0
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_________________________________________________________________
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flatten_1 (Flatten) (None, 9216) 0
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_________________________________________________________________
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dense_1 (Dense) (None, 128) 1179776
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_________________________________________________________________
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dropout_2 (Dropout) (None, 128) 0
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_________________________________________________________________
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dense_2 (Dense) (None, 10) 1290
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=================================================================
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Total params: 1,199,882
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Trainable params: 1,199,882
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Non-trainable params: 0
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_________________________________________________________________
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```
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