回答編集履歴
3
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test
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```
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## input_shape を指定するバージョン
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```python
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from tensorflow import keras
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batch_size = 128
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num_class = 10
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epochs = 20
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(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()
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x_train, x_test = x_train / 255.0, x_test / 255.0
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x_train = x_train.reshape(len(x_train), -1)
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x_test = x_test.reshape(len(x_test), -1)
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y_train = keras.utils.to_categorical(y_train)
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y_test = keras.utils.to_categorical(y_test)
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model = keras.models.Sequential(
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[
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keras.layers.Dense(512, activation="relu", input_shape=(784,)),
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keras.layers.Dropout(0.2),
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keras.layers.Dense(512, activation="relu"),
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keras.layers.Dropout(0.2),
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keras.layers.Dense(num_class, activation="softmax"),
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]
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)
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model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=["accuracy"])
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model.fit(
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x_train,
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y_train,
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batch_size=batch_size,
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epochs=epochs,
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validation_data=(x_test, y_test),
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)
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```
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2
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CHANGED
@@ -31,3 +31,77 @@
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[kerasのmnistのサンプルを読んでみる - Qiita](https://qiita.com/ash8h/items/29e24fc617b832fba136)
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----
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## 追記
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自分の環境 TensorFlow `2.0.0-alpha0` では以下のコードで動きました。
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```python
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from tensorflow import keras
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batch_size = 128
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num_class = 10
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epochs = 20
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(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()
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x_train, x_test = x_train / 255.0, x_test / 255.0
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y_train = keras.utils.to_categorical(y_train)
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y_test = keras.utils.to_categorical(y_test)
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model = keras.models.Sequential(
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[
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keras.layers.Flatten(),
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keras.layers.Dense(512, activation="relu"),
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keras.layers.Dropout(0.2),
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keras.layers.Dense(10, activation="softmax"),
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]
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)
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model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=["accuracy"])
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model.fit(
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x_train,
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y_train,
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batch_size=256,
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epochs=10,
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validation_data=(x_test, y_test),
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)
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```
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1
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test
CHANGED
@@ -30,4 +30,4 @@
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-
[
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[kerasのmnistのサンプルを読んでみる - Qiita](https://qiita.com/ash8h/items/29e24fc617b832fba136)
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