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# tensorboard --logdir import tensorflow as tfimport datetime mnist = tf.keras.datasets.mnist (x_train, y_train),(x_test, y_test) = mnist.load_data()x_train, x_test = x_train / 255.0, x_test /255.0 def create_model(): return tf.keras.models.Sequential([ tf.keras.layers.Flatten(input_shape=(28, 28)), tf.keras.layers.Dense(512, activation='relu'), tf.keras.layers.Dropout(0.2), tf.keras.layers.Dense(10, activation='softmax') ]) model = create_model()model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy']) log_dir = "logs/fit/" + datetime.datetime.now().strftime("%Y%m%d-%H%M%S")tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1) model.fit(x=x_train, y=y_train, epochs=5, validation_data=(x_test, y_test), callbacks=[tensorboard_callback])
→TensorBoard
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*起動
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# tensorboard --logdir logs/fit
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[[File:tensorboard01.png|500px]]
==Tips==
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