Using Tensorboard to monitor training real time and visualize the model architecture

问题

I am learning to use Tensorboard -- Tensorflow 2.0.

In particular, I would like to monitor the learning curves realtime and also to visually inspect and communicate the architecture of my model.

Below I will provide code for a reproducible example.

I have three problems:

Although I get the learning curves once the training is over I don't know what I should do to monitor them in real time
The learning curve I get from Tensorboard does not agree with the plot of history.history. In fact is bizarre and difficult to interpret its reversals.
I can not make sense of the graph. I have trained a sequential model with 5 dense layers and dropout layers in between. What Tensorboard shows me is something which much more elements in it.

My code is the following:

from keras.datasets import boston_housing

(train_data, train_targets), (test_data, test_targets) = boston_housing.load_data()

inputs = Input(shape = (train_data.shape[1], ))
x1 = Dense(100, kernel_initializer = 'he_normal', activation = 'elu')(inputs)
x1a = Dropout(0.5)(x1)
x2 = Dense(100, kernel_initializer = 'he_normal', activation = 'elu')(x1a)
x2a = Dropout(0.5)(x2)
x3 = Dense(100, kernel_initializer = 'he_normal', activation = 'elu')(x2a)
x3a = Dropout(0.5)(x3)
x4 = Dense(100, kernel_initializer = 'he_normal', activation = 'elu')(x3a)
x4a = Dropout(0.5)(x4)
x5 = Dense(100, kernel_initializer = 'he_normal', activation = 'elu')(x4a)
predictions = Dense(1)(x5)
model = Model(inputs = inputs, outputs = predictions)

model.compile(optimizer = 'Adam', loss = 'mse')

logdir="logs\\fit\\" + datetime.now().strftime("%Y%m%d-%H%M%S")
tensorboard_callback = keras.callbacks.TensorBoard(log_dir=logdir)

history = model.fit(train_data, train_targets,
          batch_size= 32,
          epochs= 20,
          validation_data=(test_data, test_targets),
          shuffle=True,
          callbacks=[tensorboard_callback ])

plt.plot(history.history['loss'])
plt.plot(history.history['val_loss'])

plt.plot(history.history['val_loss'])

来源：https://stackoverflow.com/questions/58115212/using-tensorboard-to-monitor-training-real-time-and-visualize-the-model-architec

标签

python-3.x

tensorflow

tensorboard