CODEWITHSUNDEEP
kerastensorboard
Luca Thiede
Luca Thiede

Reputation: 3443

Understanding tensorboard images

I want to use keras+tensorboard. My architecture looks like this:

tbCallBack = TensorBoard(log_dir='./logs', histogram_freq=2, batch_size=32, write_graph=True, write_grads=True, write_images=True)

K.clear_session()
sess = tf.Session()
K.set_session(sess)

input_img = Input(shape=(augmented_train_data[0].shape[0], augmented_train_data[0].shape[1], 3))

x = Conv2D(8, (1, 1), padding='same', activation='relu', name="1x1_1")(input_img)
x = Conv2D(16, (3, 3), padding='same', activation='relu', name="3x3_1")(x)
x = Conv2D(32, (3, 3), padding='same', activation='relu', name="3x3_2")(x)
x = Conv2D(1, (1, 1), padding='same', activation='relu', name="1x1_2")(x)
x = Flatten()(x)
x = Dense(16, activation='relu')(x)


output = Dense(2)(x)

model = Model(inputs=input_img, outputs=output)
model.compile(optimizer='adam', loss='mean_squared_error')

#tbCallBack.set_model(model)
print(model.summary())

history = model.fit(augmented_train_data, augmented_train_label, validation_data=[augmented_validation_data, augmented_validation_label] ,epochs=20, batch_size=32, callbacks=[tbCallBack])

When looking at the tensorboard image tab, it looks like thisenter image description here I cant quite interpret that though, I thought this tab would show how the weights of my convolutions develop over the epochs. So, how to interpret these images. Or did I do a mistake in setting up tensorboard?

Upvotes: 6

Views: 620

Answers (1)

papayiannis
papayiannis

Reputation: 114

It looks like that is exactly what you are getting. The grayscale of the image shows the weights. The slider on top can be used to go back and forth in epochs and hence look at the training progression.

Upvotes: 2

Related Questions