Tensorboard——高级可视化

with tf.name_scope('SGD'):
    # Gradient Descent
    optimizer = tf.train.GradientDescentOptimizer(learning_rate)
    # Op to calculate every variable gradient
    grads = tf.gradients(loss, tf.trainable_variables())
    grads = list(zip(grads, tf.trainable_variables()))
    # Op to update all variables according to their gradient
    apply_grads = optimizer.apply_gradients(grads_and_vars=grads)

# Create summaries to visualize weights
for var in tf.trainable_variables():
    tf.summary.histogram(var.name, var)
# Summarize all gradients
for grad, var in grads:
    tf.summary.histogram(var.name + '/gradient', grad)

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https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/4_Utils/tensorboard_advanced.py