eaad03cd8e49a57b425bfc01fa87d8da641655f6,vgg.py,,train,#Any#Any#,308

Before Change

    apply_gradient_op = opt.apply_gradients(grads, global_step=global_step)

    // Add histograms for trainable variables.
    for var in tf.trainable_variables():
        tf.histogram_summary(var.op.name, var)

    // Add histograms for gradients.
    for grad, var in grads:
        if grad is not None:
            tf.histogram_summary(var.op.name + "/gradients", grad)

After Change

    opt = tf.train.MomentumOptimizer(learning_rate, MOMENTUM)
    train_op = opt.minimize(total_loss, global_step=global_step)

    return learning_rate_summary, train_op


def get_model(images, train_phase):

Instances